GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: Joint Committee on Taxation Research Aide
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: The Joint Committee on Taxation Review (JCTR) Research Aide is a generative AI (GenAI) system that uses Retrieval Augmented Generation (RAG) search to answer questions on JCTR policies and procedures that are provided in natural language. This tool has a use case specific user interface (UI) that uses the Certara platform via Application Programming Interface (API) to perform the RAG search and generation.
12_outputs: This system uses an embedding model to produce a vector representation of texts for contextual searching, and Large Language Model to generate a response to user inquiries. Outputs of the tool include the model generated response to a user's inquiry, as well as the text from relevant documents identified in the retrieval stage and used by the model in generating said response.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 1/15/2024
19_date_acq_dev_began: 1/15/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 2032H8-23-F-00166
24_hisp_support: No
31_data_catalog: Yes
33_agency_data: Text from the sections of the Internal Revenue Manual relevant to the Joint Committee (JC) (4.36) and instructional/training documents provided by the IRS to JC examiners and staff.
34_data_docs: Documentation is complete: Documentation exists regarding the maintenance, composition, quality, and intended use of the training and evaluation data, as well as any statistical bias across model features and protected groups.
40_has_ato: Yes
41_system_name: RAS-1
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Other
45_question_type: We do not train any models associated with this use case. The LLMs are downloaded pretrained and hosted in the Certara tools.
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Documentation has been published: Complete documentation has been published to a repository or data catalog within the agency and is made accessible to other data science teams for review and feedback.
2_use_case_name: Technical Demo of Large Language Models for Code Development
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Problem: IRS developers spend significant time developing code and unit tests. IRS developers do not currently benefit from AI-assisted code development, which can greatly improve the accuracy and efficiency of development work. 

Use Case: Using llamafile and collama IDE plugins within VS Code, developers will be able to utilize code completion and suggestion, code generation, code refactoring, code documentation, debugging and unit testing capabilities to optimize the developer experience and produce high-integrity code solutions.

Why now? Developers need some interim solution to leverage Generative AI (GenAI) capability while the long-term Enterprise Solution is being developed.
12_outputs: Text Generation, Summarization, Code Completion, Unit Tests, Text Translation, Text-to-Text Transformation.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 5/12/2024
2_use_case_name: Internal Revenue Manual Research Aid (IRMA)
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: IRMA - Internal Revenue Manual (IRM) Research Aide is a generative AI (GenAI) system that uses Retrieval Augmented Generation (RAG) search to answer questions on IRM policies and procedures that are provided in natural language. This tool has a use case specific user interface (UI) that uses the Certara platform via Application Programming Interface (API) to perform the RAG search and generation.
12_outputs: This system uses an embedding model to produce a vector representation of texts for contextual searching, and Large Language Model to generate a response to user inquiries. Outputs of the tool include the model generated response to a user's inquiry, as well as the text from relevant documents identified in the retrieval stage and used by the model in generating said response.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 5/9/2024
19_date_acq_dev_began: 5/10/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 2032H8-23-F-00166
24_hisp_support: No
31_data_catalog: Yes
33_agency_data: All text from the sections and subsections of the unredacted Internal Revenue Manual.
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
40_has_ato: Yes
41_system_name: RAS-1
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Other
45_question_type: We do not train any models associated with this use case. The LLMs are downloaded pretrained and hosted in the Certara tools.
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Documentation has been published: Complete documentation has been published to a repository or data catalog within the agency and is made accessible to other data science teams for review and feedback.
2_use_case_name: Tax Payer Notice Modernization
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: Improving the quality of written communications using AI tools.
11_purpose_benefits: The purpose of this AI project is to modernize and simplify tax notices for better taxpayer comprehension. The AI accomplishes this by transforming complex tax language into clear, accessible content. The model automates the generation of these revised notices, with human reviewers ensuring accuracy and relevance before dissemination. Anticipated benefits include reduced errors and inquiries, increased taxpayer satisfaction, and improved efficiency in tax administration. The direct impact is clearer communication with taxpayers, who are the primary population affected by this initiative, resulting in easier navigation of their tax obligations. 
12_outputs: Rewritten taxpayer notices presented in clear, concise language.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
2_use_case_name: Enable Face ID to unlock M365 apps on Government iPhone and iPad
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: Unlocking smartphones or other devices without the need for passwords or PINs using AI-based facial recognition.
11_purpose_benefits: Improve Ease of use for customer accessing Org Data in M365 apps and TEAMS on government iPhone and IPad.Customers would no longer need to continuously input Password into the M365 apps if Face ID is enabled. https://support.apple.com/en-us/102381
12_outputs: The AI model unlocks government iPhones or iPads and Applications like Microsoft's Teams, Outlook and Other apps by comparing the customers face geometry. “Face ID analyzes thousands of invisible infrared dots to create a depth map of your face, which then captures an infrared image of your face.” 

16_dev_stage: Implementation and Assessment
17_impact_type: Neither
2_use_case_name: Data Integration using Informatica Data Management Cloud
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Informatica Intelligent Cloud Services Overview 

Informatica Intelligent Cloud Services (IICS) is a cloud-native data integration and management platform that enables organizations to connect, access, transform, and govern data across hybrid and multi-cloud environments. IICS leverages artificial intelligence and machine learning to automate and optimize data processes, enhance data quality, and accelerate data insights. IICS offers a range of services and features, such as: 

Data Integration: A service that enables users to design, develop, and deploy data integration workflows and tasks across cloud and on-premises sources and targets, using a graphical user interface or a code-based environment. Data Integration supports various data integration patterns, such as batch, real-time, streaming, and change data capture. 

The solution enables Integrated Production Model (IPM) to load data directly to the cloud from on-premises sources.  Without the solution, there's no native support to load data to Databricks, causing extra work and less-than-optimal solutions to maintain and develop.  Any custom needed IPM data is impacted by this solution.
12_outputs: The Informatica Artificial Intelligence (AI), named Claire, can make the following types of recommendations during mapping design:
- Recommend transformation types to include in the mapping.
- Recommend additional sources based on primary key and foreign key relationships.
- Recommend joining or unioning additional sources.
- Make recommendations for objects in a mapping inventory.
- Recommend mapplets or user-defined functions.
- Make recommendations to standardize your data
- Make recommendations to mask sensitive data.
- Recommend rule specifications.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 4/1/2024
19_date_acq_dev_began: 11/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 2032H5-21-F-00059 / NNG15SD22B
24_hisp_support: No
31_data_catalog: Yes
33_agency_data: The source information comes from the Informatica mapping development work.
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
40_has_ato: No
42_dev_tools_wait: More than 12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Re-use production level code and/or data products: This use case re-uses production level code as well as data products that have been published or made widely available for data science teams for within the agency.
50_internal_review: Documentation has been published: Complete documentation has been published to a repository or data catalog within the agency and is made accessible to other data science teams for review and feedback.
2_use_case_name: Answering Employee Questions with Natural Language Processing in IRWorks
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: The purpose of the Artificial Intelligence (AI) element of the IRWorks platform (a ServiceNