Commit
•
28fc101
0
Parent(s):
Deploy app
Browse files- LICENSE.md +21 -0
- README.md +11 -0
- data/documents_metadata.csv +431 -0
- requirements.txt +6 -0
- src/app_utils.py +191 -0
- src/buster/assets/index.html +1 -0
- src/buster/buster_app.py +677 -0
- src/buster/gradio_app.py +8 -0
- src/cfg.py +252 -0
- src/feedback.py +200 -0
LICENSE.md
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The MIT License (MIT)
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Copyright (c) 2023 MILA - Institut quebecois d'intelligence artificielle
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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title: AIR 💬
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emoji: 🌎
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colorFrom: pink
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colorTo: green
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sdk: gradio
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sdk_version: 3.50.2
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app_file: src/buster/gradio_app.py
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python: 3.11
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pinned: false
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---
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data/documents_metadata.csv
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| 1 |
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Source,Title,Year,Country,Link
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| 2 |
+
LimeSurvey v2,Strategy for Augmenting Intelligence Using Machines AIM,2019,United States,https://www.dni.gov/files/ODNI/documents/AIM-Strategy.pdf
|
| 3 |
+
LimeSurvey v2,TRIBUNALE ORDINARIO di BOLOGNA: Sezione Lavoro,2022,Italy,https://www.bollettinoadapt.it/wp-content/uploads/2021/01/Ordinanza-Bologna.pdf
|
| 4 |
+
LimeSurvey v2,BOLETÍN OFICIAL DEL ESTADO,2023,Spain,https://www.boe.es/boe/dias/2023/06/03/pdfs/BOE-A-2023-13313.pdf
|
| 5 |
+
LimeSurvey v2,US Air Force AI Annex to the Department of Defense AI Strategy,2019,United States,https://www.af.mil/Portals/1/documents/5/USAF-AI-Annex-to-DoD-AI-Strategy.pdf
|
| 6 |
+
LimeSurvey v2,Australias Artificial Intelligence Action Plan,2021,Australia,https://wp.oecd.ai/app/uploads/2021/12/Australia_AI_Action_Plan_2021.pdf
|
| 7 |
+
LimeSurvey v2,Office of National Higher Education Science Research and Innovation Policy Council,2020,Thailand,https://waa.inter.nstda.or.th/stks/pub/2020/20200717-conference-ethics.pdf
|
| 8 |
+
LimeSurvey v2,National Strategy for Critical and Emerging Technologies,2020,United States,https://trumpwhitehouse.archives.gov/wp-content/uploads/2020/10/National-Strategy-for-CET.pdf
|
| 9 |
+
LimeSurvey v2,White House Summit on AI in Government,2019,United States,https://trumpwhitehouse.archives.gov/wp-content/uploads/2019/09/Summary-of-White-House-Summit-on-AI-in-Government-September-2019.pdf
|
| 10 |
+
LimeSurvey v2,White House Summit on AI for American Industry,2022,United States,https://trumpwhitehouse.archives.gov/wp-content/uploads/2018/05/Summary-Report-of-White-House-AI-Summit.pdf
|
| 11 |
+
LimeSurvey v2,Knowledge and Innovation Agenda,2021,Netherlands,https://topsectoragrifood.nl/wp-content/uploads/2018/04/Kennis-en-innovatieagenda-EN.pdf
|
| 12 |
+
LimeSurvey v2,Spanish RDI Strategy In Artificial Intelligence,2021,Spain,https://www.ciencia.gob.es/dam/jcr:5af98ba2-166c-4e63-9380-4f3f68db198e/Estrategia_Inteligencia_Artificial_IDI.pdf
|
| 13 |
+
LimeSurvey v2,Data Protection Ombudsman Fines Kymen Vesi Oy,2022,Finland,https://tietosuoja.fi/documents/6927448/22406974/Ty%C3%B6ntekij%C3%B6iden+sijaintitietojen+k%C3%A4sittely+ja+vaikutustenarviointi.pdf/2d04e545-d427-8a0d-3f4d-967de7b428ac/Ty%C3%B6ntekij%C3%B6iden+sijaintitietojen+k%C3%A4sittely+ja+vaikutustenarviointi.pdf
|
| 14 |
+
LimeSurvey v2,2020 Federal Data Strategy Action Plan,2022,United States,https://strategy.data.gov/assets/docs/2020-federal-data-strategy-action-plan.pdf
|
| 15 |
+
LimeSurvey v2,ARTIFICIAL INTELLIGENCE FOR SOCIAL GOOD IN LATIN AMERICA AND THE CARIBBEAN: The Regional Landscape and 12 Country Snapshots,2021,Argentina,https://publications.iadb.org/publications/english/document/Artificial-Intelligence-for-Social-Good-in-Latin-America-and-the-Caribbean-The-Regional-Landscape-and-12-Country-Snapshots.pdf
|
| 16 |
+
LimeSurvey v2,Global Partnership on AI,2023,Serbia,https://prosveta.gov.rs/wp-content/uploads/2021/12/akcioni-plan-strategija-vestacke-inteligencije.pdf
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| 17 |
+
LimeSurvey v2,Public tender for the technical work to be performed within the programme,2023,Spain,https://portal.mineco.gob.es/RecursosNoticia/mineco/prensa/noticias/2022/20221213_plan_algoritmos_verdes.pdf
|
| 18 |
+
LimeSurvey v2,Mauritius AI Council,2022,Mauritius,https://ncb.govmu.org/ncb/strategicplans/MauritiusAIStrategy2018.pdf
|
| 19 |
+
LimeSurvey v2,POLÍTICA NACIONAL DE INTELIGENCIA ARTIFICIAL,2019,Chile,https://minciencia.gob.cl/uploads/filer_public/bc/38/bc389daf-4514-4306-867c-760ae7686e2c/documento_politica_ia_digital_.pdf
|
| 20 |
+
LimeSurvey v2,Egypts National AI Strategy,2021,Egypt,https://mcit.gov.eg/Upcont/Documents/Publications_672021000_Egypt-National-AI-Strategy-English.pdf
|
| 21 |
+
LimeSurvey v2,Action Plan,2022,Turkey,https://inhak.adalet.gov.tr/Resimler/SayfaDokuman/1262021081047Action_Plan_On_Human_Rights.pdf
|
| 22 |
+
LimeSurvey v2,Kenyas Digital Economy Strategy,2021,Kenya,https://ict.go.ke/wp-content/uploads/2020/08/10TH-JULY-FINAL-COPY-DIGITAL-ECONOMY-STRATEGY-DRAFT-ONE.pdf
|
| 23 |
+
LimeSurvey v2,Federal Data Strategy,2022,United States,https://strategy.data.gov/assets/docs/2020-federal-data-strategy-framework.pdf
|
| 24 |
+
LimeSurvey v2,National Initiative for Secured Intelligent Systems,2022,Israel,https://icrc.tau.ac.il/sites/cyberstudies-english.tau.ac.il/files/media_server/cyber%20center/The%20National%20Initiative_eng%202021_digital.pdf
|
| 25 |
+
LimeSurvey v2,National AI Initiative Act of 2020,2021,United States,https://www.congress.gov/116/crpt/hrpt617/CRPT-116hrpt617.pdf#page=1210
|
| 26 |
+
LimeSurvey v2,A legal framework for artificial intelligence,2022,Switzerland,https://www.dsi.uzh.ch/dam/jcr:3a0cb402-c3b3-4360-9332-f800895fdc58/dsi-strategy-lab-21-de.pdf
|
| 27 |
+
LimeSurvey v2,Governing Innovation,2021,Japan,https://www.meti.go.jp/press/2020/07/20200713001/20200713001-2.pdf
|
| 28 |
+
LimeSurvey v2,Governance Innovation ver2 A Guide to Designing and Implementing Agile Governance,2021,Japan,https://www.meti.go.jp/english/press/2021/pdf/0219_004a.pdf
|
| 29 |
+
LimeSurvey v2,Strategy for the Development of Artificial Intelligence in the Republic of Serbia for the period 2020-2025,2022,Serbia,https://www.media.srbija.gov.rs/medsrp/dokumenti/strategy_artificial_intelligence.pdf
|
| 30 |
+
LimeSurvey v2,Artificial Intelligence Strategy of the German Federal Government,2019,Germany,https://www.ki-strategie-deutschland.de/files/downloads/Fortschreibung_KI-Strategie_engl.pdf
|
| 31 |
+
LimeSurvey v2,Artificial Intelligence Strategic Programme 2022 2024,2021,Italy,https://www.mise.gov.it/images/stories/documenti/Strategia-Nazionale-Intelligenza-Artificiale-Bozza-Consultazione.pdf
|
| 32 |
+
LimeSurvey v2,Portugals National Strategy for Artificial Intelligence,2019,Portugal,https://www.incode2030.gov.pt/en/wp-content/uploads/2022/01/julho_incode_brochura.pdf
|
| 33 |
+
LimeSurvey v2,Plan for Federal Engagement in Developing Technical Standards and Related Tools,2019,United States,https://www.nist.gov/system/files/documents/2019/08/10/ai_standards_fedengagement_plan_9aug2019.pdf
|
| 34 |
+
LimeSurvey v2,Addition of Software Specially Designed To Automate the Analysis of Geospatial Imagery to the Export Control Classification Number 0Y521 Series,2021,United States,https://www.govinfo.gov/content/pkg/FR-2020-01-06/pdf/2019-27649.pdf
|
| 35 |
+
LimeSurvey v2,National Institute of Standards and Technology Principles for Explainable AI,2021,United States,https://www.nist.gov/system/files/documents/2020/08/17/NIST%20Explainable%20AI%20Draft%20NISTIR8312%20%281%29.pdf
|
| 36 |
+
LimeSurvey v2,AI and Society,2022,United States,https://www.nsf.gov/pubs/2019/nsf19018/nsf19018.pdf
|
| 37 |
+
LimeSurvey v2,National Defense Authorization Act for Fiscal Year 2021,2022,United States,https://www.govinfo.gov/content/pkg/BILLS-116hr6395enr/pdf/BILLS-116hr6395enr.pdf
|
| 38 |
+
LimeSurvey v2,NITRD NAIIO Supplement to the Presidents FY2022 Budget,2021,United States,https://www.nitrd.gov/pubs/FY2022-NITRD-NAIIO-Supplement.pdf
|
| 39 |
+
LimeSurvey v2,National AI RD Strategic Plan 2019 Update,2019,United States,https://www.nitrd.gov/pubs/National-AI-RD-Strategy-2019.pdf
|
| 40 |
+
LimeSurvey v2,National AI RD Strategic Plan,2022,United States,https://www.nitrd.gov/pubs/national_ai_rd_strategic_plan.pdf
|
| 41 |
+
LimeSurvey v2,PROJECTS OF SCIENTIFIC RESEARCH AND TECHNOLOGICAL DEVELOPMENT IN DATA SCIENCE AND ARTIFICIAL INTELLIGENCE IN PUBLIC ADMINISTRATION,2023,Portugal,https://www.fct.pt/wp-content/uploads/2022/06/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf
|
| 42 |
+
LimeSurvey v2,National Landcover mapping project,2021,Ireland,https://www.npws.ie/sites/default/files/general/NLCHM%20Newsletter%20May%202017.pdf
|
| 43 |
+
LimeSurvey v2,Fairness Ethics Accountability and Transparency,2022,United States,https://www.nsf.gov/pubs/2019/nsf19016/nsf19016.pdf
|
| 44 |
+
LimeSurvey v2,Assessment of current initiatives of the European Commission on better regulation,2022,European Union,https://www.europarl.europa.eu/RegData/etudes/IDAN/2022/734766/IPOL_IDA(2022)734766_EN.pdf
|
| 45 |
+
LimeSurvey v2,Ministry of Digital Economy and Society,2020,Thailand,https://www.etda.or.th/getattachment/9d370f25-f37a-4b7c-b661-48d2d730651d/Digital-Thailand-AI-Ethics-Principle-and-Guideline.pdf.aspx?lang=th-TH
|
| 46 |
+
LimeSurvey v2,Federal 5 Year STEM Education Strategic Plan,2019,United States,https://www.energy.gov/sites/default/files/2019/05/f62/STEM-Education-Strategic-Plan-2018.pdf
|
| 47 |
+
LimeSurvey v2,NITRD Supplement to the Presidents FY2020 Budget,2022,United States,https://www.nitrd.gov/pubs/FY2020-NITRD-Supplement.pdf
|
| 48 |
+
LimeSurvey v2,Emerging Technologies Handboo,2021,Colombia,https://gobiernodigital.mintic.gov.co/692/articles-160829_Guia_Tecnologias_Emergentes.pdf
|
| 49 |
+
LimeSurvey v2,FRVT Demographic Effects,2021,United States,https://nvlpubs.nist.gov/nistpubs/ir/2019/NIST.IR.8280.pdf
|
| 50 |
+
LimeSurvey v2,"Artificial intelligence: Human rights, social justice and development",2021,Argentina,https://giswatch.org/sites/default/files/gisw2019_artificial_intelligence.pdf
|
| 51 |
+
LimeSurvey v2,Public Consultation for the National AI Strategy for Ireland,2021,Ireland,https://enterprise.gov.ie/en/Consultations/Consultations-files/AI-Strategy-Public-Consultation-Report.pdf
|
| 52 |
+
LimeSurvey v2,12th National Economic and Social Development Plan,2019,Thailand,https://www.oneplanetnetwork.org/sites/default/files/thailand_national_economic_and_social_development_plan_nesdp.pdf
|
| 53 |
+
LimeSurvey v2,NATIONAL ENTREPRENEURSHIP POLICY CONPES 4011,2021,Colombia,https://colaboracion.dnp.gov.co/CDT/Conpes/Económicos/4011.pdf
|
| 54 |
+
LimeSurvey v2,POLÍTICA NACIONAL PARA LA TRANSFORMACIÓN DIGITAL E INTELIGENCIA ARTIFICIAL,2021,Colombia,https://colaboracion.dnp.gov.co/CDT/Conpes/Económicos/3975.pdf
|
| 55 |
+
LimeSurvey v2,Pan Canadian Artificial Intelligence Strategy,2019,Canada,https://cifar.ca/wp-content/uploads/2020/11/AICan-2020-CIFAR-Pan-Canadian-AI-Strategy-Impact-Report.pdf
|
| 56 |
+
LimeSurvey v2,National Center for Innovation and AI,2021,Peru,https://cdn.www.gob.pe/uploads/document/file/1909267/National%20Artificial%20Intelligence%20Strategy%20-%20Peru.pdf
|
| 57 |
+
LimeSurvey v2,National Artificial Ingelligence strategy 2021-2025,2022,Turkey,https://cbddo.gov.tr/SharedFolderServer/Genel/File/TRNationalAIStrategy2021-2025.pdf
|
| 58 |
+
LimeSurvey v2,AI in Financial Services,2021,United Kingdom,https://www.turing.ac.uk/sites/default/files/2021-06/ati_ai_in_financial_services_lores.pdf
|
| 59 |
+
LimeSurvey v2,Good Practice Recommendations to Integrate Ethics in the Development of AI Solutions in Healthcare,2022,France,https://esante.gouv.fr/sites/default/files/media_entity/documents/ethic_by_design_guide_vf.pdf
|
| 60 |
+
LimeSurvey v2,AI Ecosystem Survey,2021,United Kingdom,https://www.turing.ac.uk/sites/default/files/2021-09/ai-strategy-survey_results_020921.pdf
|
| 61 |
+
LimeSurvey v2,US Patent and Trademark Office Report on Public Views on AI and Intellectual Property Policy,2020,United States,https://www.uspto.gov/sites/default/files/documents/USPTO_AI-Report_2020-10-07.pdf
|
| 62 |
+
LimeSurvey v2,Guidance for Regulation of AI Applications,2020,United States,https://www.whitehouse.gov/wp-content/uploads/2020/11/M-21-06.pdf
|
| 63 |
+
LimeSurvey v2,PhD Scholarship,2022,Turkey,https://www.yok.gov.tr/Documents/Yayinlar/Yayinlarimiz/2020/100-2000-yok-doktora-projesi-2020.pdf
|
| 64 |
+
LimeSurvey v2,UAE National Strategy for AI 2031,2019,United Arab Emirates,https://ai.gov.ae/wp-content/uploads/2021/07/UAE-National-Strategy-for-Artificial-Intelligence-2031.pdf
|
| 65 |
+
LimeSurvey v2,Human-Centred Artificial Intelligence for Human Resources: A Toolkit for Human Resources Professionals,2022,Turkey,https://www3.weforum.org/docs/WEF_Human_Centred_Artificial_Intelligence_for_Human_Resources_2021.pdf
|
| 66 |
+
LimeSurvey v2,Decree No 2007 3003 of November 27 2007 setting the operating procedures of the national body for the protection of personal data,2022,Tunisia,http://www.inpdp.tn/ressources/decret_3003.pdf
|
| 67 |
+
LimeSurvey v2,Amendments to the Polish Labour Code,2022,Poland,http://ilo.org/dyn/natlex/docs/ELECTRONIC/45181/91758/F1623906595/The-Labour-Code%20consolidated%201997.pdf
|
| 68 |
+
LimeSurvey v2,Satellite Platform for Ireland SPEir,2021,Ireland,http://eoscience.esa.int/landtraining2018/files/posters/hanafin.pdf
|
| 69 |
+
LimeSurvey v2,Common Regulatory Capacity for AI,2022,European Union,https://www.turing.ac.uk/sites/default/files/2022-07/common_regulatory_capacity_for_ai_the_alan_turing_institute.pdf
|
| 70 |
+
LimeSurvey v2,Digital Switzerland Strategy,2019,Switzerland,https://ethicsandtechnology.org/wp-content/uploads/2019/12/bericht_idag_ki_d.pdf
|
| 71 |
+
LimeSurvey v2,AGILE GOVERNANCE UPDATE How Governments Businesses and Civil Society Can Create a Better World by Reimagining Governance,2022,Japan,https://www.meti.go.jp/shingikai/mono_info_service/governance_model_kento/pdf/20220808_2.pdf
|
| 72 |
+
LimeSurvey v2,Policy on the Compliance Assistance Sandbox,2022,United States,https://files.consumerfinance.gov/f/documents/cfpb_final-policy-on-cas.pdf
|
| 73 |
+
LimeSurvey v2,Policy on No Action Letters,2019,United States,https://files.consumerfinance.gov/f/documents/cfpb_final-policy-on-no-action-letters.pdf
|
| 74 |
+
LimeSurvey v2,Policy to Encourage Trial Disclosure Programs,2022,United States,https://files.consumerfinance.gov/f/documents/cfpb_final-policy-to-encourage-tdp.pdf
|
| 75 |
+
OECD iLibrary,Opportunities and drawbacks of using artificial intelligence for training,2021,OECD,https://www.oecd-ilibrary.org/deliver/22729bd6-en.pdf?itemId=%2Fcontent%2Fpaper%2F22729bd6-en&mimeType=pdf
|
| 76 |
+
OECD iLibrary,"Who develops AI-related innovations, goods and services? : A firm-level analysis",2021,OECD,https://www.oecd-ilibrary.org/deliver/3e4aedd4-en.pdf?itemId=%2Fcontent%2Fpaper%2F3e4aedd4-en&mimeType=pdf
|
| 77 |
+
OECD iLibrary,Nowcasting aggregate services trade,2021,OECD,https://www.oecd-ilibrary.org/deliver/0ad7d27c-en.pdf?itemId=%2Fcontent%2Fpaper%2F0ad7d27c-en&mimeType=pdf
|
| 78 |
+
OECD iLibrary,OECD Employment Outlook 2023 : Artificial Intelligence and the Labour Market,2023,OECD,https://www.oecd-ilibrary.org/deliver/08785bba-en.pdf?itemId=%2Fcontent%2Fpublication%2F08785bba-en&mimeType=pdf
|
| 79 |
+
OECD iLibrary,Know thy AI: Assessing the risks of artificial intelligence,2022,OECD,https://www.oecd-ilibrary.org/deliver/067f4cff-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F067f4cff-en&mimeType=pdf
|
| 80 |
+
OECD iLibrary,"Positive, High-achieving Students? : What Schools and Teachers Can Do",2021,OECD,https://www.oecd-ilibrary.org/deliver/3b9551db-en.pdf?itemId=%2Fcontent%2Fpublication%2F3b9551db-en&mimeType=pdf
|
| 81 |
+
OECD iLibrary,"PENELOPE 2018: A code system for Monte Carlo simulation of electron and photon transport : Workshop Proceedings, Barcelona, Spain, 28 January – 1 February 2019",2019,OECD,https://www.oecd-ilibrary.org/deliver/32da5043-en.pdf?itemId=%2Fcontent%2Fpublication%2F32da5043-en&mimeType=pdf
|
| 82 |
+
OECD iLibrary,Measuring the AI content of government-funded R&D projects : A proof of concept for the OECD Fundstat initiative,2021,OECD,https://www.oecd-ilibrary.org/deliver/7b43b038-en.pdf?itemId=%2Fcontent%2Fpaper%2F7b43b038-en&mimeType=pdf
|
| 83 |
+
OECD iLibrary,Is digital media literacy the answer to our disinformation woes?,2022,OECD,https://www.oecd-ilibrary.org/deliver/326b63bf-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F326b63bf-en&mimeType=pdf
|
| 84 |
+
OECD iLibrary,The human capital behind AI : Jobs and skills demand from online job postings,2021,OECD,https://www.oecd-ilibrary.org/deliver/2e278150-en.pdf?itemId=%2Fcontent%2Fpaper%2F2e278150-en&mimeType=pdf
|
| 85 |
+
OECD iLibrary,Measuring the environmental impacts of artificial intelligence compute and applications : The AI footprint,2022,OECD,https://www.oecd-ilibrary.org/deliver/7babf571-en.pdf?itemId=%2Fcontent%2Fpaper%2F7babf571-en&mimeType=pdf
|
| 86 |
+
OECD iLibrary,Improving reproducibility of artificial intelligence research to increase trust and productivity,2023,OECD,https://www.oecd-ilibrary.org/improving-reproducibility-of-artificial-intelligence-research-to-increase-trust-and-productivity_3f57323a-en.pdf?itemId=%2Fcontent%2Fcomponent%2F3f57323a-en&mimeType=pdf
|
| 87 |
+
OECD iLibrary,The impact of Artificial Intelligence on the labour market : What do we know so far?,2021,OECD,https://www.oecd-ilibrary.org/deliver/7c895724-en.pdf?itemId=%2Fcontent%2Fpaper%2F7c895724-en&mimeType=pdf
|
| 88 |
+
OECD iLibrary,Nowcasting trade in value added indicators,2023,OECD,https://www.oecd-ilibrary.org/deliver/00f8aff7-en.pdf?itemId=%2Fcontent%2Fpaper%2F00f8aff7-en&mimeType=pdf
|
| 89 |
+
OECD iLibrary,"Artificial intelligence companies, goods and services : A trademark-based analysis",2021,OECD,https://www.oecd-ilibrary.org/deliver/2db2d7f4-en.pdf?itemId=%2Fcontent%2Fpaper%2F2db2d7f4-en&mimeType=pdf
|
| 90 |
+
OECD iLibrary,Putting AI to the test : How does the performance of GPT and 15-year-old students in PISA compare?,2023,OECD,https://www.oecd-ilibrary.org/deliver/2c297e0b-en.pdf?itemId=%2Fcontent%2Fpaper%2F2c297e0b-en&mimeType=pdf
|
| 91 |
+
OECD iLibrary,"Artificial intelligence, its diffusion and uses in manufacturing",2021,OECD,https://www.oecd-ilibrary.org/deliver/249e2003-en.pdf?itemId=%2Fcontent%2Fpaper%2F249e2003-en&mimeType=pdf
|
| 92 |
+
OECD iLibrary,"Why are some U.S. cities successful, while others are not? Empirical evidence from machine learning",2020,OECD,https://www.oecd-ilibrary.org/deliver/7f77c2e7-en.pdf?itemId=%2Fcontent%2Fpaper%2F7f77c2e7-en&mimeType=pdf
|
| 93 |
+
OECD iLibrary,Open science - Enabling discovery in the digital age,2021,OECD,https://www.oecd-ilibrary.org/deliver/81a9dcf0-en.pdf?itemId=%2Fcontent%2Fpaper%2F81a9dcf0-en&mimeType=pdf
|
| 94 |
+
OECD iLibrary,Using Artificial Intelligence in the workplace : What are the main ethical risks?,2022,OECD,https://www.oecd-ilibrary.org/deliver/840a2d9f-en.pdf?itemId=%2Fcontent%2Fpaper%2F840a2d9f-en&mimeType=pdf
|
| 95 |
+
OECD iLibrary,Enhancing Access to and Sharing of Data : Reconciling Risks and Benefits for Data Re-use across Societies,2019,OECD,https://www.oecd-ilibrary.org/deliver/276aaca8-en.pdf?itemId=%2Fcontent%2Fpublication%2F276aaca8-en&mimeType=pdf
|
| 96 |
+
OECD iLibrary,Artificial intelligence and labour market matching,2023,OECD,https://www.oecd-ilibrary.org/deliver/2b440821-en.pdf?itemId=%2Fcontent%2Fpaper%2F2b440821-en&mimeType=pdf
|
| 97 |
+
OECD iLibrary,A blueprint for building national compute capacity for artificial intelligence,2023,OECD,https://www.oecd-ilibrary.org/deliver/876367e3-en.pdf?itemId=%2Fcontent%2Fpaper%2F876367e3-en&mimeType=pdf
|
| 98 |
+
OECD iLibrary,New Directions for Data-Driven Transport Safety,2019,OECD,https://www.oecd-ilibrary.org/deliver/2b2f71bc-en.pdf?itemId=%2Fcontent%2Fpaper%2F2b2f71bc-en&mimeType=pdf
|
| 99 |
+
OECD iLibrary,What role will artificial intelligence (AI) play in the classroom?,2020,OECD,https://www.oecd-ilibrary.org/deliver/2980fe96-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F2980fe96-en&mimeType=pdf
|
| 100 |
+
OECD iLibrary,Tools for trustworthy AI : A framework to compare implementation tools for trustworthy AI systems,2021,OECD,https://www.oecd-ilibrary.org/deliver/008232ec-en.pdf?itemId=%2Fcontent%2Fpaper%2F008232ec-en&mimeType=pdf
|
| 101 |
+
OECD iLibrary,Artificial Intelligence in Proactive Road Infrastructure Safety Management : Summary and Conclusions,2021,OECD,https://www.oecd-ilibrary.org/deliver/04509d3f-en.pdf?itemId=%2Fcontent%2Fpublication%2F04509d3f-en&mimeType=pdf
|
| 102 |
+
OECD iLibrary,Demand for AI skills in jobs : Evidence from online job postings,2021,OECD,https://www.oecd-ilibrary.org/deliver/3ed32d94-en.pdf?itemId=%2Fcontent%2Fpaper%2F3ed32d94-en&mimeType=pdf
|
| 103 |
+
OECD iLibrary,Is Education Losing the Race with Technology? : AI's Progress in Maths and Reading,2023,OECD,https://www.oecd-ilibrary.org/deliver/73105f99-en.pdf?itemId=%2Fcontent%2Fpublication%2F73105f99-en&mimeType=pdf
|
| 104 |
+
OECD iLibrary,AI measurement in ICT usage surveys : A review,2021,OECD,https://www.oecd-ilibrary.org/deliver/72cce754-en.pdf?itemId=%2Fcontent%2Fpaper%2F72cce754-en&mimeType=pdf
|
| 105 |
+
OECD iLibrary,The impact of AI on the workplace: Evidence from OECD case studies of AI implementation,2023,OECD,https://www.oecd-ilibrary.org/deliver/2247ce58-en.pdf?itemId=%2Fcontent%2Fpaper%2F2247ce58-en&mimeType=pdf
|
| 106 |
+
OECD iLibrary,Identifying artificial intelligence actors using online data,2023,OECD,https://www.oecd-ilibrary.org/deliver/1f5307e7-en.pdf?itemId=%2Fcontent%2Fpaper%2F1f5307e7-en&mimeType=pdf
|
| 107 |
+
OECD iLibrary,Adaptive Trees: a new approach to economic forecasting,2020,OECD,https://www.oecd-ilibrary.org/deliver/5569a0aa-en.pdf?itemId=%2Fcontent%2Fpaper%2F5569a0aa-en&mimeType=pdf
|
| 108 |
+
OECD iLibrary,Developing Minds in the Digital Age : Towards a Science of Learning for 21st Century Education,2019,OECD,https://www.oecd-ilibrary.org/deliver/562a8659-en.pdf?itemId=%2Fcontent%2Fpublication%2F562a8659-en&mimeType=pdf
|
| 109 |
+
OECD iLibrary,"OECD Digital Education Outlook 2021 : Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots",2021,OECD,https://www.oecd-ilibrary.org/deliver/589b283f-en.pdf?itemId=%2Fcontent%2Fpublication%2F589b283f-en&mimeType=pdf
|
| 110 |
+
OECD iLibrary,How will technology and artificial intelligence (AI) affect education?,2019,OECD,https://www.oecd-ilibrary.org/deliver/58d1112a-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F58d1112a-en&mimeType=pdf
|
| 111 |
+
OECD iLibrary,Defining and classifying AI in the workplace,2023,OECD,https://www.oecd-ilibrary.org/deliver/59e89d7f-en.pdf?itemId=%2Fcontent%2Fpaper%2F59e89d7f-en&mimeType=pdf
|
| 112 |
+
OECD iLibrary,Linking Aid to the Sustainable Development Goals – a machine learning approach,2019,OECD,https://www.oecd-ilibrary.org/deliver/4bdaeb8c-en.pdf?itemId=%2Fcontent%2Fpaper%2F4bdaeb8c-en&mimeType=pdf
|
| 113 |
+
OECD iLibrary,Laying the foundations for artificial intelligence in health,2021,OECD,https://www.oecd-ilibrary.org/deliver/3f62817d-en.pdf?itemId=%2Fcontent%2Fpaper%2F3f62817d-en&mimeType=pdf
|
| 114 |
+
OECD iLibrary,"AI and the Future of Skills, Volume 1 : Capabilities and Assessments",2021,OECD,https://www.oecd-ilibrary.org/deliver/5ee71f34-en.pdf?itemId=%2Fcontent%2Fpublication%2F5ee71f34-en&mimeType=pdf
|
| 115 |
+
OECD iLibrary,Regulatory sandboxes in artificial intelligence,2023,OECD,https://www.oecd-ilibrary.org/deliver/8f80a0e6-en.pdf?itemId=%2Fcontent%2Fpaper%2F8f80a0e6-en&mimeType=pdf
|
| 116 |
+
OECD iLibrary,The Strategic and Responsible Use of Artificial Intelligence in the Public Sector of Latin America and the Caribbean,2022,OECD,https://www.oecd-ilibrary.org/deliver/1f334543-en.pdf?itemId=%2Fcontent%2Fpublication%2F1f334543-en&mimeType=pdf
|
| 117 |
+
OECD iLibrary,Identifying and measuring developments in artificial intelligence : Making the impossible possible,2020,OECD,https://www.oecd-ilibrary.org/deliver/5f65ff7e-en.pdf?itemId=%2Fcontent%2Fpaper%2F5f65ff7e-en&mimeType=pdf
|
| 118 |
+
OECD iLibrary,Progress on implementing and using electronic health record systems : Developments in OECD countries as of 2021,2023,OECD,https://www.oecd-ilibrary.org/deliver/4f4ce846-en.pdf?itemId=%2Fcontent%2Fpaper%2F4f4ce846-en&mimeType=pdf
|
| 119 |
+
OECD iLibrary,State of implementation of the OECD AI Principles : Insights from national AI policies,2021,OECD,https://www.oecd-ilibrary.org/deliver/1cd40c44-en.pdf?itemId=%2Fcontent%2Fpaper%2F1cd40c44-en&mimeType=pdf
|
| 120 |
+
OECD iLibrary,Advancing accountability in AI : Governing and managing risks throughout the lifecycle for trustworthy AI,2023,OECD,https://www.oecd-ilibrary.org/deliver/2448f04b-en.pdf?itemId=%2Fcontent%2Fpaper%2F2448f04b-en&mimeType=pdf
|
| 121 |
+
OECD iLibrary,The digital innovation policy landscape in 2019,2019,OECD,https://www.oecd-ilibrary.org/deliver/6171f649-en.pdf?itemId=%2Fcontent%2Fpaper%2F6171f649-en&mimeType=pdf
|
| 122 |
+
OECD iLibrary,Review of national policy initiatives in support of digital and AI-driven innovation,2019,OECD,https://www.oecd-ilibrary.org/deliver/15491174-en.pdf?itemId=%2Fcontent%2Fpaper%2F15491174-en&mimeType=pdf
|
| 123 |
+
OECD iLibrary,The Effects of AI on the Working Lives of Women,2022,OECD,https://www.oecd-ilibrary.org/deliver/14e9b92c-en.pdf?itemId=%2Fcontent%2Fpublication%2F14e9b92c-en&mimeType=pdf
|
| 124 |
+
OECD iLibrary,The digitalisation of agriculture : A literature review and emerging policy issues,2022,OECD,https://www.oecd-ilibrary.org/deliver/285cc27d-en.pdf?itemId=%2Fcontent%2Fpaper%2F285cc27d-en&mimeType=pdf
|
| 125 |
+
OECD iLibrary,Labour and Skills Demand in Alberta : Insights Using Big Data Intelligence,2023,OECD,https://www.oecd-ilibrary.org/deliver/659ce346-en.pdf?itemId=%2Fcontent%2Fpublication%2F659ce346-en&mimeType=pdf
|
| 126 |
+
OECD iLibrary,The Artificial Intelligence Act: Addressing the divergence between the public and private sectors,2022,OECD,https://www.oecd-ilibrary.org/deliver/146fa80b-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F146fa80b-en&mimeType=pdf
|
| 127 |
+
OECD iLibrary,Tracking activity in real time with Google Trends,2020,OECD,https://www.oecd-ilibrary.org/deliver/6b9c7518-en.pdf?itemId=%2Fcontent%2Fpaper%2F6b9c7518-en&mimeType=pdf
|
| 128 |
+
OECD iLibrary,"AI language models : Technological, socio-economic and policy considerations",2023,OECD,https://www.oecd-ilibrary.org/deliver/13d38f92-en.pdf?itemId=%2Fcontent%2Fpaper%2F13d38f92-en&mimeType=pdf
|
| 129 |
+
OECD iLibrary,Artificial Intelligence and international trade : Some preliminary implications,2022,OECD,https://www.oecd-ilibrary.org/deliver/13212d3e-en.pdf?itemId=%2Fcontent%2Fpaper%2F13212d3e-en&mimeType=pdf
|
| 130 |
+
OECD iLibrary,"G20 Compendium on the Use of Digital Tools for Public Service Continuity : Report for the G20 Digital Economy Tak Force, Trieste, Italy, August 2021",2021,OECD,https://www.oecd-ilibrary.org/deliver/6f800fd5-en.pdf?itemId=%2Fcontent%2Fpublication%2F6f800fd5-en&mimeType=pdf
|
| 131 |
+
OECD iLibrary,"A portrait of AI adopters across countries : Firm characteristics, assets’ complementarities and productivity",2023,OECD,https://www.oecd-ilibrary.org/deliver/0fb79bb9-en.pdf?itemId=%2Fcontent%2Fpaper%2F0fb79bb9-en&mimeType=pdf
|
| 132 |
+
OECD iLibrary,"Hello, World : Artificial intelligence and its use in the public sector",2019,OECD,https://www.oecd-ilibrary.org/deliver/726fd39d-en.pdf?itemId=%2Fcontent%2Fpaper%2F726fd39d-en&mimeType=pdf
|
| 133 |
+
OECD iLibrary,Identifying and characterising AI adopters : A novel approach based on big data,2022,OECD,https://www.oecd-ilibrary.org/deliver/154981d7-en.pdf?itemId=%2Fcontent%2Fpaper%2F154981d7-en&mimeType=pdf
|
| 134 |
+
OECD iLibrary,What skills and abilities can automation technologies replicate and what does it mean for workers? : New evidence,2022,OECD,https://www.oecd-ilibrary.org/deliver/646aad77-en.pdf?itemId=%2Fcontent%2Fpaper%2F646aad77-en&mimeType=pdf
|
| 135 |
+
OECD iLibrary,Countering Public Grant Fraud in Spain : Machine Learning for Assessing Risks and Targeting Control Activities,2021,OECD,https://www.oecd-ilibrary.org/deliver/0ea22484-en.pdf?itemId=%2Fcontent%2Fpublication%2F0ea22484-en&mimeType=pdf
|
| 136 |
+
OECD iLibrary,AI scoring for international large-scale assessments using a deep learning model and multilingual data,2023,OECD,https://www.oecd-ilibrary.org/deliver/9918e1fb-en.pdf?itemId=%2Fcontent%2Fpaper%2F9918e1fb-en&mimeType=pdf
|
| 137 |
+
OECD iLibrary,Enabling environment for FinTech innovation in the Czech Republic and EU,2022,OECD,https://www.oecd-ilibrary.org/enabling-environment-for-fintech-innovation-in-the-czech-republic-and-eu_47b4db37-en.pdf?itemId=%2Fcontent%2Fcomponent%2F47b4db37-en&mimeType=pdf
|
| 138 |
+
OECD iLibrary,Elicit: Language models as research tools,2023,OECD,https://www.oecd-ilibrary.org/elicit-language-models-as-research-tools_174aee8f-en.pdf?itemId=%2Fcontent%2Fcomponent%2F174aee8f-en&mimeType=pdf
|
| 139 |
+
OECD iLibrary,"Efforts to develop a responsible, trustworthy and human-centric approach",2022,OECD,https://www.oecd-ilibrary.org/efforts-to-develop-a-responsible-trustworthy-and-human-centric-approach_96d49021-en.pdf?itemId=%2Fcontent%2Fcomponent%2F96d49021-en&mimeType=pdf
|
| 140 |
+
OECD iLibrary,Editorial,2021,OECD,https://www.oecd-ilibrary.org/editorial_b0dd0724-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fb0dd0724-en&mimeType=pdf
|
| 141 |
+
OECD iLibrary,Editorial: Beyond the hype on AI – early signs of divides in the labour market,2023,OECD,https://www.oecd-ilibrary.org/editorial-beyond-the-hype-on-ai-early-signs-of-divides-in-the-labour-market_11489d95-en.pdf?itemId=%2Fcontent%2Fcomponent%2F11489d95-en&mimeType=pdf
|
| 142 |
+
OECD iLibrary,Editorial: A transition agenda for a Future that Works for all,2019,OECD,https://www.oecd-ilibrary.org/editorial-a-transition-agenda-for-a-future-that-works-for-all_86970c5c-en.pdf?itemId=%2Fcontent%2Fcomponent%2F86970c5c-en&mimeType=pdf
|
| 143 |
+
OECD iLibrary,Ensuring trustworthy artificial intelligence in the workplace: Countries’ policy action,2023,OECD,https://www.oecd-ilibrary.org/ensuring-trustworthy-artificial-intelligence-in-the-workplace-countries-policy-action_04b3d08d-en.pdf?itemId=%2Fcontent%2Fcomponent%2F04b3d08d-en&mimeType=pdf
|
| 144 |
+
OECD iLibrary,Early warning systems and indicators of dropping out of upper secondary school: the emerging role of digital technologies,2021,OECD,https://www.oecd-ilibrary.org/early-warning-systems-and-indicators-of-dropping-out-of-upper-secondary-school-the-emerging-role-of-digital-technologies_c8e57e15-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc8e57e15-en&mimeType=pdf
|
| 145 |
+
OECD iLibrary,Digitalisation and productivity: A story of complementarities,2019,OECD,https://www.oecd-ilibrary.org/digitalisation-and-productivity-a-story-of-complementarities_5713bd7d-en.pdf?itemId=%2Fcontent%2Fcomponent%2F5713bd7d-en&mimeType=pdf
|
| 146 |
+
OECD iLibrary,Digital innovation,2020,OECD,https://www.oecd-ilibrary.org/digital-innovation_8e8f2750-en.pdf?itemId=%2Fcontent%2Fcomponent%2F8e8f2750-en&mimeType=pdf
|
| 147 |
+
OECD iLibrary,Digital health,2021,OECD,https://www.oecd-ilibrary.org/digital-health_08cffda7-en.pdf?itemId=%2Fcontent%2Fcomponent%2F08cffda7-en&mimeType=pdf
|
| 148 |
+
OECD iLibrary,Digital government strategies and institutional frameworks,2019,OECD,https://www.oecd-ilibrary.org/digital-government-strategies-and-institutional-frameworks_63029fcb-en.pdf?itemId=%2Fcontent%2Fcomponent%2F63029fcb-en&mimeType=pdf
|
| 149 |
+
OECD iLibrary,Democratising artificial intelligence to accelerate scientific discovery,2023,OECD,https://www.oecd-ilibrary.org/democratising-artificial-intelligence-to-accelerate-scientific-discovery_be9632d7-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fbe9632d7-en&mimeType=pdf
|
| 150 |
+
OECD iLibrary,Initial policy considerations for generative artificial intelligence,2023,OECD,https://www.oecd-ilibrary.org/deliver/fae2d1e6-en.pdf?itemId=%2Fcontent%2Fpaper%2Ffae2d1e6-en&mimeType=pdf
|
| 151 |
+
OECD iLibrary,Digitalisation of health information,2023,OECD,https://www.oecd-ilibrary.org/digitalisation-of-health-information_f44731cf-en.pdf?itemId=%2Fcontent%2Fcomponent%2Ff44731cf-en&mimeType=pdf
|
| 152 |
+
OECD iLibrary,Venture capital investments in artificial intelligence : Analysing trends in VC in AI companies from 2012 through 2020,2021,OECD,https://www.oecd-ilibrary.org/deliver/f97beae7-en.pdf?itemId=%2Fcontent%2Fpaper%2Ff97beae7-en&mimeType=pdf
|
| 153 |
+
OECD iLibrary,Essai n° 471: Essai de mutation réverse sur des bactéries,2020,OECD,https://www.oecd-ilibrary.org/essai-n-471-essai-de-mutation-reverse-sur-des-bacteries_5lmqcr2k7md4.pdf?itemId=%2Fcontent%2Fpublication%2F9789264071254-fr&mimeType=pdf
|
| 154 |
+
OECD iLibrary,Evolution of human skills versus AI capabilities,2023,OECD,https://www.oecd-ilibrary.org/evolution-of-human-skills-versus-ai-capabilities_d077ad2f-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd077ad2f-en&mimeType=pdf
|
| 155 |
+
OECD iLibrary,Human rights due diligence through responsible AI,2021,OECD,https://www.oecd-ilibrary.org/human-rights-due-diligence-through-responsible-ai_31e7edcc-en.pdf?itemId=%2Fcontent%2Fcomponent%2F31e7edcc-en&mimeType=pdf
|
| 156 |
+
OECD iLibrary,How can artificial intelligence help scientists? A (non-exhaustive) overview,2023,OECD,https://www.oecd-ilibrary.org/how-can-artificial-intelligence-help-scientists-a-non-exhaustive-overview_a8e6c3b6-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fa8e6c3b6-en&mimeType=pdf
|
| 157 |
+
OECD iLibrary,"How are science, technology and innovation going digital? The statistical evidence",2020,OECD,https://www.oecd-ilibrary.org/how-are-science-technology-and-innovation-going-digital-the-statistical-evidence_1cfd272a-en.pdf?itemId=%2Fcontent%2Fcomponent%2F1cfd272a-en&mimeType=pdf
|
| 158 |
+
OECD iLibrary,High-performance computing leadership to enable advances in artificial intelligence and a thriving compute ecosystem,2023,OECD,https://www.oecd-ilibrary.org/high-performance-computing-leadership-to-enable-advances-in-artificial-intelligence-and-a-thriving-compute-ecosystem_0e1b4c2f-en.pdf?itemId=%2Fcontent%2Fcomponent%2F0e1b4c2f-en&mimeType=pdf
|
| 159 |
+
OECD iLibrary,Guidance and regulatory frameworks for digital education,2023,OECD,https://www.oecd-ilibrary.org/guidance-and-regulatory-frameworks-for-digital-education_a0a23dc6-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fa0a23dc6-en&mimeType=pdf
|
| 160 |
+
OECD iLibrary,Government investment spending,2019,OECD,https://www.oecd-ilibrary.org/government-investment-spending_b4536bd6-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fb4536bd6-en&mimeType=pdf
|
| 161 |
+
OECD iLibrary,Evaluating revolutions in artificial intelligence from a human perspective,2021,OECD,https://www.oecd-ilibrary.org/evaluating-revolutions-in-artificial-intelligence-from-a-human-perspective_004710fe-en.pdf?itemId=%2Fcontent%2Fcomponent%2F004710fe-en&mimeType=pdf
|
| 162 |
+
OECD iLibrary,Global mega-trends and the future of education,2019,OECD,https://www.oecd-ilibrary.org/global-mega-trends-and-the-future-of-education_5j3x77mdk442.pdf?itemId=%2Fcontent%2Fcomponent%2Ftrends_edu-2019-3-en&mimeType=pdf
|
| 163 |
+
OECD iLibrary,From knowledge discovery to knowledge creation: How can literature-based discovery accelerate progress in science?,2023,OECD,https://www.oecd-ilibrary.org/from-knowledge-discovery-to-knowledge-creation-how-can-literature-based-discovery-accelerate-progress-in-science_de74d7a9-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fde74d7a9-en&mimeType=pdf
|
| 164 |
+
OECD iLibrary,Fraud in public grants: Piloting a data-driven risk model in Spain,2021,OECD,https://www.oecd-ilibrary.org/fraud-in-public-grants-piloting-a-data-driven-risk-model-in-spain_55696a8b-en.pdf?itemId=%2Fcontent%2Fcomponent%2F55696a8b-en&mimeType=pdf
|
| 165 |
+
OECD iLibrary,Foreword,2022,OECD,https://www.oecd-ilibrary.org/foreword_1d5c6062-en.pdf?itemId=%2Fcontent%2Fcomponent%2F1d5c6062-en&mimeType=pdf
|
| 166 |
+
OECD iLibrary,"First-class humans, not second-class robots – Andreas Schleicher on learning and the future of work",2019,OECD,https://www.oecd-ilibrary.org/first-class-humans-not-second-class-robots-andreas-schleicher-on-learning-and-the-future-of-work_87958706-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F87958706-en&mimeType=pdf
|
| 167 |
+
OECD iLibrary,Experts’ assessments of AI capabilities in literacy and numeracy,2023,OECD,https://www.oecd-ilibrary.org/experts-assessments-of-ai-capabilities-in-literacy-and-numeracy_134fa8aa-en.pdf?itemId=%2Fcontent%2Fcomponent%2F134fa8aa-en&mimeType=pdf
|
| 168 |
+
OECD iLibrary,Executive summary,2019,OECD,https://www.oecd-ilibrary.org/executive-summary_98aef837-en.pdf?itemId=%2Fcontent%2Fcomponent%2F98aef837-en&mimeType=pdf
|
| 169 |
+
OECD iLibrary,Frontiers of smart education technology: Opportunities and challenges,2021,OECD,https://www.oecd-ilibrary.org/frontiers-of-smart-education-technology-opportunities-and-challenges_d3153fcd-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd3153fcd-en&mimeType=pdf
|
| 170 |
+
OECD iLibrary,"Data-Driven, Information-Enabled Regulatory Delivery",2021,OECD,https://www.oecd-ilibrary.org/deliver/8f99ec8c-en.pdf?itemId=%2Fcontent%2Fpublication%2F8f99ec8c-en&mimeType=pdf
|
| 171 |
+
OECD iLibrary,Harnessing the power of AI and emerging technologies : Background paper for the CDEP Ministerial meeting,2022,OECD,https://www.oecd-ilibrary.org/deliver/f94df8ec-en.pdf?itemId=%2Fcontent%2Fpaper%2Ff94df8ec-en&mimeType=pdf
|
| 172 |
+
OECD iLibrary,Artificial Intelligence in Society,2019,OECD,https://www.oecd-ilibrary.org/deliver/eedfee77-en.pdf?itemId=%2Fcontent%2Fpublication%2Feedfee77-en&mimeType=pdf
|
| 173 |
+
OECD iLibrary,"Shaping Digital Education : Enabling Factors for Quality, Equity and Efficiency",2023,OECD,https://www.oecd-ilibrary.org/deliver/bac4dc9f-en.pdf?itemId=%2Fcontent%2Fpublication%2Fbac4dc9f-en&mimeType=pdf
|
| 174 |
+
OECD iLibrary,OECD Business and Finance Outlook 2021 : AI in Business and Finance,2021,OECD,https://www.oecd-ilibrary.org/deliver/ba682899-en.pdf?itemId=%2Fcontent%2Fpublication%2Fba682899-en&mimeType=pdf
|
| 175 |
+
OECD iLibrary,"The Digitalisation of Science, Technology and Innovation : Key Developments and Policies",2020,OECD,https://www.oecd-ilibrary.org/deliver/b9e4a2c0-en.pdf?itemId=%2Fcontent%2Fpublication%2Fb9e4a2c0-en&mimeType=pdf
|
| 176 |
+
OECD iLibrary,Disinformation and its discontents,2022,OECD,https://www.oecd-ilibrary.org/deliver/b8856732-en.pdf?itemId=%2Fcontent%2Fmultimedia%2Fb8856732-en&mimeType=pdf
|
| 177 |
+
OECD iLibrary,Statistical profiling in public employment services : An international comparison,2019,OECD,https://www.oecd-ilibrary.org/deliver/b5e5f16e-en.pdf?itemId=%2Fcontent%2Fpaper%2Fb5e5f16e-en&mimeType=pdf
|
| 178 |
+
OECD iLibrary,Using artificial intelligence to help combat COVID-19,2020,OECD,https://www.oecd-ilibrary.org/deliver/ae4c5c21-en.pdf?itemId=%2Fcontent%2Fpaper%2Fae4c5c21-en&mimeType=pdf
|
| 179 |
+
OECD iLibrary,"The supply, demand and characteristics of the AI workforce across OECD countries",2023,OECD,https://www.oecd-ilibrary.org/deliver/bb17314a-en.pdf?itemId=%2Fcontent%2Fpaper%2Fbb17314a-en&mimeType=pdf
|
| 180 |
+
OECD iLibrary,Speaking the same language : A machine learning approach to classify skills in Burning Glass Technologies data,2021,OECD,https://www.oecd-ilibrary.org/deliver/adb03746-en.pdf?itemId=%2Fcontent%2Fpaper%2Fadb03746-en&mimeType=pdf
|
| 181 |
+
OECD iLibrary,Six questions about the demand for artificial intelligence skills in labour markets,2023,OECD,https://www.oecd-ilibrary.org/deliver/ac1bebf0-en.pdf?itemId=%2Fcontent%2Fpaper%2Fac1bebf0-en&mimeType=pdf
|
| 182 |
+
OECD iLibrary,Perspectives de l’emploi de l’OCDE 2023 : Intelligence artificielle et marché du travail,2023,OECD,https://www.oecd-ilibrary.org/deliver/aae5dba0-fr.pdf?itemId=%2Fcontent%2Fpublication%2Faae5dba0-fr&mimeType=pdf
|
| 183 |
+
OECD iLibrary,Improving effectiveness of Lithuania’s innovation policy,2021,OECD,https://www.oecd-ilibrary.org/deliver/a8fec2ee-en.pdf?itemId=%2Fcontent%2Fpaper%2Fa8fec2ee-en&mimeType=pdf
|
| 184 |
+
OECD iLibrary,"Artificial Intelligence in Science : Challenges, Opportunities and the Future of Research",2023,OECD,https://www.oecd-ilibrary.org/deliver/a8d820bd-en.pdf?itemId=%2Fcontent%2Fpublication%2Fa8d820bd-en&mimeType=pdf
|
| 185 |
+
OECD iLibrary,Trustworthy artificial intelligence (AI) in education : Promises and challenges,2020,OECD,https://www.oecd-ilibrary.org/deliver/a6c90fa9-en.pdf?itemId=%2Fcontent%2Fpaper%2Fa6c90fa9-en&mimeType=pdf
|
| 186 |
+
OECD iLibrary,Digital Innovation : Seizing Policy Opportunities,2019,OECD,https://www.oecd-ilibrary.org/deliver/a298dc87-en.pdf?itemId=%2Fcontent%2Fpublication%2Fa298dc87-en&mimeType=pdf
|
| 187 |
+
OECD iLibrary,Effective Government Information Websites : Toolkit for Implementation,2023,OECD,https://www.oecd-ilibrary.org/deliver/ac325b03-en.pdf?itemId=%2Fcontent%2Fpublication%2Fac325b03-en&mimeType=pdf
|
| 188 |
+
OECD iLibrary,Shaping the transition : Artificial intelligence and social dialogue,2022,OECD,https://www.oecd-ilibrary.org/deliver/f097c48a-en.pdf?itemId=%2Fcontent%2Fpaper%2Ff097c48a-en&mimeType=pdf
|
| 189 |
+
OECD iLibrary,Data-driven innovation in clinical pharmaceutical research,2023,OECD,https://www.oecd-ilibrary.org/data-driven-innovation-in-clinical-pharmaceutical-research_8763a389-en.pdf?itemId=%2Fcontent%2Fcomponent%2F8763a389-en&mimeType=pdf
|
| 190 |
+
OECD iLibrary,AI is poised to revolutionise healthcare. Building trust will be key,2022,OECD,https://www.oecd-ilibrary.org/deliver/bc7f47fa-en.pdf?itemId=%2Fcontent%2Fmultimedia%2Fbc7f47fa-en&mimeType=pdf
|
| 191 |
+
OECD iLibrary,Governing Transport in the Algorithmic Age,2019,OECD,https://www.oecd-ilibrary.org/deliver/eec0b9aa-en.pdf?itemId=%2Fcontent%2Fpaper%2Feec0b9aa-en&mimeType=pdf
|
| 192 |
+
OECD iLibrary,The impact of AI on the workplace: Main findings from the OECD AI surveys of employers and workers,2023,OECD,https://www.oecd-ilibrary.org/deliver/ea0a0fe1-en.pdf?itemId=%2Fcontent%2Fpaper%2Fea0a0fe1-en&mimeType=pdf
|
| 193 |
+
OECD iLibrary,Not lost in translation : The implications of machine translation technologies for language professionals and for broader society,2023,OECD,https://www.oecd-ilibrary.org/deliver/e1d1d170-en.pdf?itemId=%2Fcontent%2Fpaper%2Fe1d1d170-en&mimeType=pdf
|
| 194 |
+
OECD iLibrary,The value of data in digital-based business models: Measurement and economic policy implications,2022,OECD,https://www.oecd-ilibrary.org/deliver/d960a10c-en.pdf?itemId=%2Fcontent%2Fpaper%2Fd960a10c-en&mimeType=pdf
|
| 195 |
+
OECD iLibrary,Scoping the OECD AI principles : Deliberations of the Expert Group on Artificial Intelligence at the OECD (AIGO),2019,OECD,https://www.oecd-ilibrary.org/deliver/d62f618a-en.pdf?itemId=%2Fcontent%2Fpaper%2Fd62f618a-en&mimeType=pdf
|
| 196 |
+
OECD iLibrary,The EU-OECD definition of a functional urban area,2019,OECD,https://www.oecd-ilibrary.org/deliver/d58cb34d-en.pdf?itemId=%2Fcontent%2Fpaper%2Fd58cb34d-en&mimeType=pdf
|
| 197 |
+
OECD iLibrary,Enhancing the security of communication infrastructure,2023,OECD,https://www.oecd-ilibrary.org/deliver/bb608fe5-en.pdf?itemId=%2Fcontent%2Fpaper%2Fbb608fe5-en&mimeType=pdf
|
| 198 |
+
OECD iLibrary,Embracing a One Health Framework to Fight Antimicrobial Resistance,2023,OECD,https://www.oecd-ilibrary.org/deliver/ce44c755-en.pdf?itemId=%2Fcontent%2Fpublication%2Fce44c755-en&mimeType=pdf
|
| 199 |
+
OECD iLibrary,OECD Framework for the Classification of AI systems,2022,OECD,https://www.oecd-ilibrary.org/deliver/cb6d9eca-en.pdf?itemId=%2Fcontent%2Fpaper%2Fcb6d9eca-en&mimeType=pdf
|
| 200 |
+
OECD iLibrary,Governing data and AI for all: Which model for a sustainable and just data governance?,2022,OECD,https://www.oecd-ilibrary.org/deliver/c3a0a473-en.pdf?itemId=%2Fcontent%2Fmultimedia%2Fc3a0a473-en&mimeType=pdf
|
| 201 |
+
OECD iLibrary,Artificial intelligence and employment : New cross-country evidence,2021,OECD,https://www.oecd-ilibrary.org/deliver/c2c1d276-en.pdf?itemId=%2Fcontent%2Fpaper%2Fc2c1d276-en&mimeType=pdf
|
| 202 |
+
OECD iLibrary,An overview of national AI strategies and policies,2021,OECD,https://www.oecd-ilibrary.org/deliver/c05140d9-en.pdf?itemId=%2Fcontent%2Fpaper%2Fc05140d9-en&mimeType=pdf
|
| 203 |
+
OECD iLibrary,G7 Hiroshima Process on Generative Artificial Intelligence (AI) : Towards a G7 Common Understanding on Generative AI,2023,OECD,https://www.oecd-ilibrary.org/deliver/bf3c0c60-en.pdf?itemId=%2Fcontent%2Fpublication%2Fbf3c0c60-en&mimeType=pdf
|
| 204 |
+
OECD iLibrary,The Digital Transformation of SMEs,2021,OECD,https://www.oecd-ilibrary.org/deliver/bdb9256a-en.pdf?itemId=%2Fcontent%2Fpublication%2Fbdb9256a-en&mimeType=pdf
|
| 205 |
+
OECD iLibrary,Development Co-operation Report 2021 : Shaping a Just Digital Transformation,2021,OECD,https://www.oecd-ilibrary.org/deliver/ce08832f-en.pdf?itemId=%2Fcontent%2Fpublication%2Fce08832f-en&mimeType=pdf
|
| 206 |
+
OECD iLibrary,Data driven approaches towards risk-based regulatory delivery,2021,OECD,https://www.oecd-ilibrary.org/data-driven-approaches-towards-risk-based-regulatory-delivery_eff10ad4-en.pdf?itemId=%2Fcontent%2Fcomponent%2Feff10ad4-en&mimeType=pdf
|
| 207 |
+
OECD iLibrary,Applying machine learning techniques to inspections,2021,OECD,https://www.oecd-ilibrary.org/applying-machine-learning-techniques-to-inspections_c052cabf-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc052cabf-en&mimeType=pdf
|
| 208 |
+
OECD iLibrary,Cross-cultural validity and comparability in assessments of complex constructs,2023,OECD,https://www.oecd-ilibrary.org/cross-cultural-validity-and-comparability-in-assessments-of-complex-constructs_91f3d034-en.pdf?itemId=%2Fcontent%2Fcomponent%2F91f3d034-en&mimeType=pdf
|
| 209 |
+
OECD iLibrary,Shifting global gravity,2019,OECD,https://www.oecd-ilibrary.org/shifting-global-gravity_5j3x77mdjbbp.pdf?itemId=%2Fcontent%2Fcomponent%2Ftrends_edu-2019-4-en&mimeType=pdf
|
| 210 |
+
OECD iLibrary,Setting the stage: Approaches to assessing AI’s impact,2023,OECD,https://www.oecd-ilibrary.org/setting-the-stage-approaches-to-assessing-ai-s-impact_8ee0810f-en.pdf?itemId=%2Fcontent%2Fcomponent%2F8ee0810f-en&mimeType=pdf
|
| 211 |
+
OECD iLibrary,Seizing the productive potential of digital change,2020,OECD,https://www.oecd-ilibrary.org/seizing-the-productive-potential-of-digital-change_af0dffc7-en.pdf?itemId=%2Fcontent%2Fcomponent%2Faf0dffc7-en&mimeType=pdf
|
| 212 |
+
OECD iLibrary,Scaling up ambitious learning practices,2019,OECD,https://www.oecd-ilibrary.org/scaling-up-ambitious-learning-practices_97c31bfe-en.pdf?itemId=%2Fcontent%2Fcomponent%2F97c31bfe-en&mimeType=pdf
|
| 213 |
+
OECD iLibrary,Robot scientists: From Adam to Eve to Genesis,2023,OECD,https://www.oecd-ilibrary.org/robot-scientists-from-adam-to-eve-to-genesis_d89b39b6-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd89b39b6-en&mimeType=pdf
|
| 214 |
+
OECD iLibrary,Risk-based control in Spain: A foundation for improved analytics,2021,OECD,https://www.oecd-ilibrary.org/risk-based-control-in-spain-a-foundation-for-improved-analytics_f3c1b67c-en.pdf?itemId=%2Fcontent%2Fcomponent%2Ff3c1b67c-en&mimeType=pdf
|
| 215 |
+
OECD iLibrary,Questions to guide assessment of artificial intelligence systems against human performance,2021,OECD,https://www.oecd-ilibrary.org/questions-to-guide-assessment-of-artificial-intelligence-systems-against-human-performance_344b0fa3-en.pdf?itemId=%2Fcontent%2Fcomponent%2F344b0fa3-en&mimeType=pdf
|
| 216 |
+
OECD iLibrary,Putting in place key enablers for AI in the public sector,2022,OECD,https://www.oecd-ilibrary.org/putting-in-place-key-enablers-for-ai-in-the-public-sector_e88632a9-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fe88632a9-en&mimeType=pdf
|
| 217 |
+
OECD iLibrary,Public policy considerations,2019,OECD,https://www.oecd-ilibrary.org/public-policy-considerations_969ff07f-en.pdf?itemId=%2Fcontent%2Fcomponent%2F969ff07f-en&mimeType=pdf
|
| 218 |
+
OECD iLibrary,Previous work,2019,OECD,https://www.oecd-ilibrary.org/previous-work_633d28e7-en.pdf?itemId=%2Fcontent%2Fcomponent%2F633d28e7-en&mimeType=pdf
|
| 219 |
+
OECD iLibrary,Preface,2019,OECD,https://www.oecd-ilibrary.org/preface_89af43d8-en.pdf?itemId=%2Fcontent%2Fcomponent%2F89af43d8-en&mimeType=pdf
|
| 220 |
+
OECD iLibrary,Personalisation of learning: Towards hybrid human-AI learning technologies,2021,OECD,https://www.oecd-ilibrary.org/personalisation-of-learning-towards-hybrid-human-ai-learning-technologies_2cc25e37-en.pdf?itemId=%2Fcontent%2Fcomponent%2F2cc25e37-en&mimeType=pdf
|
| 221 |
+
OECD iLibrary,Performance of the SDG identification algorithm,2021,OECD,https://www.oecd-ilibrary.org/performance-of-the-sdg-identification-algorithm_d7af6eac-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd7af6eac-en&mimeType=pdf
|
| 222 |
+
OECD iLibrary,Overview: What the TALIS‑PISA link insights imply for policy and future research,2021,OECD,https://www.oecd-ilibrary.org/overview-what-the-talis-pisa-link-insights-imply-for-policy-and-future-research_9bc425ba-en.pdf?itemId=%2Fcontent%2Fcomponent%2F9bc425ba-en&mimeType=pdf
|
| 223 |
+
OECD iLibrary,On evaluating artificial intelligence systems: Competitions and benchmarks,2021,OECD,https://www.oecd-ilibrary.org/on-evaluating-artificial-intelligence-systems-competitions-and-benchmarks_d755c6d6-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd755c6d6-en&mimeType=pdf
|
| 224 |
+
OECD iLibrary,New approaches to understanding the impact of computers on work and education,2021,OECD,https://www.oecd-ilibrary.org/new-approaches-to-understanding-the-impact-of-computers-on-work-and-education_65774a32-en.pdf?itemId=%2Fcontent%2Fcomponent%2F65774a32-en&mimeType=pdf
|
| 225 |
+
OECD iLibrary,National policies for Artificial Intelligence: What about diffusion?,2021,OECD,https://www.oecd-ilibrary.org/national-policies-for-artificial-intelligence-what-about-diffusion_cc3a9728-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fcc3a9728-en&mimeType=pdf
|
| 226 |
+
OECD iLibrary,Methodology for assessing AI capabilities using the Survey of Adult Skills (PIAAC),2023,OECD,https://www.oecd-ilibrary.org/methodology-for-assessing-ai-capabilities-using-the-survey-of-adult-skills-piaac_b70b1373-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fb70b1373-en&mimeType=pdf
|
| 227 |
+
OECD iLibrary,Methodological guidelines to define functional areas,2020,OECD,https://www.oecd-ilibrary.org/methodological-guidelines-to-define-functional-areas_782b6659-en.pdf?itemId=%2Fcontent%2Fcomponent%2F782b6659-en&mimeType=pdf
|
| 228 |
+
OECD iLibrary,Data and indicator gaps on pressures and responses,2019,OECD,https://www.oecd-ilibrary.org/data-and-indicator-gaps-on-pressures-and-responses_bc88d5bf-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fbc88d5bf-en&mimeType=pdf
|
| 229 |
+
OECD iLibrary,Media freedoms and digital rights in Finland,2021,OECD,https://www.oecd-ilibrary.org/media-freedoms-and-digital-rights-in-finland_919641b1-en.pdf?itemId=%2Fcontent%2Fcomponent%2F919641b1-en&mimeType=pdf
|
| 230 |
+
OECD iLibrary,Media freedoms and civic space in the digital age in Romania,2023,OECD,https://www.oecd-ilibrary.org/media-freedoms-and-civic-space-in-the-digital-age-in-romania_cbc4ab42-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fcbc4ab42-en&mimeType=pdf
|
| 231 |
+
OECD iLibrary,Measuring the share of the private sector related to the SDGs,2021,OECD,https://www.oecd-ilibrary.org/measuring-the-share-of-the-private-sector-related-to-the-sdgs_4de00ac5-en.pdf?itemId=%2Fcontent%2Fcomponent%2F4de00ac5-en&mimeType=pdf
|
| 232 |
+
OECD iLibrary,Managing access to AI advances to safeguard countries’ essential security interests,2021,OECD,https://www.oecd-ilibrary.org/managing-access-to-ai-advances-to-safeguard-countries-essential-security-interests_2e819dc8-en.pdf?itemId=%2Fcontent%2Fcomponent%2F2e819dc8-en&mimeType=pdf
|
| 233 |
+
OECD iLibrary,Main findings and recommendations,2019,OECD,https://www.oecd-ilibrary.org/main-findings-and-recommendations_78f937cc-en.pdf?itemId=%2Fcontent%2Fcomponent%2F78f937cc-en&mimeType=pdf
|
| 234 |
+
OECD iLibrary,Skill needs and policies in the age of artificial intelligence,2023,OECD,https://www.oecd-ilibrary.org/skill-needs-and-policies-in-the-age-of-artificial-intelligence_638df49a-en.pdf?itemId=%2Fcontent%2Fcomponent%2F638df49a-en&mimeType=pdf
|
| 235 |
+
OECD iLibrary,Skills assessments in education,2021,OECD,https://www.oecd-ilibrary.org/skills-assessments-in-education_68191ce9-en.pdf?itemId=%2Fcontent%2Fcomponent%2F68191ce9-en&mimeType=pdf
|
| 236 |
+
OECD iLibrary,Social dialogue and collective bargaining in the age of artificial intelligence,2023,OECD,https://www.oecd-ilibrary.org/social-dialogue-and-collective-bargaining-in-the-age-of-artificial-intelligence_c35af387-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc35af387-en&mimeType=pdf
|
| 237 |
+
OECD iLibrary,Social Robots as educators,2021,OECD,https://www.oecd-ilibrary.org/social-robots-as-educators_1c3b1d56-en.pdf?itemId=%2Fcontent%2Fcomponent%2F1c3b1d56-en&mimeType=pdf
|
| 238 |
+
OECD iLibrary,Zusammenfassung,2020,OECD,https://www.oecd-ilibrary.org/zusammenfassung_adae5bf3-de.pdf?itemId=%2Fcontent%2Fcomponent%2Fadae5bf3-de&mimeType=pdf
|
| 239 |
+
OECD iLibrary,"Why everyone in Finland’s teaching themselves AI. Teemu Roos, U of Helsinki, tells us.",2019,OECD,https://www.oecd-ilibrary.org/why-everyone-in-finland-s-teaching-themselves-ai-teemu-roos-u-of-helsinki-tells-us_d1f98cfe-en.pdf?itemId=%2Fcontent%2Fmultimedia%2Fd1f98cfe-en&mimeType=pdf
|
| 240 |
+
OECD iLibrary,What do teachers and schools do that matters most for students' social and emotional development?,2021,OECD,https://www.oecd-ilibrary.org/what-do-teachers-and-schools-do-that-matters-most-for-students-social-and-emotional-development_d44d0f58-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd44d0f58-en&mimeType=pdf
|
| 241 |
+
OECD iLibrary,What can governments do to be ready for the future of work? With OECD’s Stefano Scarpetta,2019,OECD,https://www.oecd-ilibrary.org/what-can-governments-do-to-be-ready-for-the-future-of-work-with-oecd-s-stefano-scarpetta_2957db51-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F2957db51-en&mimeType=pdf
|
| 242 |
+
OECD iLibrary,What can artificial intelligence do for physics?,2023,OECD,https://www.oecd-ilibrary.org/what-can-artificial-intelligence-do-for-physics_724b14a6-en.pdf?itemId=%2Fcontent%2Fcomponent%2F724b14a6-en&mimeType=pdf
|
| 243 |
+
OECD iLibrary,“Virtual Assistant” for VAT,2019,OECD,https://www.oecd-ilibrary.org/virtual-assistant-for-vat_faa89db0-en.pdf?itemId=%2Fcontent%2Fcomponent%2Ffaa89db0-en&mimeType=pdf
|
| 244 |
+
OECD iLibrary,Using machine learning to verify scientific claims,2023,OECD,https://www.oecd-ilibrary.org/using-machine-learning-to-verify-scientific-claims_ab9d235c-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fab9d235c-en&mimeType=pdf
|
| 245 |
+
OECD iLibrary,Using human skills taxonomies and tests as measures of artificial intelligence,2021,OECD,https://www.oecd-ilibrary.org/using-human-skills-taxonomies-and-tests-as-measures-of-artificial-intelligence_e182dd0d-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fe182dd0d-en&mimeType=pdf
|
| 246 |
+
OECD iLibrary,Understanding digital transformation,2019,OECD,https://www.oecd-ilibrary.org/understanding-digital-transformation_58ee7fe5-en.pdf?itemId=%2Fcontent%2Fcomponent%2F58ee7fe5-en&mimeType=pdf
|
| 247 |
+
OECD iLibrary,Trends Shaping Education 2019,2019,OECD,https://www.oecd-ilibrary.org/trends-shaping-education-2019_5j8jll3f016g.pdf?itemId=%2Fcontent%2Fpublication%2Ftrends_edu-2019-en&mimeType=pdf
|
| 248 |
+
OECD iLibrary,Trends and policy frameworks for AI in finance,2021,OECD,https://www.oecd-ilibrary.org/trends-and-policy-frameworks-for-ai-in-finance_cbc9d1af-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fcbc9d1af-en&mimeType=pdf
|
| 249 |
+
OECD iLibrary,Trend 4: New ways of engaging citizens and residents,2023,OECD,https://www.oecd-ilibrary.org/trend-4-new-ways-of-engaging-citizens-and-residents_d5b3aed9-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd5b3aed9-en&mimeType=pdf
|
| 250 |
+
OECD iLibrary,"Machine reading: Successes, challenges and implications for science",2023,OECD,https://www.oecd-ilibrary.org/machine-reading-successes-challenges-and-implications-for-science_368178a6-en.pdf?itemId=%2Fcontent%2Fcomponent%2F368178a6-en&mimeType=pdf
|
| 251 |
+
OECD iLibrary,Trend 2: New approaches to care,2023,OECD,https://www.oecd-ilibrary.org/trend-2-new-approaches-to-care_9be6313e-en.pdf?itemId=%2Fcontent%2Fcomponent%2F9be6313e-en&mimeType=pdf
|
| 252 |
+
OECD iLibrary,The use of SupTech to enhance market supervision and integrity,2021,OECD,https://www.oecd-ilibrary.org/the-use-of-suptech-to-enhance-market-supervision-and-integrity_d478df4c-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd478df4c-en&mimeType=pdf
|
| 253 |
+
OECD iLibrary,The technical landscape,2019,OECD,https://www.oecd-ilibrary.org/the-technical-landscape_8b303b6f-en.pdf?itemId=%2Fcontent%2Fcomponent%2F8b303b6f-en&mimeType=pdf
|
| 254 |
+
OECD iLibrary,The skill profiles and the competences of workers in digital occupations,2022,OECD,https://www.oecd-ilibrary.org/the-skill-profiles-and-the-competences-of-workers-in-digital-occupations_6bafcb87-en.pdf?itemId=%2Fcontent%2Fcomponent%2F6bafcb87-en&mimeType=pdf
|
| 255 |
+
OECD iLibrary,The rule of law: A fragile tool for the development of emerging nuclear technologies,2023,OECD,https://www.oecd-ilibrary.org/the-rule-of-law-a-fragile-tool-for-the-development-of-emerging-nuclear-technologies_3bd72ca3-en.pdf?itemId=%2Fcontent%2Fpaper%2F3bd72ca3-en&mimeType=pdf
|
| 256 |
+
OECD iLibrary,The importance of knowledge bases for artificial intelligence in science,2023,OECD,https://www.oecd-ilibrary.org/the-importance-of-knowledge-bases-for-artificial-intelligence-in-science_3aba9f4b-en.pdf?itemId=%2Fcontent%2Fcomponent%2F3aba9f4b-en&mimeType=pdf
|
| 257 |
+
OECD iLibrary,The encroachment of artificial intelligence: Timing and prospects,2021,OECD,https://www.oecd-ilibrary.org/the-encroachment-of-artificial-intelligence-timing-and-prospects_e39255bb-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fe39255bb-en&mimeType=pdf
|
| 258 |
+
OECD iLibrary,The economic landscape,2019,OECD,https://www.oecd-ilibrary.org/the-economic-landscape_3abc27f1-en.pdf?itemId=%2Fcontent%2Fcomponent%2F3abc27f1-en&mimeType=pdf
|
| 259 |
+
OECD iLibrary,The case for a digital government in Mexico,2020,OECD,https://www.oecd-ilibrary.org/the-case-for-a-digital-government-in-mexico_6a7384e3-en.pdf?itemId=%2Fcontent%2Fcomponent%2F6a7384e3-en&mimeType=pdf
|
| 260 |
+
OECD iLibrary,The air we breathe : Rich Fuller of Pure Earth,2019,OECD,https://www.oecd-ilibrary.org/the-air-we-breathe-rich-fuller-of-pure-earth_9a00aff1-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F9a00aff1-en&mimeType=pdf
|
| 261 |
+
OECD iLibrary,Test No. 471: Bacterial Reverse Mutation Test,2020,OECD,https://www.oecd-ilibrary.org/test-no-471-bacterial-reverse-mutation-test_5lmqcr2k7mg0.pdf?itemId=%2Fcontent%2Fpublication%2F9789264071247-en&mimeType=pdf
|
| 262 |
+
OECD iLibrary,Technische Grundlagen,2020,OECD,https://www.oecd-ilibrary.org/technische-grundlagen_64ae49f7-de.pdf?itemId=%2Fcontent%2Fcomponent%2F64ae49f7-de&mimeType=pdf
|
| 263 |
+
OECD iLibrary,Tasks and tests for assessing artificial intelligence and robotics in comparison with humans,2021,OECD,https://www.oecd-ilibrary.org/tasks-and-tests-for-assessing-artificial-intelligence-and-robotics-in-comparison-with-humans_265f8d24-en.pdf?itemId=%2Fcontent%2Fcomponent%2F265f8d24-en&mimeType=pdf
|
| 264 |
+
OECD iLibrary,Trend 1: New forms of accountability for a new era of government,2023,OECD,https://www.oecd-ilibrary.org/trend-1-new-forms-of-accountability-for-a-new-era-of-government_1b12de43-en.pdf?itemId=%2Fcontent%2Fcomponent%2F1b12de43-en&mimeType=pdf
|
| 265 |
+
OECD iLibrary,Leveraging artificial intelligence for proactive delivery of public policies and services,2023,OECD,https://www.oecd-ilibrary.org/leveraging-artificial-intelligence-for-proactive-delivery-of-public-policies-and-services_5702d250-en.pdf?itemId=%2Fcontent%2Fcomponent%2F5702d250-en&mimeType=pdf
|
| 266 |
+
OECD iLibrary,Methodological algorithms,2020,OECD,https://www.oecd-ilibrary.org/methodological-algorithms_caf29d59-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fcaf29d59-en&mimeType=pdf
|
| 267 |
+
OECD iLibrary,LAC Artificial Intelligence strategies,2022,OECD,https://www.oecd-ilibrary.org/lac-artificial-intelligence-strategies_636827ae-en.pdf?itemId=%2Fcontent%2Fcomponent%2F636827ae-en&mimeType=pdf
|
| 268 |
+
OECD iLibrary,Artificial intelligence for science and engineering: A priority for public investment in research and development,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-for-science-and-engineering-a-priority-for-public-investment-in-research-and-development_7b7b1bce-en.pdf?itemId=%2Fcontent%2Fcomponent%2F7b7b1bce-en&mimeType=pdf
|
| 269 |
+
OECD iLibrary,Artificial intelligence for science in Africa,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-for-science-in-africa_399730cc-en.pdf?itemId=%2Fcontent%2Fcomponent%2F399730cc-en&mimeType=pdf
|
| 270 |
+
OECD iLibrary,Artificial intelligence in education: Bringing it all together,2021,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-in-education-bringing-it-all-together_f54ea644-en.pdf?itemId=%2Fcontent%2Fcomponent%2Ff54ea644-en&mimeType=pdf
|
| 271 |
+
OECD iLibrary,Artificial intelligence in science: Overview and policy proposals,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-in-science-overview-and-policy-proposals_a2817e1f-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fa2817e1f-en&mimeType=pdf
|
| 272 |
+
OECD iLibrary,Artificial intelligence in scientific discovery: Challenges and opportunities,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-in-scientific-discovery-challenges-and-opportunities_ca841465-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fca841465-en&mimeType=pdf
|
| 273 |
+
OECD iLibrary,Lessons from shortcomings in machine learning for medical imaging,2023,OECD,https://www.oecd-ilibrary.org/lessons-from-shortcomings-in-machine-learning-for-medical-imaging_b885eecd-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fb885eecd-en&mimeType=pdf
|
| 274 |
+
OECD iLibrary,Artificial Intelligence: Managing the ethical challenges,2021,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-managing-the-ethical-challenges_54c51e69-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F54c51e69-en&mimeType=pdf
|
| 275 |
+
OECD iLibrary,Artificial Intelligence: Regulation Can Support Innovation,2021,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-regulation-can-support-innovation_f7fe0e1d-en.pdf?itemId=%2Fcontent%2Fmultimedia%2Ff7fe0e1d-en&mimeType=pdf
|
| 276 |
+
OECD iLibrary,Assessing artificial intelligence capabilities,2021,OECD,https://www.oecd-ilibrary.org/assessing-artificial-intelligence-capabilities_47d04fe3-en.pdf?itemId=%2Fcontent%2Fcomponent%2F47d04fe3-en&mimeType=pdf
|
| 277 |
+
OECD iLibrary,Assessing collective intelligence in human groups,2021,OECD,https://www.oecd-ilibrary.org/assessing-collective-intelligence-in-human-groups_ce863473-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fce863473-en&mimeType=pdf
|
| 278 |
+
OECD iLibrary,Assessing Household Financial Vulnerability: Empirical evidence from the U.S. using machine learning,2019,OECD,https://www.oecd-ilibrary.org/assessing-household-financial-vulnerability-empirical-evidence-from-the-u-s-using-machine-learning_75c63aa1-en.pdf?itemId=%2Fcontent%2Fcomponent%2F75c63aa1-en&mimeType=pdf
|
| 279 |
+
OECD iLibrary,Assessing Natural Language Processing,2021,OECD,https://www.oecd-ilibrary.org/assessing-natural-language-processing_fcd5e244-en.pdf?itemId=%2Fcontent%2Fcomponent%2Ffcd5e244-en&mimeType=pdf
|
| 280 |
+
OECD iLibrary,Artificial Intelligence-enabled adaptive assessments with Intelligent Tutors,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-enabled-adaptive-assessments-with-intelligent-tutors_22731ca8-en.pdf?itemId=%2Fcontent%2Fcomponent%2F22731ca8-en&mimeType=pdf
|
| 281 |
+
OECD iLibrary,Assessment and recommendations,2019,OECD,https://www.oecd-ilibrary.org/assessment-and-recommendations_cdb89610-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fcdb89610-en&mimeType=pdf
|
| 282 |
+
OECD iLibrary,Bringing space to earth with data-driven activities,2019,OECD,https://www.oecd-ilibrary.org/bringing-space-to-earth-with-data-driven-activities_07d50927-en.pdf?itemId=%2Fcontent%2Fcomponent%2F07d50927-en&mimeType=pdf
|
| 283 |
+
OECD iLibrary,Building an assessment of artificial intelligence capabilities,2021,OECD,https://www.oecd-ilibrary.org/building-an-assessment-of-artificial-intelligence-capabilities_01421d08-en.pdf?itemId=%2Fcontent%2Fcomponent%2F01421d08-en&mimeType=pdf
|
| 284 |
+
OECD iLibrary,Building key governance capacities,2022,OECD,https://www.oecd-ilibrary.org/building-key-governance-capacities_56a4e1d2-en.pdf?itemId=%2Fcontent%2Fcomponent%2F56a4e1d2-en&mimeType=pdf
|
| 285 |
+
OECD iLibrary,Case study: Planning for the future of work,2021,OECD,https://www.oecd-ilibrary.org/case-study-planning-for-the-future-of-work_ff4b8bd3-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fff4b8bd3-en&mimeType=pdf
|
| 286 |
+
OECD iLibrary,Changes in AI capabilities in literacy and numeracy between 2016 and 2021,2023,OECD,https://www.oecd-ilibrary.org/changes-in-ai-capabilities-in-literacy-and-numeracy-between-2016-and-2021_4301a378-en.pdf?itemId=%2Fcontent%2Fcomponent%2F4301a378-en&mimeType=pdf
|
| 287 |
+
OECD iLibrary,Combining collective and machine intelligence at the knowledge frontier,2023,OECD,https://www.oecd-ilibrary.org/combining-collective-and-machine-intelligence-at-the-knowledge-frontier_dbbd48a9-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fdbbd48a9-en&mimeType=pdf
|
| 288 |
+
OECD iLibrary,Common sense skills: Artificial intelligence and the workplace,2021,OECD,https://www.oecd-ilibrary.org/common-sense-skills-artificial-intelligence-and-the-workplace_5fe70a0c-en.pdf?itemId=%2Fcontent%2Fcomponent%2F5fe70a0c-en&mimeType=pdf
|
| 289 |
+
OECD iLibrary,Competence assessment in German vocational education and training,2021,OECD,https://www.oecd-ilibrary.org/competence-assessment-in-german-vocational-education-and-training_c3d7aa74-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc3d7aa74-en&mimeType=pdf
|
| 290 |
+
OECD iLibrary,Competition and AI,2021,OECD,https://www.oecd-ilibrary.org/competition-and-ai_3acbe1cd-en.pdf?itemId=%2Fcontent%2Fcomponent%2F3acbe1cd-en&mimeType=pdf
|
| 291 |
+
OECD iLibrary,Conclusion and recommendations,2022,OECD,https://www.oecd-ilibrary.org/conclusion-and-recommendations_c61de01b-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc61de01b-en&mimeType=pdf
|
| 292 |
+
OECD iLibrary,Consumer policy in the digital transformation,2020,OECD,https://www.oecd-ilibrary.org/consumer-policy-in-the-digital-transformation_7570fa4a-en.pdf?itemId=%2Fcontent%2Fcomponent%2F7570fa4a-en&mimeType=pdf
|
| 293 |
+
OECD iLibrary,Cracking the glass ceiling on wages: Gapsquare CEO Zara Nanu,2019,OECD,https://www.oecd-ilibrary.org/cracking-the-glass-ceiling-on-wages-gapsquare-ceo-zara-nanu_ca12b314-en.pdf?itemId=%2Fcontent%2Fmultimedia%2Fca12b314-en&mimeType=pdf
|
| 294 |
+
OECD iLibrary,Bringing health into the 21st century,2019,OECD,https://www.oecd-ilibrary.org/bringing-health-into-the-21st-century_e130fcc2-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fe130fcc2-en&mimeType=pdf
|
| 295 |
+
OECD iLibrary,"Artificial intelligence, digital technology and advanced production",2020,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-digital-technology-and-advanced-production_629af843-en.pdf?itemId=%2Fcontent%2Fcomponent%2F629af843-en&mimeType=pdf
|
| 296 |
+
OECD iLibrary,"Artificial intelligence, job quality and inclusiveness",2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-job-quality-and-inclusiveness_99c4c123-en.pdf?itemId=%2Fcontent%2Fcomponent%2F99c4c123-en&mimeType=pdf
|
| 297 |
+
OECD iLibrary,Artificial intelligence: Changing landscape for SMEs,2021,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-changing-landscape-for-smes_01a4ae9d-en.pdf?itemId=%2Fcontent%2Fcomponent%2F01a4ae9d-en&mimeType=pdf
|
| 298 |
+
OECD iLibrary,Korea,2021,OECD,https://www.oecd-ilibrary.org/korea_88d8a0bc-en.pdf?itemId=%2Fcontent%2Fcomponent%2F88d8a0bc-en&mimeType=pdf
|
| 299 |
+
OECD iLibrary,Knowledge and power,2022,OECD,https://www.oecd-ilibrary.org/knowledge-and-power_6cca2555-en.pdf?itemId=%2Fcontent%2Fcomponent%2F6cca2555-en&mimeType=pdf
|
| 300 |
+
OECD iLibrary,Is there a narrowing of AI research?,2023,OECD,https://www.oecd-ilibrary.org/is-there-a-narrowing-of-ai-research_77709ef0-en.pdf?itemId=%2Fcontent%2Fcomponent%2F77709ef0-en&mimeType=pdf
|
| 301 |
+
OECD iLibrary,Introduction,2022,OECD,https://www.oecd-ilibrary.org/introduction_c545040a-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc545040a-en&mimeType=pdf
|
| 302 |
+
OECD iLibrary,Interpretability: Should – and can – we understand the reasoning of machine-learning systems?,2023,OECD,https://www.oecd-ilibrary.org/interpretability-should-and-can-we-understand-the-reasoning-of-machine-learning-systems_2d0478b9-en.pdf?itemId=%2Fcontent%2Fcomponent%2F2d0478b9-en&mimeType=pdf
|
| 303 |
+
OECD iLibrary,A framework for evaluating the AI-driven automation of science,2023,OECD,https://www.oecd-ilibrary.org/a-framework-for-evaluating-the-ai-driven-automation-of-science_63faa850-en.pdf?itemId=%2Fcontent%2Fcomponent%2F63faa850-en&mimeType=pdf
|
| 304 |
+
OECD iLibrary,"Artificial intelligence, developing-country science and bilateral co‑operation",2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-developing-country-science-and-bilateral-co-operation_4edb761e-en.pdf?itemId=%2Fcontent%2Fcomponent%2F4edb761e-en&mimeType=pdf
|
| 305 |
+
OECD iLibrary,Abilities and skills: Assessing humans and artificial intelligence/robotics systems,2021,OECD,https://www.oecd-ilibrary.org/abilities-and-skills-assessing-humans-and-artificial-intelligence-robotics-systems_497be8f9-en.pdf?itemId=%2Fcontent%2Fcomponent%2F497be8f9-en&mimeType=pdf
|
| 306 |
+
OECD iLibrary,Adaptability,2019,OECD,https://www.oecd-ilibrary.org/adaptability_3d8ecdfb-en.pdf?itemId=%2Fcontent%2Fcomponent%2F3d8ecdfb-en&mimeType=pdf
|
| 307 |
+
OECD iLibrary,Addressing labour-market disruptions from trade and automation,2019,OECD,https://www.oecd-ilibrary.org/addressing-labour-market-disruptions-from-trade-and-automation_e309eca0-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fe309eca0-en&mimeType=pdf
|
| 308 |
+
OECD iLibrary,AI and scientific productivity: Considering policy and governance challenges,2023,OECD,https://www.oecd-ilibrary.org/ai-and-scientific-productivity-considering-policy-and-governance-challenges_84cde28b-en.pdf?itemId=%2Fcontent%2Fcomponent%2F84cde28b-en&mimeType=pdf
|
| 309 |
+
OECD iLibrary,AI applications,2019,OECD,https://www.oecd-ilibrary.org/ai-applications_79edf9d8-en.pdf?itemId=%2Fcontent%2Fcomponent%2F79edf9d8-en&mimeType=pdf
|
| 310 |
+
OECD iLibrary,AI in drug discovery,2023,OECD,https://www.oecd-ilibrary.org/ai-in-drug-discovery_6717b361-en.pdf?itemId=%2Fcontent%2Fcomponent%2F6717b361-en&mimeType=pdf
|
| 311 |
+
OECD iLibrary,A tale of two worlds: Machine learning approaches at the intersection with educational measurement,2023,OECD,https://www.oecd-ilibrary.org/a-tale-of-two-worlds-machine-learning-approaches-at-the-intersection-with-educational-measurement_d01eb8a4-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fd01eb8a4-en&mimeType=pdf
|
| 312 |
+
OECD iLibrary,AI policies and initiatives,2019,OECD,https://www.oecd-ilibrary.org/ai-policies-and-initiatives_cf3f3be0-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fcf3f3be0-en&mimeType=pdf
|
| 313 |
+
OECD iLibrary,AI in finance,2021,OECD,https://www.oecd-ilibrary.org/ai-in-finance_39b6299a-en.pdf?itemId=%2Fcontent%2Fcomponent%2F39b6299a-en&mimeType=pdf
|
| 314 |
+
OECD iLibrary,"Artificial intelligence, blockchain and quantum computing",2020,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-blockchain-and-quantum-computing_c51bcfeb-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fc51bcfeb-en&mimeType=pdf
|
| 315 |
+
OECD iLibrary,Artificial intelligence and the labour market: Introduction,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-and-the-labour-market-introduction_63bcc69a-en.pdf?itemId=%2Fcontent%2Fcomponent%2F63bcc69a-en&mimeType=pdf
|
| 316 |
+
OECD iLibrary,Artificial intelligence and jobs: No signs of slowing labour demand (yet),2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-and-jobs-no-signs-of-slowing-labour-demand-yet_9c86de40-en.pdf?itemId=%2Fcontent%2Fcomponent%2F9c86de40-en&mimeType=pdf
|
| 317 |
+
OECD iLibrary,Artificial intelligence and development projects: A case study in funding mechanisms to optimise research excellence in sub-Saharan Africa,2023,OECD,https://www.oecd-ilibrary.org/artificial-intelligence-and-development-projects-a-case-study-in-funding-mechanisms-to-optimise-research-excellence-in-sub-saharan-africa_f41aa308-en.pdf?itemId=%2Fcontent%2Fcomponent%2Ff41aa308-en&mimeType=pdf
|
| 318 |
+
OECD iLibrary,Identifying artificial intelligence capabilities: What and how to test,2021,OECD,https://www.oecd-ilibrary.org/identifying-artificial-intelligence-capabilities-what-and-how-to-test_85aeb432-en.pdf?itemId=%2Fcontent%2Fcomponent%2F85aeb432-en&mimeType=pdf
|
| 319 |
+
OECD iLibrary,Implications of evolving AI capabilities for employment and education,2023,OECD,https://www.oecd-ilibrary.org/implications-of-evolving-ai-capabilities-for-employment-and-education_ed919621-en.pdf?itemId=%2Fcontent%2Fcomponent%2Fed919621-en&mimeType=pdf
|
| 320 |
+
OECD iLibrary,ANPAL Guidelines,2019,OECD,https://www.oecd-ilibrary.org/anpal-guidelines_1373d882-en.pdf?itemId=%2Fcontent%2Fcomponent%2F1373d882-en&mimeType=pdf
|
| 321 |
+
OECD iLibrary,An overview of key developments and policies,2020,OECD,https://www.oecd-ilibrary.org/an-overview-of-key-developments-and-policies_5260917b-en.pdf?itemId=%2Fcontent%2Fcomponent%2F5260917b-en&mimeType=pdf
|
| 322 |
+
OECD iLibrary,An occupational taxonomic approach to assessing AI capabilities,2021,OECD,https://www.oecd-ilibrary.org/an-occupational-taxonomic-approach-to-assessing-ai-capabilities_2c1d8961-en.pdf?itemId=%2Fcontent%2Fcomponent%2F2c1d8961-en&mimeType=pdf
|
| 323 |
+
OECD iLibrary,All about AI: Should we be concerned about artificial intelligence?,2020,OECD,https://www.oecd-ilibrary.org/all-about-ai-should-we-be-concerned-about-artificial-intelligence_1b63c3bd-en.pdf?itemId=%2Fcontent%2Fmultimedia%2F1b63c3bd-en&mimeType=pdf
|
| 324 |
+
OECD iLibrary,AI use cases in LAC governments,2022,OECD,https://www.oecd-ilibrary.org/ai-use-cases-in-lac-governments_08955f48-en.pdf?itemId=%2Fcontent%2Fcomponent%2F08955f48-en&mimeType=pdf
|
| 325 |
+
OECD iLibrary,"Applying AI to real-world health-care settings and the life sciences: Tackling data privacy, security and policy challenges with federated learning",2023,OECD,https://www.oecd-ilibrary.org/applying-ai-to-real-world-health-care-settings-and-the-life-sciences-tackling-data-privacy-security-and-policy-challenges-with-federated-learning_058a23d0-en.pdf?itemId=%2Fcontent%2Fcomponent%2F058a23d0-en&mimeType=pdf
|
| 326 |
+
OECD publications,What are the OECD Principles on AI,2020,OECD,https://www.oecd-ilibrary.org/docserver/6ff2a1c4-en.pdf?expires=1684155213&id=id&accname=guest&checksum=47DD8B6DF2D9129E96D568E8A575B941
|
| 327 |
+
OECD publications,Examples of LAC AI instruments aligned with OECD AI values-based principles,2021,OECD,https://www.oecd-ilibrary.org/sites/5fbd4ea6-en/index.html?itemId=/content/component/5fbd4ea6-en
|
| 328 |
+
Policy documents,A Framework for Developing a National Artificial Intelligence Strategy Centre for Fourth Industrial Revolution,2019,World Economic Forum,https://www3.weforum.org/docs/WEF_National_AI_Strategy.pdf?_gl=1*1ycz2tk*_up*MQ..&gclid=EAIaIQobChMI2LuIqrL1_gIVSazVCh3WZA_0EAAYASAAEgKY9fD_BwE
|
| 329 |
+
Policy documents,Memorandum for the Heads of Executive Departments and Agencies,2020,United States,https://www.whitehouse.gov/wp-content/uploads/2020/01/Draft-OMB-Memo-on-Regulation-of-AI-1-7-19.pdf
|
| 330 |
+
Policy documents,AI Voor Nederland,2018,Netherlands,https://www.vno-ncw.nl/sites/default/files/aivnl_20181106_0.pdf
|
| 331 |
+
Policy documents,Preparing for the Future of Transportation,2019,United States,https://www.transportation.gov/sites/dot.gov/files/docs/policy-initiatives/automated-vehicles/320711/preparing-future-transportation-automated-vehicle-30.pdf
|
| 332 |
+
Policy documents,Outline for a German Strategy for Artificial Intelligence,2018,Germany,https://www.stiftung-nv.de/sites/default/files/outline_for_a_german_artificial_intelligence_strategy.pdf
|
| 333 |
+
Policy documents,AUS AI Standards Roadmap,2020,Australia,https://www.standards.org.au/getmedia/ede81912-55a2-4d8e-849f-9844993c3b9d/O_1515-An-Artificial-Intelligence-Standards-Roadmap-soft_1.pdf.aspx
|
| 334 |
+
Policy documents,AI Report,2019,Estonia,https://www.ria.ee/en/media/580/download
|
| 335 |
+
Policy documents,Draft AI R&D Guidelines for International Discussions,2017,Japan,https://www.soumu.go.jp/main_content/000507517.pdf
|
| 336 |
+
Policy documents,Saudi Vision 2030,2019,Saudi Arabia,https://www.saudiembassy.net/sites/default/files/u66/Saudi_Vision2030_EN.pdf
|
| 337 |
+
Policy documents,National Strategy for Artificial Intelligence,2020,Norway,https://www.regjeringen.no/contentassets/1febbbb2c4fd4b7d92c67ddd353b6ae8/en-gb/pdfs/ki-strategi_en.pdf
|
| 338 |
+
Policy documents,Saudi PWC Economic Potential AI Middle East,2018,Saudi Arabia,https://www.pwc.com/m1/en/publications/documents/economic-potential-ai-middle-east.pdf
|
| 339 |
+
Policy documents,Model Artificial Intelligence Governance Framework Second Edition,2020,Singapore,https://www.pdpc.gov.sg/-/media/files/pdpc/pdf-files/resource-for-organisation/ai/sgmodelaigovframework2.pdf
|
| 340 |
+
Policy documents,Draft AI Utilization Principles,2018,Japan,https://www.soumu.go.jp/main_content/000581310.pdf
|
| 341 |
+
Policy documents,Examples Of Ai National Policies,2020,OECD,https://www.oecd.org/sti/examples-of-ai-national-policies.pdf
|
| 342 |
+
Policy documents,Unlocking Armenia’s AI Potential,2021,Armenia,/
|
| 343 |
+
Policy documents,Artificial Intelligence Research Agenda for the Netherlands,2019,Netherlands,https://www.nwo.nl/sites/nwo/files/documents/AIREA-NL%20AI%20Research%20Agenda%20for%20the%20Netherlands.pdf
|
| 344 |
+
Policy documents,National Strategy for Artificial Intelligence,2019,Denmark,https://eng.em.dk/media/13081/305755-gb-version_4k.pdf
|
| 345 |
+
Policy documents,DIRECTIVE (EU) 2019/1024 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 20 June 2019 on open data and the re-use of public sector information,2019,European Union,https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32019L1024
|
| 346 |
+
Policy documents,"Report on the safety and liability implications of Artificial Intelligence, the Internet of Things and robotics",2020,European Union,https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52020DC0064
|
| 347 |
+
Policy documents,2030 Digital Compass: the European way for the Digital Decade,2021,European Union,https://eur-lex.europa.eu/resource.html?uri=cellar:12e835e2-81af-11eb-9ac9-01aa75ed71a1.0001.02/DOC_1&format=PDF
|
| 348 |
+
Policy documents,Singapore Compendium of Use Cases Vol 2,2020,Singapore,https://file.go.gov.sg/ai-gov-use-cases-2.pdf
|
| 349 |
+
Policy documents,Zonas Libres Tecnologicas,2020,Portugal,https://files.dre.pt/1s/2020/04/07800/0000600032.pdf
|
| 350 |
+
Policy documents,New Generation of Artificial Intelligence Development Plan,2017,China,https://flia.org/wp-content/uploads/2017/07/A-New-Generation-of-Artificial-Intelligence-Development-Plan-1.pdf
|
| 351 |
+
Policy documents,Towards an AI Strategy In Mexico: Harnessing the AI Revolution,2018,Mexico,https://go.wizeline.com/rs/571-SRN-279/images/Towards-an-AI-strategy-in-Mexico.pdf
|
| 352 |
+
Policy documents,Strategy for Denmark’s Digital Growth,2018,Denmark,https://eng.em.dk/media/10566/digital-growth-strategy-report_uk_web-2.pdf
|
| 353 |
+
Policy documents,Artificial Intelligence: A Strategic Vision for Luxembourg.,2019,Luxembourg,https://gouvernement.lu/dam-assets/fr/publications/rapport-etude-analyse/minist-digitalisation/Artificial-Intelligence-a-strategic-vision-for-Luxembourg.pdf
|
| 354 |
+
Policy documents,Artificial Ingelligence at the service of citizens,2018,Italy,https://ia.italia.it/assets/whitepaper.pdf
|
| 355 |
+
Policy documents,Portugal INCoDe 2030,2021,Portugal,https://incode2030.pt/sites/default/files/incode2030_en_0.pdf
|
| 356 |
+
Policy documents,National Strategy for Artificial Ingelligence,2018,India,https://indiaai.gov.in/documents/pdf/NationalStrategy-for-AI-Discussion-Paper.pdf
|
| 357 |
+
Policy documents,China AI Development Report,2018,China,https://indianstrategicknowledgeonline.com/web/China_AI_development_report_2018.pdf
|
| 358 |
+
Policy documents,Finland’s Age of Artificial Intelligence,2017,Finland,https://julkaisut.valtioneuvosto.fi/bitstream/handle/10024/160391/TEMrap_47_2017_verkkojulkaisu.pdf
|
| 359 |
+
Policy documents,Work in the age of artificial intelligence,2018,Finland,https://julkaisut.valtioneuvosto.fi/bitstream/handle/10024/160980/TEMjul_21_2018_Work_in_the_age.pdf
|
| 360 |
+
Policy documents,Malta Towards an AI Strategy: High-level policy document for public consultation,2019,Malta,https://malta.ai/wp-content/uploads/2019/04/Draft_Policy_document_-_online_version.pdf
|
| 361 |
+
Policy documents,Summary of the 2018 Department of Defense Artificial Intelligence Strategy,2018,United States,https://media.defense.gov/2019/Feb/12/2002088963/-1/-1/1/SUMMARY-OF-DOD-AI-STRATEGY.PDF
|
| 362 |
+
Policy documents,The Data-Driven Innovation Strategy for the Development of a Trusted and Sustainable Economy in Luxembourg,2019,Luxembourg,https://gouvernement.lu/dam-assets/fr/publications/rapport-etude-analyse/minist-economie/The-Data-driven-Innovation-Strategy.pdf
|
| 363 |
+
Policy documents,Data for the Benefit of the People: Recommendations from the Danish Expert Group on Data Ethics,2018,Denmark,https://em.dk/media/12190/dataethics-v2.pdf
|
| 364 |
+
Policy documents,Shaping Europe's digital future – Questions and Answers,2020,European Union,https://ec.europa.eu/commission/presscorner/api/files/document/print/en/qanda_20_264/QANDA_20_264_EN.pdf
|
| 365 |
+
Policy documents,Member States and Commission to work together to boost artificial intelligence made in Europe,2018,European Union,https://ec.europa.eu/commission/presscorner/api/files/document/print/en/ip_18_6689/IP_18_6689_EN.pdf
|
| 366 |
+
Policy documents,"AUS Tech Future: Delivering a Strong, Safe and Inclusive Digital Economy",2018,Australia,Missing
|
| 367 |
+
Policy documents,The Effective and Ethical Development of Artificial Intelligence,2019,Australia,https://acola.org/wp-content/uploads/2019/07/hs4_artificial-intelligence-report.pdf
|
| 368 |
+
Policy documents,AI 4 Belgium,2019,Belgium,https://ai4belgium.be/wp-content/uploads/2019/04/report_en.pdf
|
| 369 |
+
Policy documents,National AI Strategy,2021,United Kingdom,https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1020402/National_AI_Strategy_-_PDF_version.pdf
|
| 370 |
+
Policy documents,The Pathway to Driverless Cars Summary report and action plan,2015,United Kingdom,https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/401562/pathway-driverless-cars-summary.pdf
|
| 371 |
+
Policy documents,Growing the Artificial Intelligence Industry in the UK,2019,United Kingdom,https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/652097/Growing_the_artificial_intelligence_industry_in_the_UK.pdf
|
| 372 |
+
Policy documents,Industrial Strategy Artificial Intelligence Sector Deal,2018,United Kingdom,https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/702810/180425_BEIS_AI_Sector_Deal__4_.pdf
|
| 373 |
+
Policy documents,Realising the potential of technology in education: A strategy for education providers and the technology industry,2019,United Kingdom,https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/791931/DfE-Education_Technology_Strategy.pdf
|
| 374 |
+
Policy documents,"Strategic Research, Innovation and Deployment Agenda- AI, Data and Robotics Partnership",2020,European Union,https://bdva.eu/sites/default/files/AI-Data-Robotics-Partnership-SRIDA%20V3.1.pdf
|
| 375 |
+
Policy documents,Ethics Commission Automated And Connected Driving,2017,Germany,https://bmdv.bund.de/SharedDocs/EN/publications/report-ethics-commission-automated-and-connected-driving.pdf?__blob=publicationFile
|
| 376 |
+
Policy documents,Rebooting Regulation: Exploring the Future of AI Policy in Canada,2020,Canada,https://cifar.ca/wp-content/uploads/2020/01/rebooting-regulation-exploring-the-future-of-ai-policy-in-canada.pdf
|
| 377 |
+
Policy documents,AICan 2019- Annual Report of the CIFAR Pan-Canadian AI Strategy,2019,Canada,https://cifar.ca/wp-content/uploads/2020/04/ai_annualreport2019_web.pdf
|
| 378 |
+
Policy documents,Cifar Annual Report 2018-2019,2019,Canada,https://cifar.ca/wp-content/uploads/2020/04/annualreport20182019.pdf
|
| 379 |
+
Policy documents,Pan-Canadian AI Strategy Impact Assessment Report,2020,Canada,https://cifar.ca/wp-content/uploads/2020/11/Pan-Canadian-AI-Strategy-Impact-Assessment-Report.pdf
|
| 380 |
+
Policy documents,White Paper On Artificial Intelligence - A European approach to excellence and trust,2020,European Union,https://commission.europa.eu/system/files/2020-02/commission-white-paper-artificial-intelligence-feb2020_en.pdf
|
| 381 |
+
Policy documents,Estimating investments in General Purpose Technologies,2020,European Union,https://core.ac.uk/download/pdf/322748045.pdf
|
| 382 |
+
Policy documents,Artificial Intelligence Standardization White Paper,2018,China,https://cset.georgetown.edu/wp-content/uploads/t0120_AI_standardization_white_paper_EN.pdf
|
| 383 |
+
Policy documents,AI Technology Roadmap,2019,Australia,https://data61.csiro.au/~/media/D61/AI-Roadmap-assets/19-00346_DATA61_REPORT_AI-Roadmap_WEB_191111.pdf?la=en&hash=58386288921D9C21EC8C4861CDFD863F1FBCD457
|
| 384 |
+
Policy documents,Summary of the National Defense Strategy of The United States of America,2018,United States,https://dod.defense.gov/Portals/1/Documents/pubs/2018-National-Defense-Strategy-Summary.pdf
|
| 385 |
+
Policy documents,AI Principles: Recommendations on the Ethical Use of Artificial Intelligence by the Department of Defense,2019,United States,https://media.defense.gov/2019/Oct/31/2002204458/-1/-1/0/DIB_AI_PRINCIPLES_PRIMARY_DOCUMENT.PDF
|
| 386 |
+
Policy documents,Integrated Innovation Strategy,2018,Japan,https://www8.cao.go.jp/cstp/english/doc/integrated_main.pdf
|
| 387 |
+
Policy documents,"Artificial Intelligence, Automation, and the Economy",2016,United States,https://obamawhitehouse.archives.gov/sites/whitehouse.gov/files/documents/Artificial-Intelligence-Automation-Economy.PDF
|
| 388 |
+
Policy documents,The Age of Artificial Intelligence- Towards a European Strategy for Human-Centric Machines,2018,European Union,https://op.europa.eu/en/publication-detail/-/publication/f22f6811-1007-11ea-8c1f-01aa75ed71a1/language-en
|
| 389 |
+
Policy documents,Initial code of conduct for data-driven health and care technology,2018,United Kingdom,https://www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology/initial-code-of-conduct-for-data-driven-health-and-care-technology
|
| 390 |
+
Policy documents,US Executive Order - Maintaining American Leadership in Artificial Intelligence,2019,United States,https://www.govinfo.gov/content/pkg/FR-2019-02-14/pdf/2019-02544.pdf
|
| 391 |
+
Policy documents,Better Together? Franco-German Cooperation on AI,2018,Germany,https://www.hertie-school.org/fileadmin/user_upload/20181218_Dt-frz-KI_Dittrich_neu.pdf
|
| 392 |
+
Policy documents,Industry 4.0 Testlabs in Australia Preparing for the Future,2017,Australia,https://www.industry.gov.au/sites/default/files/July%202018/document/pdf/industry-4.0-testlabs-report.pdf
|
| 393 |
+
Policy documents,AUS 2030-Prosperity Through Innovation,2017,Australia,https://www.industry.gov.au/sites/default/files/May%202018/document/pdf/australia-2030-prosperity-through-innovation-full-report.pdf
|
| 394 |
+
Policy documents,Digital Transformation towards 2030 in Portugal,2018,Portugal,https://www.itu.int/en/ITU-D/Regional-Presence/Europe/Documents/Events/2018/WSIS/Matos%20InnovWSIS-V1.pdf
|
| 395 |
+
Policy documents,For A Meaningful Artificial Intelligence,2018,France,https://www.jaist.ac.jp/~bao/AI/OtherAIstrategies/MissionVillani_Report_ENG-VF.pdf
|
| 396 |
+
Policy documents,Designing a Winning A.I. Strategy,2017,Saudi Arabia,https://www.kineticcs.com/wp-content/uploads/2017/11/Designing-A-Winning-AI-Strategy-_Kinetic-Consulting-Services.pdf
|
| 397 |
+
Policy documents,Nacionalni program spodbujanja razvoja in uporabe umetne inteligence v Republiki Sloveniji do leta 2025 (NpUI),2021,Slovenia,https://www.gov.si/assets/ministrstva/MJU/DID/NpUI-SI-2025.docx
|
| 398 |
+
Policy documents,Governance Guidelines for Implementation of AI Principles,2021,Japan,https://www.meti.go.jp/shingikai/mono_info_service/ai_shakai_jisso/pdf/20210709_9.pdf
|
| 399 |
+
Policy documents,Action plan for the digital transformation of Slovakia for 2019 – 2022,2019,Slovakia,https://www.mirri.gov.sk/wp-content/uploads/2019/10/AP-DT-English-Version-FINAL.pdf
|
| 400 |
+
Policy documents,Digital Economy Partnership Agreement,2020,New Zealand,https://www.mti.gov.sg/-/media/MTI/Microsites/DEAs/Digital-Economy-Partnership-Agreement/Digital-Economy-Partnership-Agreement.pdf
|
| 401 |
+
Policy documents,Concept for the Development of Artificial Intelligence in Bulgaria until 2030,2020,Bulgaria,https://www.mtitc.government.bg/sites/default/files/conceptforthedevelopmentofaiinbulgariauntil2030.pdf
|
| 402 |
+
Policy documents,The Dutch Digitalisation Strategy 2021,2021,Netherlands,https://www.nederlanddigitaal.nl/binaries/nederlanddigitaal-nl/documenten/publicaties/2021/06/22/the-dutch-digitalisation-strategy-2021-eng/210621-min-ezk-digitaliseringstrategie-en-v03.pdf
|
| 403 |
+
Policy documents,AIRAWAT- Establishing an AI Specific Cloud Computing Intrastructure for India,2020,India,https://www.niti.gov.in/sites/default/files/2020-01/AIRAWAT_Approach_Paper.pdf
|
| 404 |
+
Policy documents,American Artificial Intelligence Initiative: Year One Annual Report,2020,United States,https://www.nitrd.gov/nitrdgroups/images/c/c1/American-AI-Initiative-One-Year-Annual-Report.pdf
|
| 405 |
+
Policy documents,Recommendations for Leveraging Cloud Computing Resources for Federally Funded Artificial Intelligence Research and Development,2020,United States,https://www.nitrd.gov/pubs/Recommendations-Cloud-AI-RD-Nov2020.pdf
|
| 406 |
+
Policy documents,National Robotics Initiative 3.0: Innovations in Integration of Robotics (NRI-3.0),2021,United States,https://www.nsf.gov/pubs/2021/nsf21559/nsf21559.pdf
|
| 407 |
+
Policy documents,Proposte per una Strategia italiana per l'intelligenza artificiale,2020,Italy,https://www.mimit.gov.it/images/stories/documenti/Proposte_per_una_Strategia_italiana_AI.pdf
|
| 408 |
+
Policy documents,BRAZIL 2021 - National AI strategy,2021,Brazil,https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/transformacaodigital/arquivosinteligenciaartificial/ebia-portaria_mcti_4-979_2021_anexo1.pdf
|
| 409 |
+
Policy documents,MEXICO Consolidado Comentarios Consulta,2019,Mexico,https://www.gob.mx/cms/uploads/attachment/file/415644/Consolidado_Comentarios_Consulta_IA__1_.pdf
|
| 410 |
+
Policy documents,Resolution Directing Use of Compulsory Process Regarding Abuse of Intellectual Property,2021,United States,https://www.ftc.gov/system/files/attachments/press-releases/ftc-streamlines-consumer-protection-competition-investigations-eight-key-enforcement-areas-enable/omnibus_resolutions_p859900.pdf
|
| 411 |
+
Policy documents,Robustness and Explainability of Artificial Intelligence,2020,European Union,https://publications.jrc.ec.europa.eu/repository/bitstream/JRC119336/dpad_report.pdf
|
| 412 |
+
Policy documents,"AI in the UK: ready, willing and able",2018,United Kingdom,https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf
|
| 413 |
+
Policy documents,AI in the UK: No Room for Complacency,2020,United Kingdom,https://publications.parliament.uk/pa/ld5801/ldselect/ldliaison/196/196.pdf
|
| 414 |
+
Policy documents,Developing Standards for Artificial Intelligence,2019,Australia,https://publicsectornetwork.com/wp-content/uploads/2019/11/Artificial-Intelligence-Discussion-Paper-004.pdf
|
| 415 |
+
Policy documents,Resource Guide on Artificial Ingelligence Strategies,2021,United Nations,https://sdgs.un.org/sites/default/files/2021-06/Resource%20Guide%20on%20AI%20Strategies_June%202021.pdf
|
| 416 |
+
Policy documents,Draft 2019-2020 Federal Data Strategy Action Plan,2019,United States,https://strategy.data.gov/assets/docs/draft-2019-2020-federal-data-strategy-action-plan.pdf
|
| 417 |
+
Policy documents,Science & Technology Highlights,2017,United States,https://trumpwhitehouse.archives.gov/wp-content/uploads/2018/03/Administration-2017-ST-Highlights.pdf
|
| 418 |
+
Policy documents,Towards a vibrant European Network of AI excellence centres,2020,European Union,https://umai.uma.es/shared/Commission-Presentation-H2020.pdf
|
| 419 |
+
Policy documents,Policy for the Development of Artificial Intelligence in Poland from 2020,2020,Poland,https://wp.oecd.ai/app/uploads/2021/12/Poland_Policy_for_Artificial_Intelligence_Development_in_Poland_from_2020_2020.pdf
|
| 420 |
+
Policy documents,National approach to artificial intelligence,2018,Sweden,https://wp.oecd.ai/app/uploads/2021/12/Sweden_National_Approach_to_Artificial_Intelligence_2018.pdf
|
| 421 |
+
Policy documents,Key points for a Federal Government Strategy on Artificial Intelligence,2018,Germany,https://www.bmwk.de/Redaktion/EN/Downloads/E/key-points-for-federal-government-strategy-on-artificial-intelligence.pdf?__blob=publicationFile&v=1
|
| 422 |
+
Policy documents,Strengthening international cooperation on AI,2021,United States,https://www.brookings.edu/wp-content/uploads/2021/10/Strengthening-International-Cooperation-AI_Oct21.pdf
|
| 423 |
+
Policy documents,Australia`s AI ethics framework- A discussion Paper,2019,Australia,https://www.csiro.au/-/media/D61/Reports/Artificial-Intelligence-ethics-framework.pdf
|
| 424 |
+
Policy documents,Algorithm Assessment Report,2018,New Zealand,https://www.data.govt.nz/assets/Uploads/Algorithm-Assessment-Report-Oct-2018.pdf
|
| 425 |
+
Policy documents,Recommendations when using supervised machine learning,2018,Denmark,https://www.dfsa.dk/-/media/Tilsyn/Recommendations_when_using_supervised_ML-pdf.pdf
|
| 426 |
+
Policy documents,Opportunities of Artificial Intelligence,2020,European Union,https://www.europarl.europa.eu/RegData/etudes/STUD/2020/652713/IPOL_STU(2020)652713_EN.pdf
|
| 427 |
+
Policy documents,Liability for Artificial Intelligence and other emerging digital technologies,2019,European Union,https://www.europarl.europa.eu/meetdocs/2014_2019/plmrep/COMMITTEES/JURI/DV/2020/01-09/AI-report_EN.pdf
|
| 428 |
+
Policy documents,Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan,2021,United States,https://www.fda.gov/media/145022/download
|
| 429 |
+
Policy documents,Deciphering China’s AI Dream,2018,China,https://www.fhi.ox.ac.uk/wp-content/uploads/Deciphering_Chinas_AI-Dream.pdf
|
| 430 |
+
Policy documents,"Statement on Artificial Intelligence, Robotics and Autonomous Systems",2018,European Union,https://op.europa.eu/en/publication-detail/-/publication/6b1bc507-af70-11e8-99ee-01aa75ed71a1/language-en/format-PDF
|
| 431 |
+
Policy documents,Social Principles of Human-centric AI (Draft),2019,Japan,https://www8.cao.go.jp/cstp/stmain/aisocialprinciples.pdf
|
requirements.txt
ADDED
|
@@ -0,0 +1,6 @@
|
|
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|
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|
|
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|
|
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|
|
|
|
| 1 |
+
buster-doctalk==1.0.28
|
| 2 |
+
gradio==3.50.2
|
| 3 |
+
gunicorn==21.2.0
|
| 4 |
+
joblib>=1.3.2
|
| 5 |
+
pandas[output-formatting]>=2.1.3
|
| 6 |
+
pymongo>=4.6.1
|
src/app_utils.py
ADDED
|
@@ -0,0 +1,191 @@
|
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|
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|
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|
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|
|
|
|
|
|
|
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|
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|
|
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|
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|
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|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import logging
|
| 2 |
+
import os
|
| 3 |
+
import uuid
|
| 4 |
+
from datetime import datetime, timezone
|
| 5 |
+
from urllib.parse import quote_plus
|
| 6 |
+
|
| 7 |
+
import gradio as gr
|
| 8 |
+
import pandas as pd
|
| 9 |
+
import pymongo
|
| 10 |
+
from pymongo import MongoClient
|
| 11 |
+
|
| 12 |
+
from buster.completers import Completion, UserInputs
|
| 13 |
+
from buster.tokenizers import Tokenizer
|
| 14 |
+
|
| 15 |
+
logger = logging.getLogger(__name__)
|
| 16 |
+
logging.basicConfig(level=logging.INFO)
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
class WordTokenizer(Tokenizer):
|
| 20 |
+
"""Naive word-level tokenizer
|
| 21 |
+
|
| 22 |
+
The original tokenizer from openAI eats way too much Ram.
|
| 23 |
+
This is a naive word count tokenizer to be used instead."""
|
| 24 |
+
|
| 25 |
+
def __init__(self, *args, **kwargs):
|
| 26 |
+
super().__init__(*args, **kwargs)
|
| 27 |
+
|
| 28 |
+
def encode(self, string):
|
| 29 |
+
return string.split()
|
| 30 |
+
|
| 31 |
+
def decode(self, encoded):
|
| 32 |
+
return " ".join(encoded)
|
| 33 |
+
|
| 34 |
+
|
| 35 |
+
def get_logging_db_name(instance_type: str) -> str:
|
| 36 |
+
assert instance_type in ["dev", "prod", "local", "test"], "Invalid instance_type declared."
|
| 37 |
+
return f"ai4h-databank-{instance_type}"
|
| 38 |
+
|
| 39 |
+
|
| 40 |
+
def get_session_id() -> str:
|
| 41 |
+
"""Generate a uuid for each user."""
|
| 42 |
+
return str(uuid.uuid1())
|
| 43 |
+
|
| 44 |
+
|
| 45 |
+
def verify_required_env_vars(required_vars: list[str]):
|
| 46 |
+
unset_vars = [var for var in required_vars if os.getenv(var) is None]
|
| 47 |
+
if len(unset_vars) > 0:
|
| 48 |
+
logger.warning(f"Lisf of env. variables that weren't set: {unset_vars}")
|
| 49 |
+
else:
|
| 50 |
+
logger.info("All environment variables are set appropriately.")
|
| 51 |
+
|
| 52 |
+
|
| 53 |
+
def make_uri(username: str, password: str, cluster: str) -> str:
|
| 54 |
+
"""Create mongodb uri."""
|
| 55 |
+
uri = (
|
| 56 |
+
"mongodb+srv://"
|
| 57 |
+
+ quote_plus(username)
|
| 58 |
+
+ ":"
|
| 59 |
+
+ quote_plus(password)
|
| 60 |
+
+ "@"
|
| 61 |
+
+ cluster
|
| 62 |
+
+ "/?retryWrites=true&w=majority"
|
| 63 |
+
)
|
| 64 |
+
return uri
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
def init_db(mongo_uri: str, db_name: str) -> pymongo.database.Database:
|
| 68 |
+
"""
|
| 69 |
+
Initialize and return a connection to the specified MongoDB database.
|
| 70 |
+
|
| 71 |
+
Parameters:
|
| 72 |
+
- mongo_uri (str): The connection string for the MongoDB. This can be formed using `make_uri` function.
|
| 73 |
+
- db_name (str): The name of the MongoDB database to connect to.
|
| 74 |
+
|
| 75 |
+
Returns:
|
| 76 |
+
pymongo.database.Database: The connected database object.
|
| 77 |
+
|
| 78 |
+
Note:
|
| 79 |
+
If there's a problem with the connection, an exception will be logged and the program will terminate.
|
| 80 |
+
"""
|
| 81 |
+
|
| 82 |
+
try:
|
| 83 |
+
mongodb_client = MongoClient(mongo_uri)
|
| 84 |
+
# Ping the database to make sure authentication is good
|
| 85 |
+
mongodb_client.admin.command("ping")
|
| 86 |
+
database = mongodb_client[db_name]
|
| 87 |
+
logger.info("Succesfully connected to the MongoDB database")
|
| 88 |
+
return database
|
| 89 |
+
except Exception as e:
|
| 90 |
+
logger.exception("Something went wrong connecting to mongodb")
|
| 91 |
+
|
| 92 |
+
|
| 93 |
+
def get_utc_time() -> str:
|
| 94 |
+
return str(datetime.now(timezone.utc))
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
def check_auth(username: str, password: str) -> bool:
|
| 98 |
+
"""Check if authentication succeeds or not.
|
| 99 |
+
|
| 100 |
+
The authentication leverages the built-in gradio authentication. We use a shared password among users.
|
| 101 |
+
It is temporary for developing the PoC. Proper authentication needs to be implemented in the future.
|
| 102 |
+
We allow a valid username to be any username beginning with 'databank-', this will allow us to differentiate between users easily.
|
| 103 |
+
"""
|
| 104 |
+
|
| 105 |
+
# get auth information from env. vars, they need to be set
|
| 106 |
+
USERNAME = os.environ["AI4H_APP_USERNAME"]
|
| 107 |
+
PASSWORD = os.environ["AI4H_APP_PASSWORD"]
|
| 108 |
+
|
| 109 |
+
valid_user = username.startswith(USERNAME)
|
| 110 |
+
valid_password = password == PASSWORD
|
| 111 |
+
is_auth = valid_user and valid_password
|
| 112 |
+
logger.info(f"Log-in attempted by {username=}. {is_auth=}")
|
| 113 |
+
return is_auth
|
| 114 |
+
|
| 115 |
+
|
| 116 |
+
def format_sources(matched_documents: pd.DataFrame) -> list[str]:
|
| 117 |
+
formatted_sources = []
|
| 118 |
+
|
| 119 |
+
# We first group on Title of the document, so that 2 chunks from a same doc get lumped together
|
| 120 |
+
grouped_df = matched_documents.groupby("title")
|
| 121 |
+
|
| 122 |
+
# Here we just rank the titles by highest to lowest similarity score...
|
| 123 |
+
ranked_titles = (
|
| 124 |
+
grouped_df.apply(lambda x: x.similarity_to_answer.max()).sort_values(ascending=False).index.to_list()
|
| 125 |
+
)
|
| 126 |
+
|
| 127 |
+
for title in ranked_titles:
|
| 128 |
+
df = grouped_df.get_group(title)
|
| 129 |
+
|
| 130 |
+
# Adds a link break between sources from a same chunk
|
| 131 |
+
chunks = "<br><br>".join(["🔗 " + chunk for chunk in df.content.to_list()])
|
| 132 |
+
|
| 133 |
+
url = df.url.to_list()[0]
|
| 134 |
+
source = df.source.to_list()[0]
|
| 135 |
+
year = df.year.to_list()[0]
|
| 136 |
+
country = df.country.to_list()[0]
|
| 137 |
+
|
| 138 |
+
formatted_sources.append(
|
| 139 |
+
f"""
|
| 140 |
+
|
| 141 |
+
### Publication: [{title}]({url})
|
| 142 |
+
**Year of publication:** {year}
|
| 143 |
+
**Source:** {source}
|
| 144 |
+
**Country:** {country}
|
| 145 |
+
|
| 146 |
+
**Identified sections**:
|
| 147 |
+
{chunks}
|
| 148 |
+
"""
|
| 149 |
+
)
|
| 150 |
+
|
| 151 |
+
return formatted_sources
|
| 152 |
+
|
| 153 |
+
|
| 154 |
+
def pad_sources(sources: list[str], max_sources: int) -> list[str]:
|
| 155 |
+
"""Pad sources with empty strings to ensure that the number of sources is always max_sources."""
|
| 156 |
+
k = len(sources)
|
| 157 |
+
return sources + [""] * (max_sources - k)
|
| 158 |
+
|
| 159 |
+
|
| 160 |
+
def add_sources(completion, max_sources: int):
|
| 161 |
+
if not completion.question_relevant:
|
| 162 |
+
# Question was not relevant, don't bother doing anything else...
|
| 163 |
+
formatted_sources = [""]
|
| 164 |
+
else:
|
| 165 |
+
formatted_sources = format_sources(completion.matched_documents)
|
| 166 |
+
|
| 167 |
+
formatted_sources = pad_sources(formatted_sources, max_sources)
|
| 168 |
+
|
| 169 |
+
sources_textboxes = []
|
| 170 |
+
for source in formatted_sources:
|
| 171 |
+
visible = False if source == "" else True
|
| 172 |
+
t = gr.Markdown(source, latex_delimiters=[], elem_classes="source", visible=visible)
|
| 173 |
+
sources_textboxes.append(t)
|
| 174 |
+
return sources_textboxes
|
| 175 |
+
|
| 176 |
+
|
| 177 |
+
def debug_completion(user_input, reformulate_question):
|
| 178 |
+
"""Generate a debug completion."""
|
| 179 |
+
user_inputs = UserInputs(original_input=user_input)
|
| 180 |
+
if reformulate_question:
|
| 181 |
+
user_inputs.reformulated_input = "This is your reformulated question?"
|
| 182 |
+
|
| 183 |
+
completion = Completion(
|
| 184 |
+
user_inputs=user_inputs,
|
| 185 |
+
error=False,
|
| 186 |
+
matched_documents=[],
|
| 187 |
+
answer_generator="This is the answer you'd expect a User to see.",
|
| 188 |
+
question_relevant=True,
|
| 189 |
+
answer_relevant=True,
|
| 190 |
+
)
|
| 191 |
+
return completion
|
src/buster/assets/index.html
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
<html><head><meta content="text/html; charset=UTF-8" http-equiv="content-type"><style type="text/css">@import url(https://themes.googleusercontent.com/fonts/css?kit=wAPX1HepqA24RkYW1AuHYA);ol.lst-kix_list_1-3{list-style-type:none}ol.lst-kix_list_1-4{list-style-type:none}.lst-kix_list_2-6>li:before{content:"" counter(lst-ctn-kix_list_2-0,decimal) "." counter(lst-ctn-kix_list_2-1,decimal) "." counter(lst-ctn-kix_list_2-2,decimal) "." counter(lst-ctn-kix_list_2-3,decimal) "." counter(lst-ctn-kix_list_2-4,decimal) "." counter(lst-ctn-kix_list_2-5,decimal) "." counter(lst-ctn-kix_list_2-6,decimal) ". "}.lst-kix_list_2-7>li:before{content:"" counter(lst-ctn-kix_list_2-0,decimal) "." counter(lst-ctn-kix_list_2-1,decimal) "." counter(lst-ctn-kix_list_2-2,decimal) "." counter(lst-ctn-kix_list_2-3,decimal) "." counter(lst-ctn-kix_list_2-4,decimal) "." counter(lst-ctn-kix_list_2-5,decimal) "." counter(lst-ctn-kix_list_2-6,decimal) "." counter(lst-ctn-kix_list_2-7,decimal) ". 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You may not use AIR (i) to mislead any person to believe that the Output (as defined below) from AIR was solely human generated; (ii) in a way that would negatively affect the use of AIR by other users or its operation by Mila; (iii) to infringe on any third party’s rights; or (iv) in a manner that would otherwise reasonably constitute misuse or abuse. You also shall not use AIR or its Output in a manner that creates harm or biased results. Biased results include using the Output, or a decision, recommendation or prediction that is made by AIR in a way that adversely differentiates, directly or indirectly and without justification, in relation to an individual on one or more of the prohibited grounds of discrimination set out in Section 3 of the </span><span class="c9">Canadian Human Rights Act</span><span> (“</span><span class="c4">CHRA</span><span class="c8 c2">”), or on a combination of such prohibited grounds.</span></p><ol class="c0 lst-kix_list_2-0" start="2"><li class="c7 li-bullet-0"><h2 id="h.gjdgxs" style="display:inline"><span class="c5 c4 c2">Intended Purpose and Accuracy</span></h2></li></ol><p class="c10"><span class="c9">Output of this tool may not be accurate. </span><span>AIR is an experimental AI tool that uses generative artificial intelligence technologies to generate an output (“</span><span class="c4">Output</span><span>”) in relation to and based on any content you may provide to it (“</span><span class="c4">Input</span><span>”), in order to answer queries related to artificial intelligence legislation and governance materials (“</span><span class="c4">Intended Purpose</span><span>”). AIR answers these questions by using content retrieved from third-party sources (“</span><span class="c4">Third-Party Sources</span><span>”), the accuracy of which is not endorsed nor confirmed by Mila. AIR is not intended to provide information outside of its Intended Purpose, and is not intended to be used to provide legal advice. In any case, even when using AIR for its Intended Purpose, you understand that AIR relies on experimental and exploratory technologies and that Mila cannot attest that the Output shall be accurate, complete or valid, and may as such not meet your desired use including, without limitation, that it may be duplicative of content generated by AIR for other users or third-parties. </span><span class="c6 c4">You must use caution and discretion when relying on, publishing, distributing, or otherwise using any Output resulting from the use of AIR and a human should always review the Output before any subsequent use of the Output is contemplated, including compliance with legislation, regulations or any other legal duties</span><span class="c8 c2">. Furthermore, you understand that Mila does not endorse the Output and you agree to not construe the Output as an official statement by Mila. You understand that some Third-Party Sources may be outdated at the time the Output is generated or later become outdated and, as such, the Output may be outdated or become so over time.</span></p><ol class="c0 lst-kix_list_2-0" start="3"><li class="c7 li-bullet-0"><h2 style="display:inline"><span class="c5 c4 c2">Intellectual Property</span></h2></li></ol><p class="c10"><span class="c9">You remain the owner of your Input and you become the owner of the Output</span><span>. You grant us a non-exclusive, irrevocable, worldwide, royalty-free, sublicensable licence to the Input and to the Output, including without limitation to provide you access to AIR, to improve AIR or to use in relation with other services developed by Mila, its affiliates or partners (“</span><span class="c4">Mila Services</span><span class="c8 c2">”), which includes the right to use, process, copy, reproduce, modify, create derivative works of, excerpt, translate, publish, display, transmit, perform, and distribute the Input and Output as necessary to operate, enhance, improve, and further develop AIR and to provide the Mila Services. To the extent it is permitted under law, and subject to third-party rights and compliance with your obligations under the Terms, we assign to you all rights, title and interest in and to the Output that may be held by Mila and waive, on behalf of any individuals associated thereto, all moral rights existing in such works.</span></p><p class="c10"><span class="c8 c2">You are solely responsible for any Input entered into AIR, including the accuracy, quality, appropriateness, and legality thereof, and will ensure that such Input and use thereof in AIR does not (i) violate any applicable law; (ii) contain any Personal Information (as defined below), as further described in Section 4 (Privacy); (iii) violate these Terms; or (iv) infringe, violate, or misappropriate the rights of Mila or of any third party. You represent and warrant that you possess all rights necessary to provide the Input into AIR and to grant the licenses to Mila set forth herein.</span></p><p class="c10"><span class="c8 c2">Subject to the foregoing and to third-party rights, either Mila or its licensors remain the owners of any intellectual property rights included in or embedded in AIR or its underlying technologies, including all branding elements and trademarks pertaining thereto. Despite anything to the contrary in these Terms, no rights are granted to you in regard to the Third-Party Sources.</span></p><p class="c10"><span>If you provide to us feedback, comments or ideas with respect to AIR or any Mila Services (“</span><span class="c4">Feedback</span><span class="c8 c2">”), you grant us a perpetual, non-exclusive, irrevocable, worldwide, royalty-free, sublicensable and fully transferable licence to this Feedback for any purpose without further consideration owed to you.</span></p><ol class="c0 lst-kix_list_2-0" start="4"><li class="c7 li-bullet-0"><h2 style="display:inline"><span class="c5 c4 c2">Privacy</span></h2></li></ol><p class="c10"><span class="c9">No Personal Information. </span><span>AIR is not intended to process personal information or any information that would be subject to applicable privacy laws (“</span><span class="c4">Personal Information</span><span class="c8 c2">”). Therefore, you represent that your Input does not contain Personal Information, including names, addresses, phone numbers, email addresses, or birth dates. If, despite the foregoing, your Input does contain Personal Information, you represent that you have obtained in writing the necessary consents, authorizations and licences to allow us to process this Personal Information through AIR in compliance with the Terms.</span></p><p class="c10"><span>Any collection, use and sharing of Personal Information by Mila on you and your use of AIR will be subject to, and undertaken in compliance with, the terms of our Privacy Policy, available on our website: </span><span class="c6">https://mila.quebec/en/resource/privacy-policy/</span><span class="c8 c2">.</span></p><ol class="c0 lst-kix_list_2-0" start="5"><li class="c7 li-bullet-0"><h2 style="display:inline"><span class="c5 c4 c2">Limitation of Liability</span></h2></li></ol><p class="c10"><span class="c8 c2">To the maximum extent permitted by applicable law, and except for its gross fault, willful misconduct or breach of an essential obligation of the agreement, neither Mila nor its respective directors, officers, researchers, employees, agents, or service providers, shall be liable under these Terms and under any legal theory for any direct or indirect damages, including without limitation lost revenues, profits or loss of clients or expected clients, damages for business interruption or failure to realize expected savings, loss of use, loss of goodwill, loss of data and any other incidental commercial or financial losses of any kind, whether caused by tort (including negligence), breach of contract or otherwise, even if Mila was allegedly advised or had reason to know, but excluding claims based on fraud. Without limiting the generality of the foregoing, Mila specifically disclaims any liability for any business, legal or compliance decision, act or omission made by you in reliance of the Output.</span></p><p class="c10"><span class="c8 c2">To the full extent permitted by the law, and subject to the paragraph above, the aggregate liability of Mila, its employees, directors, officers, affiliates, researchers and partners under these Terms shall be limited to 50 CAD. You understand that AIR is an experimental and preliminary tool and is provided to you “as-is” without any warranties (express, implied or otherwise) and we disclaim all warranties including without limitation merchantability, fitness for a particular purpose (even for the Intended Purpose), satisfactory quality and non-infringement. AIR may be interrupted without prior notification and data (including the Input) may be lost or altered. Mila disclaims all warranties and representations (express, implied or otherwise) in regard to the security or confidentiality of any content, including without limitation content provided to, licensed to, or licensed by Mila under these Terms.</span></p><ol class="c0 lst-kix_list_2-0" start="6"><li class="c7 li-bullet-0"><h2 style="display:inline"><span class="c5 c4 c2">Termination</span></h2></li></ol><p class="c10"><span class="c8 c2">You may terminate these Terms at any time by ceasing to use AIR. We may terminate these Terms without prior notice at our discretion. Section 2 (Intended Purpose and Accuracy) and Section 5 (Limitation of Liability) shall survive the termination of these Terms.</span></p><ol class="c0 lst-kix_list_2-0" start="7"><li class="c7 li-bullet-0"><h2 style="display:inline"><span class="c4 c2 c5">General</span></h2></li></ol><p class="c1"><span class="c4">7.1 Severability and Waiver</span><span class="c8 c2">. If any portion of these Terms is determined by a court of competent jurisdiction to be invalid or unenforceable, then any such invalid or unenforceable portion shall be deemed deleted from these Terms; provided that any such invalidity or unenforceability shall not affect the remaining portions of these Terms, all of which shall remain in full force and effect. Failure or delay by Mila to exercise any right under these Terms does not constitute a waiver of these Terms. All waivers must be in writing and signed by Mila.</span></p><p class="c1"><span class="c4">7.2 Modifications</span><span>. These Terms may be amended from time to time. Such amended version will be published on the website hosting AIR </span><span class="c2">and</span><span> will be effective immediately. Your subsequent use of AIR means that you agree to these changes.</span></p><p class="c1"><span class="c4">7.3 Independent Parties</span><span>. Mila and you are independent parties and nothing in these Terms shall constitute any party as the employer, principal or partner of, or joint venture with, the other party. No party has the authority to assume or create any obligation or liability, either expressed or implied, on behalf of any other party.</span></p><p class="c1"><span class="c4">7.4 Use of Brand</span><span class="c2">. Nothing in these Terms grant you any rights to use the brand (including trademarks and brand names) of Mila or any of its </span><span>partners</span><span class="c8 c2">.</span></p><p class="c1"><span class="c4">7.5 Entire Agreement</span><span class="c2">. These Terms </span><span>constitute</span><span class="c8 c2"> the entire agreement between Mila and you with respect to the subject matter hereof and supersedes all other prior written or oral agreements hereto with respect to the subject matter hereof.</span></p><p class="c1"><span class="c4">7.6 Export Control</span><span>. The AIR platform, including any software, documentation, and any related technical data included with, or contained in, such platform, and any products utilizing any </span><span class="c4">such software</span><span>, documentation, or technical data (collectively, “</span><span class="c4">Regulated Products</span><span>”) may be subject to US export control laws and regulations, including the </span><span class="c9">Export Administration Regulations</span><span> and the </span><span class="c9">International Traffic in Arms Regulations</span><span class="c8 c2">. You shall not, and shall not permit any third parties to, directly or indirectly, export, reexport, or release any Regulated Products to any jurisdiction or country to which, or any party to whom, or for any use for which, the export, reexport, or release of any Regulated Products is prohibited by applicable federal or foreign law, regulation, or rule. You shall comply with all applicable federal and foreign laws, regulations, and rules, and complete all required undertakings (including obtaining any necessary export license or other governmental approval), prior to exporting, reexporting, or releasing any Regulated Products. You shall provide prior written notice of the need to comply with such laws, regulations, and rules to any person, firm, or entity which you have reason to believe is obtaining any such Regulated Products from you with the intent to export or reexport.</span></p><p class="c1"><span class="c4">7.7 Governing Law</span><span class="c2">. These Terms shall be construed in accordance with the laws of the Province of Quebec and the federal laws of Canada applicable </span><span>therein</span><span class="c8 c2">. Any dispute arising from or related to these Terms shall be submitted to a court of competent jurisdiction in the judicial district of Montreal, Quebec.</span></p><div><p class="c3"><span class="c2 c8"></span></p></div></body></html>
|
src/buster/buster_app.py
ADDED
|
@@ -0,0 +1,677 @@
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|
| 1 |
+
import copy
|
| 2 |
+
import logging
|
| 3 |
+
from typing import Optional, Union
|
| 4 |
+
|
| 5 |
+
import gradio as gr
|
| 6 |
+
import pandas as pd
|
| 7 |
+
|
| 8 |
+
import src.cfg as cfg
|
| 9 |
+
from buster.completers import Completion
|
| 10 |
+
from src.app_utils import add_sources, get_session_id, get_utc_time
|
| 11 |
+
from src.cfg import setup_buster
|
| 12 |
+
from src.feedback import FeedbackForm, Interaction
|
| 13 |
+
|
| 14 |
+
logger = logging.getLogger(__name__)
|
| 15 |
+
logging.basicConfig(level=logging.INFO)
|
| 16 |
+
|
| 17 |
+
# Typehint for chatbot history
|
| 18 |
+
ChatHistory = list[list[Optional[str], Optional[str]]]
|
| 19 |
+
|
| 20 |
+
app_name = cfg.app_name
|
| 21 |
+
example_questions = cfg.example_questions
|
| 22 |
+
disclaimer = cfg.disclaimer
|
| 23 |
+
mongo_db = cfg.mongo_db
|
| 24 |
+
buster_cfg = copy.deepcopy(cfg.buster_cfg)
|
| 25 |
+
buster = setup_buster(buster_cfg=buster_cfg)
|
| 26 |
+
max_sources = cfg.max_sources
|
| 27 |
+
data_dir = cfg.data_dir
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
# link to the terms and conditions to be rendered in markdown blocks
|
| 31 |
+
path_to_tncs = "file=src/buster/assets/index.html"
|
| 32 |
+
md_link_to_tncs = f"[terms and conditions]({path_to_tncs})"
|
| 33 |
+
|
| 34 |
+
# get documents metadata
|
| 35 |
+
documents_metadata_file = str(data_dir / "documents_metadata.csv")
|
| 36 |
+
documents_metadata = pd.read_csv(documents_metadata_file)
|
| 37 |
+
|
| 38 |
+
css = """
|
| 39 |
+
.source {
|
| 40 |
+
max-height: 250px; /* Set the maximum height for the textboxes */
|
| 41 |
+
overflow: auto; /* Enable scrollbars when content exceeds dimensions */
|
| 42 |
+
outline: 1px solid gray; /* Add a gray outline */
|
| 43 |
+
border-radius: 5px; /* Add rounded corners to the outline */
|
| 44 |
+
}
|
| 45 |
+
"""
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
def add_disclaimer(completion: Completion, chat_history: ChatHistory, disclaimer: str = disclaimer):
|
| 49 |
+
"""Add a disclaimer response if the answer was relevant."""
|
| 50 |
+
if completion.question_relevant:
|
| 51 |
+
chat_history.append([None, disclaimer])
|
| 52 |
+
return chat_history
|
| 53 |
+
|
| 54 |
+
|
| 55 |
+
def hide_about_panel(accept_checkbox):
|
| 56 |
+
# Stay open while not accepted
|
| 57 |
+
open = not bool(accept_checkbox)
|
| 58 |
+
return {about_panel: gr.update(open=open)}
|
| 59 |
+
|
| 60 |
+
|
| 61 |
+
def set_relevant_sources_selection(num_sources: int):
|
| 62 |
+
relevant_sources_selection = gr.CheckboxGroup(
|
| 63 |
+
choices=[f"Source {i+1}" for i in range(num_sources)],
|
| 64 |
+
label="Check all relevant sources (if any)",
|
| 65 |
+
)
|
| 66 |
+
return relevant_sources_selection
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
def setup_feedback_form(num_sources: int):
|
| 70 |
+
# Feedback
|
| 71 |
+
feedback_elems = {}
|
| 72 |
+
with gr.Box():
|
| 73 |
+
with gr.Row():
|
| 74 |
+
with gr.Box():
|
| 75 |
+
with gr.Column():
|
| 76 |
+
gr.Markdown(
|
| 77 |
+
f""" ## We would love your feedback!
|
| 78 |
+
Please submit feedback for each question asked.
|
| 79 |
+
|
| 80 |
+
Your feedback is anonymous and will help us make the tool as useful as possible for the community!
|
| 81 |
+
"""
|
| 82 |
+
)
|
| 83 |
+
with gr.Row():
|
| 84 |
+
overall_experience = gr.Radio(
|
| 85 |
+
choices=["👍", "👎"], label=f"Did {app_name} help answer your question?"
|
| 86 |
+
)
|
| 87 |
+
|
| 88 |
+
# Currently, we show all feedback, but also support having a small portion of it display at first
|
| 89 |
+
show_additional_feedback = gr.Group(visible=True)
|
| 90 |
+
with show_additional_feedback:
|
| 91 |
+
with gr.Column():
|
| 92 |
+
clear_answer = gr.Radio(
|
| 93 |
+
choices=["👍", "👎"], label="Was the generated answer clear and understandable?"
|
| 94 |
+
)
|
| 95 |
+
accurate_answer = gr.Radio(choices=["👍", "👎"], label="Was the generated answer accurate?")
|
| 96 |
+
relevant_sources = gr.Radio(
|
| 97 |
+
choices=["👍", "👎"],
|
| 98 |
+
label="Were the retrieved sources generally relevant to your query?",
|
| 99 |
+
)
|
| 100 |
+
relevant_sources_selection = set_relevant_sources_selection(num_sources=num_sources)
|
| 101 |
+
relevant_sources_order = gr.Radio(
|
| 102 |
+
choices=["👍", "👎"],
|
| 103 |
+
label="Were the sources ranked appropriately, in order of relevance?",
|
| 104 |
+
)
|
| 105 |
+
|
| 106 |
+
extra_info = gr.Textbox(
|
| 107 |
+
label="Any other comments?",
|
| 108 |
+
lines=3,
|
| 109 |
+
placeholder="Please enter other feedback for improvement here...",
|
| 110 |
+
)
|
| 111 |
+
|
| 112 |
+
expertise = gr.Radio(
|
| 113 |
+
choices=["Beginner", "Intermediate", "Expert"],
|
| 114 |
+
label="How would you rate your knowledge of AI policy",
|
| 115 |
+
interactive=True,
|
| 116 |
+
)
|
| 117 |
+
|
| 118 |
+
submit_feedback_btn = gr.Button("Submit feedback", variant="primary", interactive=True)
|
| 119 |
+
with gr.Column(visible=False) as submitted_message:
|
| 120 |
+
gr.Markdown(
|
| 121 |
+
"Feedback recorded, thank you 📝! You can now ask a new question in the search bar."
|
| 122 |
+
)
|
| 123 |
+
|
| 124 |
+
# fmt: off
|
| 125 |
+
submit_feedback_btn.click(
|
| 126 |
+
toggle_visibility,
|
| 127 |
+
inputs=gr.State(False),
|
| 128 |
+
outputs=submitted_message,
|
| 129 |
+
).then(
|
| 130 |
+
submit_feedback,
|
| 131 |
+
inputs=[
|
| 132 |
+
overall_experience,
|
| 133 |
+
clear_answer,
|
| 134 |
+
accurate_answer,
|
| 135 |
+
relevant_sources,
|
| 136 |
+
relevant_sources_order,
|
| 137 |
+
relevant_sources_selection,
|
| 138 |
+
expertise,
|
| 139 |
+
extra_info,
|
| 140 |
+
last_completion,
|
| 141 |
+
session_id,
|
| 142 |
+
],
|
| 143 |
+
).success(
|
| 144 |
+
toggle_visibility,
|
| 145 |
+
inputs=gr.State(True),
|
| 146 |
+
outputs=submitted_message,
|
| 147 |
+
).success(
|
| 148 |
+
toggle_interactivity,
|
| 149 |
+
inputs=gr.State(False),
|
| 150 |
+
outputs=submit_feedback_btn,
|
| 151 |
+
)
|
| 152 |
+
|
| 153 |
+
# fmt: on
|
| 154 |
+
feedback_elems = {
|
| 155 |
+
"overall_experience": overall_experience,
|
| 156 |
+
"clear_answer": clear_answer,
|
| 157 |
+
"accurate_answer": accurate_answer,
|
| 158 |
+
"relevant_sources": relevant_sources,
|
| 159 |
+
"relevant_sources_selection": relevant_sources_selection,
|
| 160 |
+
"relevant_sources_order": relevant_sources_order,
|
| 161 |
+
"submit_feedback_btn": submit_feedback_btn,
|
| 162 |
+
"submitted_message": submitted_message,
|
| 163 |
+
"show_additional_feedback": show_additional_feedback,
|
| 164 |
+
"expertise": expertise,
|
| 165 |
+
"extra_info": extra_info,
|
| 166 |
+
}
|
| 167 |
+
|
| 168 |
+
return feedback_elems
|
| 169 |
+
|
| 170 |
+
|
| 171 |
+
def to_md_link(title: str, link: str) -> str:
|
| 172 |
+
"""Converts a title and link to markown link format"""
|
| 173 |
+
return f"[{title}]({link})"
|
| 174 |
+
|
| 175 |
+
|
| 176 |
+
def get_metadata_markdown(df) -> str:
|
| 177 |
+
"""Converts the content from a dataframe to a markdown table string format."""
|
| 178 |
+
metadata = []
|
| 179 |
+
|
| 180 |
+
# Order articles by year, with latest first
|
| 181 |
+
df = df.sort_values(["Country", "Year"], ascending=True)
|
| 182 |
+
|
| 183 |
+
for _, item in df.iterrows():
|
| 184 |
+
# source = item["Source"]
|
| 185 |
+
link = item["Link"]
|
| 186 |
+
title = item["Title"]
|
| 187 |
+
year = item["Year"]
|
| 188 |
+
country = item["Country"]
|
| 189 |
+
|
| 190 |
+
metadata.append(f"{year} | {country} | {to_md_link(title, link)} ")
|
| 191 |
+
metadata_str = "\n".join(metadata)
|
| 192 |
+
|
| 193 |
+
markdown_text = f"""
|
| 194 |
+
| Year | Country | Report |
|
| 195 |
+
| --- | --- | --- |
|
| 196 |
+
{metadata_str}
|
| 197 |
+
"""
|
| 198 |
+
return markdown_text
|
| 199 |
+
|
| 200 |
+
|
| 201 |
+
def add_user_question(user_question: str, chat_history: Optional[ChatHistory] = None) -> ChatHistory:
|
| 202 |
+
"""Adds a user's question to the chat history.
|
| 203 |
+
|
| 204 |
+
If no history is provided, the first element of the history will be the user conversation.
|
| 205 |
+
"""
|
| 206 |
+
if chat_history is None:
|
| 207 |
+
chat_history = []
|
| 208 |
+
chat_history.append([user_question, None])
|
| 209 |
+
return chat_history
|
| 210 |
+
|
| 211 |
+
|
| 212 |
+
def chat(chat_history: ChatHistory, reformulate_question: bool, top_k: Optional[int] = None):
|
| 213 |
+
"""Answer a user's question using retrieval augmented generation."""
|
| 214 |
+
|
| 215 |
+
# Make sure top k is an int between 1 and 15
|
| 216 |
+
top_k = int(top_k)
|
| 217 |
+
top_k = max(top_k, 1)
|
| 218 |
+
top_k = min(top_k, max_sources)
|
| 219 |
+
|
| 220 |
+
# We assume that the question is the user's last interaction
|
| 221 |
+
user_input = chat_history[-1][0]
|
| 222 |
+
|
| 223 |
+
completion = buster.process_input(user_input, reformulate_question=reformulate_question, top_k=top_k)
|
| 224 |
+
|
| 225 |
+
if completion.question_relevant and not completion.error:
|
| 226 |
+
if reformulate_question and user_input not in cfg.example_questions:
|
| 227 |
+
assert completion.user_inputs.reformulated_input is not None
|
| 228 |
+
|
| 229 |
+
chat_history.append(
|
| 230 |
+
[
|
| 231 |
+
None,
|
| 232 |
+
f"{cfg.message_before_reformulation}{completion.user_inputs.reformulated_input}{cfg.message_after_reformulation}",
|
| 233 |
+
]
|
| 234 |
+
)
|
| 235 |
+
chat_history.append([None, None])
|
| 236 |
+
|
| 237 |
+
# Stream tokens one at a time
|
| 238 |
+
chat_history[-1][1] = ""
|
| 239 |
+
for token in completion.answer_generator:
|
| 240 |
+
chat_history[-1][1] += token
|
| 241 |
+
|
| 242 |
+
yield chat_history, completion
|
| 243 |
+
|
| 244 |
+
|
| 245 |
+
def log_completion(
|
| 246 |
+
completion: Union[Completion, list[Completion]],
|
| 247 |
+
collection: str,
|
| 248 |
+
session_id: str,
|
| 249 |
+
request: gr.Request,
|
| 250 |
+
instance_type: Optional[str] = cfg.INSTANCE_TYPE,
|
| 251 |
+
instance_name: Optional[str] = cfg.INSTANCE_NAME,
|
| 252 |
+
mongo_db=cfg.mongo_db,
|
| 253 |
+
):
|
| 254 |
+
"""
|
| 255 |
+
Log user completions in a specified collection for analytics.
|
| 256 |
+
|
| 257 |
+
Parameters:
|
| 258 |
+
completion (Union[Completion, list[Completion]]): A single completion or a list of completions
|
| 259 |
+
to log. Completions can be instances of the Completion class.
|
| 260 |
+
collection (str): The name of the MongoDB collection where the interactions will be stored.
|
| 261 |
+
session_id (str): A unique identifier for the current session. In gradio this is reset every time a page is refreshed.
|
| 262 |
+
request (gr.Request): The gradio request object containing request metadata.
|
| 263 |
+
instance_type (str, optional): The type of instance where the completion took place.
|
| 264 |
+
Defaults to cfg.INSTANCE_TYPE.
|
| 265 |
+
instance_name (str, optional): The name of the instance where the completion took place.
|
| 266 |
+
Defaults to cfg.INSTANCE_NAME.
|
| 267 |
+
"""
|
| 268 |
+
|
| 269 |
+
# TODO: add UID for each page visitor instead of username
|
| 270 |
+
|
| 271 |
+
# make sure it's always a list
|
| 272 |
+
if isinstance(completion, Completion):
|
| 273 |
+
user_completions = [completion]
|
| 274 |
+
else:
|
| 275 |
+
user_completions = completion
|
| 276 |
+
|
| 277 |
+
interaction = Interaction(
|
| 278 |
+
user_completions=user_completions,
|
| 279 |
+
time=get_utc_time(),
|
| 280 |
+
username=request.username,
|
| 281 |
+
session_id=session_id,
|
| 282 |
+
instance_name=instance_name,
|
| 283 |
+
instance_type=instance_type,
|
| 284 |
+
data_version=cfg.MONGO_DATABASE_DATA,
|
| 285 |
+
)
|
| 286 |
+
interaction.send(mongo_db, collection=collection)
|
| 287 |
+
|
| 288 |
+
|
| 289 |
+
def submit_feedback(
|
| 290 |
+
overall_experience: str,
|
| 291 |
+
clear_answer: str,
|
| 292 |
+
accuracte_answer: str,
|
| 293 |
+
relevant_sources: str,
|
| 294 |
+
relevant_sources_order: list[str],
|
| 295 |
+
relevant_sources_selection: str,
|
| 296 |
+
expertise: list[str],
|
| 297 |
+
extra_info: str,
|
| 298 |
+
completion: Union[Completion, list[Completion]],
|
| 299 |
+
session_id: str,
|
| 300 |
+
request: gr.Request,
|
| 301 |
+
instance_type: Optional[str] = cfg.INSTANCE_TYPE,
|
| 302 |
+
instance_name: Optional[str] = cfg.INSTANCE_NAME,
|
| 303 |
+
):
|
| 304 |
+
feedback_form = FeedbackForm(
|
| 305 |
+
overall_experience=overall_experience,
|
| 306 |
+
clear_answer=clear_answer,
|
| 307 |
+
accurate_answer=accuracte_answer,
|
| 308 |
+
relevant_sources=relevant_sources,
|
| 309 |
+
relevant_sources_order=relevant_sources_order,
|
| 310 |
+
relevant_sources_selection=relevant_sources_selection,
|
| 311 |
+
expertise=expertise,
|
| 312 |
+
extra_info=extra_info,
|
| 313 |
+
)
|
| 314 |
+
|
| 315 |
+
# make sure it's always a list
|
| 316 |
+
if isinstance(completion, Completion):
|
| 317 |
+
user_completions = [completion]
|
| 318 |
+
else:
|
| 319 |
+
user_completions = completion
|
| 320 |
+
|
| 321 |
+
feedback = Interaction(
|
| 322 |
+
user_completions=user_completions,
|
| 323 |
+
form=feedback_form,
|
| 324 |
+
time=get_utc_time(),
|
| 325 |
+
username=request.username,
|
| 326 |
+
session_id=session_id,
|
| 327 |
+
instance_name=instance_name,
|
| 328 |
+
instance_type=instance_type,
|
| 329 |
+
)
|
| 330 |
+
feedback.send(mongo_db, collection=cfg.MONGO_COLLECTION_FEEDBACK)
|
| 331 |
+
|
| 332 |
+
|
| 333 |
+
def toggle_visibility(visible: bool):
|
| 334 |
+
"""Toggles the visibility of the gradio element."""
|
| 335 |
+
return gr.update(visible=visible)
|
| 336 |
+
|
| 337 |
+
|
| 338 |
+
def toggle_interactivity(interactive: bool):
|
| 339 |
+
"""Toggles the visibility of the gradio element."""
|
| 340 |
+
return gr.update(interactive=interactive)
|
| 341 |
+
|
| 342 |
+
|
| 343 |
+
def clear_user_input():
|
| 344 |
+
"""Clears the contents of the user_input box."""
|
| 345 |
+
return gr.update(value="")
|
| 346 |
+
|
| 347 |
+
|
| 348 |
+
def clear_sources():
|
| 349 |
+
"""Clears all the documents in the tabs"""
|
| 350 |
+
return ["" for _ in range(max_sources)]
|
| 351 |
+
|
| 352 |
+
|
| 353 |
+
def clear_feedback_form():
|
| 354 |
+
"""Clears the contents of the feedback form."""
|
| 355 |
+
return {
|
| 356 |
+
feedback_elems["overall_experience"]: gr.update(value=None),
|
| 357 |
+
feedback_elems["clear_answer"]: gr.update(value=None),
|
| 358 |
+
feedback_elems["accurate_answer"]: gr.update(value=None),
|
| 359 |
+
feedback_elems["relevant_sources"]: gr.update(value=None),
|
| 360 |
+
feedback_elems["relevant_sources_selection"]: gr.update(value=None),
|
| 361 |
+
feedback_elems["relevant_sources_order"]: gr.update(value=None),
|
| 362 |
+
feedback_elems["expertise"]: gr.update(value=None),
|
| 363 |
+
feedback_elems["extra_info"]: gr.update(value=None),
|
| 364 |
+
}
|
| 365 |
+
|
| 366 |
+
|
| 367 |
+
def reveal_app(choice: gr.SelectData):
|
| 368 |
+
return (
|
| 369 |
+
gr.Group.update(visible=False),
|
| 370 |
+
gr.update(interactive=True, placeholder="Ask your AI policy question here…"),
|
| 371 |
+
gr.update(interactive=True),
|
| 372 |
+
)
|
| 373 |
+
|
| 374 |
+
|
| 375 |
+
def display_sources():
|
| 376 |
+
with gr.Column():
|
| 377 |
+
gr.Markdown(
|
| 378 |
+
"""## Relevant sources
|
| 379 |
+
All retrieved documents will be listed here in order of importance.
|
| 380 |
+
"""
|
| 381 |
+
)
|
| 382 |
+
sources_textboxes = []
|
| 383 |
+
for i in range(max_sources):
|
| 384 |
+
t = gr.Markdown(latex_delimiters=[], elem_classes="source", visible=False)
|
| 385 |
+
sources_textboxes.append(t)
|
| 386 |
+
return sources_textboxes
|
| 387 |
+
|
| 388 |
+
|
| 389 |
+
def setup_about_panel():
|
| 390 |
+
with gr.Accordion(label=f"About {app_name}", open=False) as about_panel:
|
| 391 |
+
with gr.Row(variant="panel"):
|
| 392 |
+
with gr.Box():
|
| 393 |
+
gr.Markdown(
|
| 394 |
+
f"""
|
| 395 |
+
|
| 396 |
+
## Welcome
|
| 397 |
+
Artificial intelligence is a field that's developing fast! In response, policy makers from around the world are creating guidelines, rules and regulations to keep up.
|
| 398 |
+
|
| 399 |
+
Finding accurate and up-to-date information about regulatory changes can be difficult but crucial to share best practices, ensure interoperability and promote adherence to local laws and regulations. That's why we've created {app_name}.
|
| 400 |
+
|
| 401 |
+
{app_name} is a Q&A search engine designed to provide relevant and high quality information about AI policies from around the world. Using this tool, your AI policy questions will be answered, accompanied by relevant analyses by the OECD's AI Observatory!
|
| 402 |
+
|
| 403 |
+
## How it works (and doesn't)
|
| 404 |
+
|
| 405 |
+
{app_name} uses Large Language Models (AI algorithms that work with text) to pinpoint sections of policy documents that are relevant to your question. Rather than presenting you with the specific policy section verbatim, {app_name} has been designed to summarize the information in a digestible format, so that the response you receive more naturally fits with the question you've posed.
|
| 406 |
+
|
| 407 |
+
It's helpful to keep in mind that {app_name} is entirely restricted to our database (see “Available Sources” below). These sources are from the [OECD.AI](http://oecd.ai/) Database (containing national AI policies) and AI-related reports from the OECD iLibrary. If the answer to your question is not contained in these policy documents, the model won't be able to respond.
|
| 408 |
+
|
| 409 |
+
Since we restrict the model to information found in the documentation, it has a hard time with questions that require more generalized knowledge. Therefore, if you ask the model for information about AI policies in Asia, the model won't necessarily show you Japanese policy documentation. To overcome this limitation, it's best to be as specific as possible in your question, referencing the particular country you're looking for information on.
|
| 410 |
+
|
| 411 |
+
For more information about the tool's strengths and limitations, please see our website [here](https://mila.quebec/en/project/sai/).
|
| 412 |
+
"""
|
| 413 |
+
)
|
| 414 |
+
|
| 415 |
+
with gr.Box():
|
| 416 |
+
gr.Markdown(
|
| 417 |
+
f"""
|
| 418 |
+
## Risks
|
| 419 |
+
|
| 420 |
+
We have done our best to make sure that the AI algorithms are __only__ taking information from what is available in the OECD AI Observatory's Database; but, of course, Large Language Models (LLMs) are prone to fabrication. This means LLMs can make things up and present this made up information as if it were real, making it seem as if the information was found in a policy document. We therefore advise you to check the sources provided by the model to validate that the answer is in fact true. If you'd like to know exactly which documents the model can reference in its response, please see below.
|
| 421 |
+
|
| 422 |
+
|
| 423 |
+
## Recommended usage
|
| 424 |
+
|
| 425 |
+
{app_name} can only answer specific types of questions, for example:
|
| 426 |
+
|
| 427 |
+
* Questions about policy documents that are currently in the OECD AI Observatory's database
|
| 428 |
+
* Questions that are posed in English and target English language documents;
|
| 429 |
+
* Questions for which the answer can be found in the text (i.e. the thinking has already been done by the author) these AI models are not able to write their own research report combining information across policy documents and analyzing them itself).
|
| 430 |
+
|
| 431 |
+
If your question is outside the scope of the recommended use, the model has been instructed not to answer.
|
| 432 |
+
|
| 433 |
+
We are looking to create a tool that is as inclusive as possible.
|
| 434 |
+
While currently the tool only works with English language questions and documents we will continue assessing {app_name}'s capacity to perform as intended for users with different levels of fluency in English and plan to expand the functionality to ensure accessibility and impact across countries and user groups.
|
| 435 |
+
"""
|
| 436 |
+
)
|
| 437 |
+
|
| 438 |
+
return about_panel
|
| 439 |
+
|
| 440 |
+
|
| 441 |
+
def setup_terms_and_conditions():
|
| 442 |
+
with gr.Group(visible=True) as accept_terms_group:
|
| 443 |
+
with gr.Column(scale=1):
|
| 444 |
+
gr.Markdown(
|
| 445 |
+
f"""
|
| 446 |
+
By using this tool you agree to our {md_link_to_tncs}
|
| 447 |
+
""",
|
| 448 |
+
)
|
| 449 |
+
accept_checkbox = gr.Checkbox(value=0, label="I accept", interactive=True, container=False, scale=1)
|
| 450 |
+
return accept_terms_group, accept_checkbox
|
| 451 |
+
|
| 452 |
+
|
| 453 |
+
def setup_additional_sources():
|
| 454 |
+
# Display additional sources
|
| 455 |
+
with gr.Box():
|
| 456 |
+
gr.Markdown(f"")
|
| 457 |
+
|
| 458 |
+
gr.Markdown(
|
| 459 |
+
f"""## 📚 Available sources
|
| 460 |
+
{app_name} has access to dozens of AI policy documents from various sources.
|
| 461 |
+
Below we list all of the sources that {app_name} has access to.
|
| 462 |
+
"""
|
| 463 |
+
)
|
| 464 |
+
with gr.Accordion(open=False, label="Click to list all available sources 📚"):
|
| 465 |
+
with gr.Column():
|
| 466 |
+
# Display the sources using a dataframe table
|
| 467 |
+
documents_metadata["Report"] = documents_metadata.apply(
|
| 468 |
+
lambda row: to_md_link(row["Title"], row["Link"]), axis=1
|
| 469 |
+
)
|
| 470 |
+
sub_df = documents_metadata[["Country", "Year", "Report"]]
|
| 471 |
+
gr.DataFrame(
|
| 472 |
+
sub_df, headers=list(sub_df.columns), interactive=False, datatype=["number", "str", "markdown"]
|
| 473 |
+
)
|
| 474 |
+
|
| 475 |
+
# Uncomment to display the sources instead as a simple markdown table
|
| 476 |
+
# gr.Markdown(get_metadata_markdown(documents_metadata))
|
| 477 |
+
|
| 478 |
+
|
| 479 |
+
def raise_flagging_message():
|
| 480 |
+
"""Raises a red banner indicating that the content has been flagged."""
|
| 481 |
+
gr.Info(
|
| 482 |
+
"Thank you for flagging the content. Our moderation team will look closely at these samples. We appologize for any harm this might have caused you."
|
| 483 |
+
)
|
| 484 |
+
|
| 485 |
+
|
| 486 |
+
def setup_flag_button():
|
| 487 |
+
"""Sets up a flag button with some accompanying text explaining why we have it."""
|
| 488 |
+
with gr.Column(variant="compact"):
|
| 489 |
+
with gr.Box():
|
| 490 |
+
gr.Markdown(
|
| 491 |
+
"""# Report bugs and harmful content
|
| 492 |
+
While we took many steps to ensure the tool is safe, we still rely on third parties for some of the model's capabilities. Please let us know if any harmful content shows up by clicking the button below and sending screenshots/concerns to mila.databank@gmail.com"""
|
| 493 |
+
)
|
| 494 |
+
flag_button = gr.Button(value="Flag content 🚩")
|
| 495 |
+
return flag_button
|
| 496 |
+
|
| 497 |
+
|
| 498 |
+
def setup_user_settings(
|
| 499 |
+
reformulate_question: bool, visible: bool, num_sources: int, max_sources: int = 15, min_sources: int = 1
|
| 500 |
+
) -> dict:
|
| 501 |
+
"""Set up user interface elements for frontend user settings in a web application.
|
| 502 |
+
|
| 503 |
+
This function creates an accordion containing a slider and a checkbox to configure
|
| 504 |
+
the number of sources and the option to reformulate questions, respectively.
|
| 505 |
+
The values set here will also be the values used by default by the app.
|
| 506 |
+
|
| 507 |
+
Args:
|
| 508 |
+
reformulate_question (bool): Initial state of the checkbox for reformulating questions.
|
| 509 |
+
visible (bool, optional): Visibility state of the settings tab. Defaults to False.
|
| 510 |
+
num_sources (int): Initial value for the number of sources slider. Defaults to 3.
|
| 511 |
+
max_sources (int, optional): Maximum limit for the number of sources slider. Defaults to 15.
|
| 512 |
+
min_sources (int, optional): Minimum limit for the number of sources slider. Defaults to 1.
|
| 513 |
+
|
| 514 |
+
Returns:
|
| 515 |
+
dict: A dictionary containing the UI elements for the reformulate question checkbox and the sources slider.
|
| 516 |
+
"""
|
| 517 |
+
|
| 518 |
+
with gr.Accordion(label=f"Settings ⚙️", open=False, visible=visible):
|
| 519 |
+
top_k_slider = gr.Slider(
|
| 520 |
+
minimum=min_sources,
|
| 521 |
+
maximum=max_sources,
|
| 522 |
+
interactive=True,
|
| 523 |
+
value=num_sources,
|
| 524 |
+
step=1,
|
| 525 |
+
label="Number of sources",
|
| 526 |
+
info="Number of documents to pass to the language model during its retrieval.",
|
| 527 |
+
)
|
| 528 |
+
|
| 529 |
+
reformulate_question_cbox = gr.Checkbox(
|
| 530 |
+
value=reformulate_question,
|
| 531 |
+
label="Reformulate Question (Beta)",
|
| 532 |
+
info="Reformulates a user's question to enhance source retrieval.",
|
| 533 |
+
)
|
| 534 |
+
|
| 535 |
+
settings_elems = {
|
| 536 |
+
"reformulate_question_cbox": reformulate_question_cbox,
|
| 537 |
+
"top_k_slider": top_k_slider,
|
| 538 |
+
}
|
| 539 |
+
return settings_elems
|
| 540 |
+
|
| 541 |
+
|
| 542 |
+
buster_app = gr.Blocks(css=css)
|
| 543 |
+
with buster_app:
|
| 544 |
+
# State variables are client-side and are reset every time a client refreshes the page
|
| 545 |
+
# Store the users' last completion here
|
| 546 |
+
last_completion = gr.State()
|
| 547 |
+
|
| 548 |
+
# A unique identifier that resets every time a page is refreshed
|
| 549 |
+
session_id = gr.State(get_session_id)
|
| 550 |
+
|
| 551 |
+
gr.Markdown(f"<h1><center>AIR: Q&A tool for AI Policy</center></h1>")
|
| 552 |
+
|
| 553 |
+
about_panel = setup_about_panel()
|
| 554 |
+
|
| 555 |
+
with gr.Row():
|
| 556 |
+
with gr.Column(scale=2, variant="panel"):
|
| 557 |
+
gr.Markdown(
|
| 558 |
+
f"""
|
| 559 |
+
Ask {app_name} your AI policy questions! Keep in mind this tool is a demo and can sometimes provide inaccurate information. Always verify the integrity of the information using the provided sources.
|
| 560 |
+
Since this tool is still in its early stages of development, please only engage with it as a demo.
|
| 561 |
+
"""
|
| 562 |
+
)
|
| 563 |
+
accept_terms_group, accept_terms_checkbox = setup_terms_and_conditions()
|
| 564 |
+
with gr.Row():
|
| 565 |
+
with gr.Column(scale=20):
|
| 566 |
+
user_input = gr.Textbox(
|
| 567 |
+
label="",
|
| 568 |
+
placeholder="⚠️ Accept the terms and conditions to use the app",
|
| 569 |
+
lines=1,
|
| 570 |
+
interactive=False,
|
| 571 |
+
)
|
| 572 |
+
submit = gr.Button(value="Ask", variant="primary", size="lg", interactive=False)
|
| 573 |
+
|
| 574 |
+
gr.Examples(
|
| 575 |
+
examples=example_questions,
|
| 576 |
+
inputs=user_input,
|
| 577 |
+
label=f"Sample questions to ask {app_name}",
|
| 578 |
+
)
|
| 579 |
+
|
| 580 |
+
chatbot = gr.Chatbot(label="Generated Answer", show_share_button=False)
|
| 581 |
+
sources_textboxes = display_sources()
|
| 582 |
+
|
| 583 |
+
with gr.Column():
|
| 584 |
+
settings_elems = setup_user_settings(
|
| 585 |
+
reformulate_question=cfg.reformulate_question,
|
| 586 |
+
visible=cfg.reveal_user_settings,
|
| 587 |
+
num_sources=cfg.buster_cfg.retriever_cfg["top_k"],
|
| 588 |
+
max_sources=cfg.max_sources,
|
| 589 |
+
)
|
| 590 |
+
top_k_slider = settings_elems["top_k_slider"]
|
| 591 |
+
feedback_elems = setup_feedback_form(top_k_slider.value)
|
| 592 |
+
flag_button = setup_flag_button()
|
| 593 |
+
|
| 594 |
+
top_k_slider.change(
|
| 595 |
+
set_relevant_sources_selection, inputs=top_k_slider, outputs=feedback_elems["relevant_sources_selection"]
|
| 596 |
+
)
|
| 597 |
+
|
| 598 |
+
setup_additional_sources()
|
| 599 |
+
|
| 600 |
+
gr.HTML(
|
| 601 |
+
f"""
|
| 602 |
+
<center>
|
| 603 |
+
<div style='margin-bottom: 20px;'> <!-- Add margin to the bottom of this div -->
|
| 604 |
+
Powered by <a href='https://github.com/jerpint/buster'>Buster</a> 🤖
|
| 605 |
+
</div>
|
| 606 |
+
|
| 607 |
+
<div>
|
| 608 |
+
<a href='{path_to_tncs}'> Terms And Conditions </a>
|
| 609 |
+
</div>
|
| 610 |
+
</center>
|
| 611 |
+
"""
|
| 612 |
+
)
|
| 613 |
+
|
| 614 |
+
# fmt: off
|
| 615 |
+
# Allow use of submit button and hide checkbox when accepted
|
| 616 |
+
accept_terms_checkbox.select(
|
| 617 |
+
reveal_app,
|
| 618 |
+
outputs=[accept_terms_group, user_input, submit]
|
| 619 |
+
)
|
| 620 |
+
|
| 621 |
+
gr.on(
|
| 622 |
+
triggers=[submit.click, user_input.submit],
|
| 623 |
+
fn=add_user_question,
|
| 624 |
+
inputs=[user_input],
|
| 625 |
+
outputs=[chatbot]
|
| 626 |
+
).then(
|
| 627 |
+
clear_user_input,
|
| 628 |
+
outputs=[user_input]
|
| 629 |
+
).then(
|
| 630 |
+
clear_sources,
|
| 631 |
+
outputs=[*sources_textboxes]
|
| 632 |
+
).then(
|
| 633 |
+
toggle_visibility,
|
| 634 |
+
inputs=gr.State(False),
|
| 635 |
+
outputs=feedback_elems["submitted_message"],
|
| 636 |
+
).then(
|
| 637 |
+
toggle_interactivity,
|
| 638 |
+
inputs=gr.State(True),
|
| 639 |
+
outputs=feedback_elems["submit_feedback_btn"],
|
| 640 |
+
).then(
|
| 641 |
+
clear_feedback_form,
|
| 642 |
+
outputs=[
|
| 643 |
+
feedback_elems["overall_experience"],
|
| 644 |
+
feedback_elems["clear_answer"],
|
| 645 |
+
feedback_elems["accurate_answer"],
|
| 646 |
+
feedback_elems["relevant_sources"],
|
| 647 |
+
feedback_elems["relevant_sources_selection"],
|
| 648 |
+
feedback_elems["relevant_sources_order"],
|
| 649 |
+
feedback_elems["expertise"],
|
| 650 |
+
feedback_elems["extra_info"],
|
| 651 |
+
]
|
| 652 |
+
).then(
|
| 653 |
+
chat,
|
| 654 |
+
inputs=[chatbot, settings_elems["reformulate_question_cbox"], settings_elems["top_k_slider"]],
|
| 655 |
+
outputs=[chatbot, last_completion],
|
| 656 |
+
).then(
|
| 657 |
+
add_disclaimer,
|
| 658 |
+
inputs=[last_completion, chatbot, gr.State(cfg.disclaimer)],
|
| 659 |
+
outputs=[chatbot]
|
| 660 |
+
).then(
|
| 661 |
+
add_sources,
|
| 662 |
+
inputs=[last_completion, gr.State(max_sources)],
|
| 663 |
+
outputs=[*sources_textboxes]
|
| 664 |
+
).then(
|
| 665 |
+
log_completion,
|
| 666 |
+
inputs=[last_completion, gr.State(cfg.MONGO_COLLECTION_INTERACTION), session_id]
|
| 667 |
+
)
|
| 668 |
+
|
| 669 |
+
|
| 670 |
+
flag_button.click(
|
| 671 |
+
log_completion,
|
| 672 |
+
inputs=[last_completion, gr.State(cfg.MONGO_COLLECTION_FLAGGED), session_id]
|
| 673 |
+
).then(
|
| 674 |
+
raise_flagging_message,
|
| 675 |
+
)
|
| 676 |
+
|
| 677 |
+
# fmt: on
|
src/buster/gradio_app.py
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
|
| 3 |
+
from src.buster.buster_app import buster_app
|
| 4 |
+
|
| 5 |
+
concurrency_count = int(os.getenv("CONCURRENCY_COUNT", 32))
|
| 6 |
+
|
| 7 |
+
buster_app.queue(concurrency_count=concurrency_count, api_open=False)
|
| 8 |
+
buster_app.launch(share=False, show_api=False)
|
src/cfg.py
ADDED
|
@@ -0,0 +1,252 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
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|
|
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|
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|
|
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|
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|
|
|
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
|
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|
|
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|
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|
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|
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|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
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|
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
|
|
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|
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|
|
|
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|
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|
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|
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|
|
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import logging
|
| 2 |
+
import os
|
| 3 |
+
from pathlib import Path
|
| 4 |
+
|
| 5 |
+
import openai
|
| 6 |
+
|
| 7 |
+
from buster.busterbot import Buster, BusterConfig
|
| 8 |
+
from buster.completers import ChatGPTCompleter, DocumentAnswerer
|
| 9 |
+
from buster.formatters.documents import DocumentsFormatterJSON
|
| 10 |
+
from buster.formatters.prompts import PromptFormatter
|
| 11 |
+
from buster.llm_utils import QuestionReformulator
|
| 12 |
+
from buster.llm_utils.embeddings import get_openai_embedding_constructor
|
| 13 |
+
from buster.retriever import Retriever, ServiceRetriever
|
| 14 |
+
from buster.tokenizers import GPTTokenizer
|
| 15 |
+
from buster.validators import Validator
|
| 16 |
+
from src.app_utils import get_logging_db_name, init_db
|
| 17 |
+
|
| 18 |
+
logger = logging.getLogger(__name__)
|
| 19 |
+
logging.basicConfig(level=logging.INFO)
|
| 20 |
+
|
| 21 |
+
# Note: The app will not launch if the environment variables aren't set. This is intentional.
|
| 22 |
+
# Set OpenAI Configurations
|
| 23 |
+
openai.api_key = os.environ["OPENAI_API_KEY"]
|
| 24 |
+
openai.organization = os.environ["OPENAI_ORG_ID"]
|
| 25 |
+
|
| 26 |
+
# the embedding function that will get used throughout the app
|
| 27 |
+
embedding_fn = get_openai_embedding_constructor(
|
| 28 |
+
model="text-embedding-ada-002", client_kwargs={"timeout": 2, "max_retries": 2}
|
| 29 |
+
)
|
| 30 |
+
|
| 31 |
+
# Pinecone Configurations
|
| 32 |
+
PINECONE_API_KEY = os.environ["PINECONE_API_KEY"]
|
| 33 |
+
PINECONE_INDEX = "sai-hf"
|
| 34 |
+
PINECONE_NAMESPACE = "data-2024-02-07"
|
| 35 |
+
|
| 36 |
+
# MongoDB Configurations
|
| 37 |
+
MONGO_URI = os.environ["MONGO_URI"]
|
| 38 |
+
|
| 39 |
+
# Instance Configurations
|
| 40 |
+
INSTANCE_NAME = os.environ["INSTANCE_NAME"] # e.g., huggingface, heroku
|
| 41 |
+
INSTANCE_TYPE = os.environ["INSTANCE_TYPE"] # e.g. ["dev", "prod", "local"]
|
| 42 |
+
|
| 43 |
+
# MongoDB Databases
|
| 44 |
+
MONGO_DATABASE_LOGGING = get_logging_db_name(INSTANCE_TYPE) # Where all interactions will be stored
|
| 45 |
+
MONGO_DATABASE_DATA = "data-2024-02-07" # Where documents are stored
|
| 46 |
+
|
| 47 |
+
# Check that data chunks are aligned on Mongo and Pinecone
|
| 48 |
+
if MONGO_DATABASE_DATA != PINECONE_NAMESPACE:
|
| 49 |
+
logger.warning(
|
| 50 |
+
f"""The collection is different on pinecone and Mongo, is this expected?
|
| 51 |
+
|
| 52 |
+
{MONGO_DATABASE_DATA=}
|
| 53 |
+
{PINECONE_NAMESPACE=}
|
| 54 |
+
"""
|
| 55 |
+
)
|
| 56 |
+
|
| 57 |
+
# MongoDB Collections
|
| 58 |
+
# Naming convention: Collection name followed by purpose.
|
| 59 |
+
MONGO_COLLECTION_FEEDBACK = "feedback" # Feedback form
|
| 60 |
+
MONGO_COLLECTION_INTERACTION = "interaction" # User interaction
|
| 61 |
+
MONGO_COLLECTION_FLAGGED = "flagged" # Flagged interactions
|
| 62 |
+
|
| 63 |
+
# Make the connections to the databases
|
| 64 |
+
mongo_db = init_db(mongo_uri=MONGO_URI, db_name=MONGO_DATABASE_LOGGING)
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
# Set relative path to data dir
|
| 68 |
+
current_dir = Path(__file__).resolve().parent
|
| 69 |
+
data_dir = current_dir.parent / "data" # ../data
|
| 70 |
+
|
| 71 |
+
app_name = "AIR ️💬"
|
| 72 |
+
|
| 73 |
+
# User settings default values
|
| 74 |
+
reveal_user_settings = False # Wheter to display settings to the user or not
|
| 75 |
+
max_sources = 15 # maximum number of sources that can be set by a user for retrieval
|
| 76 |
+
reformulate_question = False # Default setting for reformulating a user's question
|
| 77 |
+
|
| 78 |
+
# sample questions
|
| 79 |
+
example_questions = [
|
| 80 |
+
"Are there any AI policies related to AI adoption in the public sector in the UK?",
|
| 81 |
+
"How is Canada evaluating the success of its AI strategy?",
|
| 82 |
+
"Has the EU proposed specific legislation on AI?",
|
| 83 |
+
]
|
| 84 |
+
|
| 85 |
+
|
| 86 |
+
disclaimer = f"""
|
| 87 |
+
**Use the feedback form on the right to help us improve** 👉
|
| 88 |
+
|
| 89 |
+
**Always verify the integrity of {app_name} responses using the sources provided below** 👇
|
| 90 |
+
"""
|
| 91 |
+
|
| 92 |
+
message_before_reformulation = "I reformulated your answer to: '"
|
| 93 |
+
message_after_reformulation = (
|
| 94 |
+
"'\n\nThis is done automatically to increase performance of the tool. You can disable this in the Settings ⚙️ tab."
|
| 95 |
+
)
|
| 96 |
+
|
| 97 |
+
# default client config for OpenAI Completions
|
| 98 |
+
client_kwargs = {
|
| 99 |
+
"api_key": os.environ["OPENAI_API_KEY"],
|
| 100 |
+
"organization": os.environ["OPENAI_ORG_ID"],
|
| 101 |
+
"timeout": 10,
|
| 102 |
+
"max_retries": 2,
|
| 103 |
+
}
|
| 104 |
+
|
| 105 |
+
|
| 106 |
+
buster_cfg = BusterConfig(
|
| 107 |
+
validator_cfg={
|
| 108 |
+
"use_reranking": True, # Reranks documents according to generated answer
|
| 109 |
+
"validate_documents": False, # Validates documents using chatGPT (expensive)
|
| 110 |
+
"answer_validator_cfg": {
|
| 111 |
+
"unknown_response_templates": [
|
| 112 |
+
"I cannot answer this question based on the information I have available",
|
| 113 |
+
"The information I have access to does not address the question",
|
| 114 |
+
],
|
| 115 |
+
"unknown_threshold": 0.84,
|
| 116 |
+
"embedding_fn": embedding_fn,
|
| 117 |
+
},
|
| 118 |
+
"question_validator_cfg": {
|
| 119 |
+
"invalid_question_response": """Thank you for your question! Unfortunately, I haven't been able to find the information you're looking for. Your question might be:
|
| 120 |
+
* Outside the scope of AI policy documents
|
| 121 |
+
* Too recent (i.e. draft policies) or about the future
|
| 122 |
+
* Building on my previous answer (I have no memory of previous conversations)
|
| 123 |
+
* Vague (i.e not affiliated with a specific country)
|
| 124 |
+
* Asking the model to perform its own assessment of the policies (i.e. What is the best/worst AI policy)
|
| 125 |
+
You can always try rewording your question and ask again!
|
| 126 |
+
""",
|
| 127 |
+
"check_question_prompt": """You are a chatbot answering questions on behalf of the OECD specifically on AI policies.
|
| 128 |
+
Your first job is to determine whether or not a question is valid, and should be answered.
|
| 129 |
+
For a question to be considered valid, it must be related to AI and policies.
|
| 130 |
+
More general questions are not considered valid, even if you might know the response.
|
| 131 |
+
A user will submit a question. Respond 'true' if it is valid, respond 'false' if it is invalid.
|
| 132 |
+
Do not judge the tone of the question. As long as it is relevant to the topic, respond 'true'.
|
| 133 |
+
|
| 134 |
+
For example:
|
| 135 |
+
Q: What policies did countries like Canada put in place with respect to artificial intelligence?
|
| 136 |
+
true
|
| 137 |
+
|
| 138 |
+
Q: What policies are put in place to ensure the wellbeing of agriculture?
|
| 139 |
+
false
|
| 140 |
+
|
| 141 |
+
Q:
|
| 142 |
+
""",
|
| 143 |
+
"completion_kwargs": {
|
| 144 |
+
"model": "gpt-3.5-turbo-0613",
|
| 145 |
+
"stream": False,
|
| 146 |
+
"temperature": 0,
|
| 147 |
+
},
|
| 148 |
+
"client_kwargs": client_kwargs,
|
| 149 |
+
},
|
| 150 |
+
},
|
| 151 |
+
retriever_cfg={
|
| 152 |
+
"pinecone_api_key": PINECONE_API_KEY,
|
| 153 |
+
"pinecone_index": PINECONE_INDEX,
|
| 154 |
+
"pinecone_namespace": PINECONE_NAMESPACE,
|
| 155 |
+
"mongo_uri": MONGO_URI,
|
| 156 |
+
"mongo_db_name": MONGO_DATABASE_DATA,
|
| 157 |
+
"top_k": 3,
|
| 158 |
+
"thresh": 0.7,
|
| 159 |
+
"embedding_fn": embedding_fn,
|
| 160 |
+
},
|
| 161 |
+
documents_answerer_cfg={
|
| 162 |
+
"no_documents_message": "No documents are available for this question.",
|
| 163 |
+
},
|
| 164 |
+
completion_cfg={
|
| 165 |
+
"completion_kwargs": {
|
| 166 |
+
"model": "gpt-3.5-turbo-0613",
|
| 167 |
+
"stream": True,
|
| 168 |
+
"temperature": 0,
|
| 169 |
+
},
|
| 170 |
+
"client_kwargs": client_kwargs,
|
| 171 |
+
},
|
| 172 |
+
tokenizer_cfg={
|
| 173 |
+
"model_name": "gpt-3.5-turbo-0613",
|
| 174 |
+
},
|
| 175 |
+
documents_formatter_cfg={
|
| 176 |
+
"max_tokens": 3500,
|
| 177 |
+
"columns": ["content", "source", "title"],
|
| 178 |
+
},
|
| 179 |
+
question_reformulator_cfg={
|
| 180 |
+
"completion_kwargs": {
|
| 181 |
+
"model": "gpt-3.5-turbo",
|
| 182 |
+
"stream": False,
|
| 183 |
+
"temperature": 0,
|
| 184 |
+
},
|
| 185 |
+
"system_prompt": """
|
| 186 |
+
Your role is to reformat a user's input into a question that is useful in the context of a semantic retrieval system.
|
| 187 |
+
Reformulate the question in a way that captures the original essence of the question while also adding more relevant details that can be useful in the context of semantic retrieval.""",
|
| 188 |
+
},
|
| 189 |
+
prompt_formatter_cfg={
|
| 190 |
+
"max_tokens": 4000,
|
| 191 |
+
"text_before_docs": (
|
| 192 |
+
"You are a chatbot assistant answering questions about artificial intelligence (AI) policies and laws. "
|
| 193 |
+
"You represent the OECD AI Policy Observatory. "
|
| 194 |
+
"You can only respond to a question if the content necessary to answer the question is contained in the information provided to you. "
|
| 195 |
+
"The information will be provided in a json format. "
|
| 196 |
+
"If the answer is found in the information provided, summarize it in a helpful way to the user. "
|
| 197 |
+
"If it isn't, simply reply that you cannot answer the question. "
|
| 198 |
+
"Do not refer to the documents directly, but use the information provided within it to answer questions. "
|
| 199 |
+
"Always cite which document you pulled information from. "
|
| 200 |
+
"Do not say 'according to the documentation' or related phrases. "
|
| 201 |
+
"Do not mention the documents directly, but use the information available within them to answer the question. "
|
| 202 |
+
"You are forbidden from using the expressions 'according to the documentation' and 'the provided documents'. "
|
| 203 |
+
"Here is the information available to you in a json table:\n"
|
| 204 |
+
),
|
| 205 |
+
"text_after_docs": (
|
| 206 |
+
"REMEMBER:\n"
|
| 207 |
+
"You are a chatbot assistant answering questions about artificial intelligence (AI) policies and laws. "
|
| 208 |
+
"You represent the OECD AI Policy Observatory. "
|
| 209 |
+
"Here are the rules you must follow:\n"
|
| 210 |
+
"1) You must only respond with information contained in the documents above. Say you do not know if the information is not provided.\n"
|
| 211 |
+
"2) Make sure to format your answers in Markdown format, including code block and snippets.\n"
|
| 212 |
+
"3) Do not reference any links, urls or hyperlinks in your answers.\n"
|
| 213 |
+
"4) Do not mention the documentation directly, but use the information provided within it to answer questions.\n"
|
| 214 |
+
"5) You are forbidden from using the expressions 'according to the documentation' and 'the provided documents'.\n"
|
| 215 |
+
"6) If you do not know the answer to a question, or if it is completely irrelevant to the library usage, simply reply with:\n"
|
| 216 |
+
"'I'm sorry, but I am an AI language model trained to assist with questions related to AI policies and laws. I cannot answer that question as it is not relevant to AI policies and laws. Is there anything else I can assist you with?'\n"
|
| 217 |
+
"For example:\n"
|
| 218 |
+
"Q: What is the meaning of life for a qa bot?\n"
|
| 219 |
+
"A: I'm sorry, but I am an AI language model trained to assist with questions related to AI policies and laws. I cannot answer that question as it is not relevant to AI policies and laws. Is there anything else I can assist you with?\n"
|
| 220 |
+
"7) Always cite which document you pulled information from. Do this directly in the text. You can refer directly to the title in-line with your answer. Make it clear when information came directly from a source. "
|
| 221 |
+
"8) If the information available to you does not directly address the question, simply state that you do not have the information required to answer. Do not summarize what is available to you. "
|
| 222 |
+
"For example, say: 'I cannot answer this question based on the information I have available.'\n"
|
| 223 |
+
"9) Keep a neutral tone, and put things into context.\n"
|
| 224 |
+
"For example:\n"
|
| 225 |
+
"Q: What do African countries say about data privacy?\n"
|
| 226 |
+
"A: There are currently 28 countries in Africa that have personal data protection legislation. However, limited resources, a lack of clear leadership in the region and localized approaches with regard to data-driven technology run the risk of creating an unfavorable environment for data privacy regulation from a business and data rights standpoint. For example, without policies for data sharing across countries, multinational data companies may choose to move their foreign direct investment to more favorable destinations. African countries also grapple with issues of higher priority, which stunts progress in the field of data privacy. According to one regional policy expert, “a government that is still battling [to set up a] school feeding programme in 2019 is not going to be the one to prioritise data and data protection policies with respect to AI.”\n"
|
| 227 |
+
"Now answer the following question:\n"
|
| 228 |
+
),
|
| 229 |
+
},
|
| 230 |
+
)
|
| 231 |
+
|
| 232 |
+
|
| 233 |
+
def setup_buster(buster_cfg):
|
| 234 |
+
retriever: Retriever = ServiceRetriever(**buster_cfg.retriever_cfg)
|
| 235 |
+
tokenizer = GPTTokenizer(**buster_cfg.tokenizer_cfg)
|
| 236 |
+
document_answerer: DocumentAnswerer = DocumentAnswerer(
|
| 237 |
+
completer=ChatGPTCompleter(**buster_cfg.completion_cfg),
|
| 238 |
+
documents_formatter=DocumentsFormatterJSON(tokenizer=tokenizer, **buster_cfg.documents_formatter_cfg),
|
| 239 |
+
prompt_formatter=PromptFormatter(tokenizer=tokenizer, **buster_cfg.prompt_formatter_cfg),
|
| 240 |
+
**buster_cfg.documents_answerer_cfg,
|
| 241 |
+
)
|
| 242 |
+
validator = Validator(**buster_cfg.validator_cfg)
|
| 243 |
+
|
| 244 |
+
question_reformulator = QuestionReformulator(**buster_cfg.question_reformulator_cfg)
|
| 245 |
+
|
| 246 |
+
buster: Buster = Buster(
|
| 247 |
+
retriever=retriever,
|
| 248 |
+
document_answerer=document_answerer,
|
| 249 |
+
validator=validator,
|
| 250 |
+
question_reformulator=question_reformulator,
|
| 251 |
+
)
|
| 252 |
+
return buster
|
src/feedback.py
ADDED
|
@@ -0,0 +1,200 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
import logging
|
| 4 |
+
from dataclasses import dataclass
|
| 5 |
+
from typing import Any, Type
|
| 6 |
+
|
| 7 |
+
import pandas as pd
|
| 8 |
+
import pymongo
|
| 9 |
+
from fastapi.encoders import jsonable_encoder
|
| 10 |
+
from pyparsing import Optional
|
| 11 |
+
|
| 12 |
+
from buster.completers import UserInputs
|
| 13 |
+
from buster.completers.base import Completion
|
| 14 |
+
|
| 15 |
+
logger = logging.getLogger(__name__)
|
| 16 |
+
logging.basicConfig(level=logging.INFO)
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
@dataclass
|
| 20 |
+
class StandardForm:
|
| 21 |
+
def to_json(self) -> Any:
|
| 22 |
+
return jsonable_encoder(self)
|
| 23 |
+
|
| 24 |
+
@classmethod
|
| 25 |
+
def from_dict(cls, interaction_dict: dict) -> StandardForm:
|
| 26 |
+
return cls(**interaction_dict)
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
@dataclass
|
| 30 |
+
class FeedbackForm(StandardForm):
|
| 31 |
+
"""Form on the original Buster app."""
|
| 32 |
+
|
| 33 |
+
# Overall experience
|
| 34 |
+
overall_experience: str
|
| 35 |
+
|
| 36 |
+
# Answer Quality
|
| 37 |
+
clear_answer: str
|
| 38 |
+
accurate_answer: str
|
| 39 |
+
|
| 40 |
+
# Source Relevance
|
| 41 |
+
relevant_sources: str
|
| 42 |
+
relevant_sources_order: str
|
| 43 |
+
relevant_sources_selection: list
|
| 44 |
+
|
| 45 |
+
# beginner, intermediate, expert at AI policy?
|
| 46 |
+
expertise: list[str]
|
| 47 |
+
|
| 48 |
+
# Additional Feedback
|
| 49 |
+
extra_info: str
|
| 50 |
+
|
| 51 |
+
|
| 52 |
+
@dataclass
|
| 53 |
+
class ComparisonForm(StandardForm):
|
| 54 |
+
"""Easily readable comparison result on the battle arena."""
|
| 55 |
+
|
| 56 |
+
question: str
|
| 57 |
+
model_left: str
|
| 58 |
+
model_right: str
|
| 59 |
+
vote: str
|
| 60 |
+
extra_info: str
|
| 61 |
+
|
| 62 |
+
|
| 63 |
+
@dataclass
|
| 64 |
+
class Interaction:
|
| 65 |
+
user_completions: list[Completion]
|
| 66 |
+
time: str
|
| 67 |
+
session_id: str # A unique identifier for each gradio session, e.g. UUID
|
| 68 |
+
username: Optional[str] = None
|
| 69 |
+
instance_type: Optional[str] = None # Dev or prod
|
| 70 |
+
instance_name: Optional[str] = None # Heroku, hf-space, etc.
|
| 71 |
+
data_version: Optional[str] = None # Which collection of the was used
|
| 72 |
+
form: Optional[StandardForm] = None
|
| 73 |
+
|
| 74 |
+
def send(self, mongo_db: pymongo.database.Database, collection: str):
|
| 75 |
+
feedback_json = self.to_json()
|
| 76 |
+
logger.info(feedback_json)
|
| 77 |
+
|
| 78 |
+
try:
|
| 79 |
+
mongo_db[collection].insert_one(feedback_json)
|
| 80 |
+
logger.info(f"response logged to mondogb {collection=}")
|
| 81 |
+
except Exception as err:
|
| 82 |
+
logger.exception(f"Something went wrong logging to mongodb {collection=}")
|
| 83 |
+
raise err
|
| 84 |
+
|
| 85 |
+
def flatten(self) -> dict:
|
| 86 |
+
"""Flattens the Interaction object into a dict for easier reading."""
|
| 87 |
+
interaction_dict = self.to_json()
|
| 88 |
+
|
| 89 |
+
# Flatten user completions, only keep the most recent interaction
|
| 90 |
+
if len(interaction_dict["user_completions"]) > 0:
|
| 91 |
+
completion_dict = interaction_dict["user_completions"][-1]
|
| 92 |
+
# # TODO: add test for this...
|
| 93 |
+
for k in completion_dict.keys():
|
| 94 |
+
interaction_dict[f"completion_{k}"] = completion_dict[k]
|
| 95 |
+
del interaction_dict["user_completions"]
|
| 96 |
+
|
| 97 |
+
if self.form is not None:
|
| 98 |
+
# Flatten feedback form
|
| 99 |
+
for k in interaction_dict["form"].keys():
|
| 100 |
+
interaction_dict[f"form_{k}"] = interaction_dict["form"][k]
|
| 101 |
+
del interaction_dict["form"]
|
| 102 |
+
|
| 103 |
+
# Flatten matched documents
|
| 104 |
+
interaction_dict["matched_documents"] = self.user_completions[-1].matched_documents
|
| 105 |
+
interaction_dict["matched_documents"].reset_index(inplace=True)
|
| 106 |
+
interaction_dict["matched_documents"].drop(columns=["index"], inplace=True)
|
| 107 |
+
interaction_dict["matched_documents"] = interaction_dict["matched_documents"].T
|
| 108 |
+
if len(interaction_dict["matched_documents"]) > 0:
|
| 109 |
+
for k in interaction_dict["matched_documents"].keys():
|
| 110 |
+
interaction_dict[f"matched_documents_{k}"] = interaction_dict["matched_documents"][k].values
|
| 111 |
+
del interaction_dict["matched_documents"]
|
| 112 |
+
|
| 113 |
+
return interaction_dict
|
| 114 |
+
|
| 115 |
+
def to_json(self) -> Any:
|
| 116 |
+
custom_encoder = {
|
| 117 |
+
# Converts the matched_documents in the user_completions to json
|
| 118 |
+
Completion: lambda completion: completion.to_json(columns_to_ignore=["embedding", "_id"]),
|
| 119 |
+
}
|
| 120 |
+
|
| 121 |
+
to_encode = {
|
| 122 |
+
"username": self.username,
|
| 123 |
+
"session_id": self.session_id,
|
| 124 |
+
"user_completions": self.user_completions,
|
| 125 |
+
"time": self.time,
|
| 126 |
+
"instance_type": self.instance_type,
|
| 127 |
+
"instance_name": self.instance_name,
|
| 128 |
+
"data_version": self.data_version,
|
| 129 |
+
}
|
| 130 |
+
|
| 131 |
+
if self.form is not None:
|
| 132 |
+
to_encode["form"] = self.form.to_json()
|
| 133 |
+
|
| 134 |
+
return jsonable_encoder(to_encode, custom_encoder=custom_encoder)
|
| 135 |
+
|
| 136 |
+
@classmethod
|
| 137 |
+
def from_dict(cls, interaction_dict: dict, feedback_cls: Optional[Type[StandardForm]] = None) -> Interaction:
|
| 138 |
+
# remove the _id from mongodb
|
| 139 |
+
if "_id" in interaction_dict.keys():
|
| 140 |
+
del interaction_dict["_id"]
|
| 141 |
+
|
| 142 |
+
interaction_dict["user_completions"] = [Completion.from_dict(r) for r in interaction_dict["user_completions"]]
|
| 143 |
+
|
| 144 |
+
if "form" in interaction_dict.keys():
|
| 145 |
+
# The interaction contained a type of form, e.g. feedback form, parse it accordingly
|
| 146 |
+
|
| 147 |
+
# Make sure the user specified a feedback_cls
|
| 148 |
+
assert feedback_cls is not None, "You must specify which type of feedback it is"
|
| 149 |
+
|
| 150 |
+
interaction_dict["form"] = feedback_cls.from_dict(interaction_dict["form"])
|
| 151 |
+
|
| 152 |
+
return cls(**interaction_dict)
|
| 153 |
+
|
| 154 |
+
|
| 155 |
+
def read_collection(
|
| 156 |
+
mongo_db: pymongo.database.Database,
|
| 157 |
+
collection: str,
|
| 158 |
+
feedback_cls: Optional[Type[StandardForm]] = None,
|
| 159 |
+
filters: Optional[dict] = None,
|
| 160 |
+
) -> pd.DataFrame:
|
| 161 |
+
"""
|
| 162 |
+
Retrieve data from a MongoDB collection and return it as a pandas DataFrame.
|
| 163 |
+
|
| 164 |
+
Parameters:
|
| 165 |
+
- mongo_db (pymongo.database.Database): The MongoDB database instance.
|
| 166 |
+
- collection (str): The name of the MongoDB collection to read from.
|
| 167 |
+
- feedback_cls (Optional[Type[StandardForm]]): A class to which the retrieved data might be mapped.
|
| 168 |
+
If the collection contains instances of Interaction, this is not needed. If a form is attached
|
| 169 |
+
(i.e., interaction["form"] exists), it should be provided.
|
| 170 |
+
- filters (Optional[dict]): A dictionary of filters to apply to the mongodb query. If not provided,
|
| 171 |
+
all items in the collection are returned. E.g., to get interactions from a specific user,
|
| 172 |
+
use `filters={"username": <username>}`.
|
| 173 |
+
|
| 174 |
+
Returns:
|
| 175 |
+
- pd.DataFrame: A DataFrame containing the retrieved data. Data is flattened for convenience.
|
| 176 |
+
|
| 177 |
+
Notes:
|
| 178 |
+
- Interactions that cannot be processed are skipped, and a log message is generated with the
|
| 179 |
+
count of retrieved and skipped entries.
|
| 180 |
+
"""
|
| 181 |
+
flattened_interactions = []
|
| 182 |
+
skipped_interactions = []
|
| 183 |
+
interactions = mongo_db[collection].find(filters)
|
| 184 |
+
for interaction in interactions:
|
| 185 |
+
try:
|
| 186 |
+
if user_input := interaction["user_completions"][0].get("user_input"):
|
| 187 |
+
# We used to only have a single key for user input
|
| 188 |
+
# This changed when we introduced question reformulation.
|
| 189 |
+
# Only useful to maintain backwards compatibility with data collected previously
|
| 190 |
+
interaction["user_completions"][0]["user_inputs"] = UserInputs(user_input)
|
| 191 |
+
del interaction["user_completions"][0]["user_input"]
|
| 192 |
+
|
| 193 |
+
flattened_interaction = Interaction.from_dict(interaction, feedback_cls=feedback_cls).flatten()
|
| 194 |
+
flattened_interactions.append(flattened_interaction)
|
| 195 |
+
except Exception as err:
|
| 196 |
+
skipped_interactions.append(interaction)
|
| 197 |
+
|
| 198 |
+
logger.info(f"Retrieved {len(flattened_interactions)} entries. Skipped {len(skipped_interactions)} entries")
|
| 199 |
+
|
| 200 |
+
return pd.DataFrame(flattened_interactions)
|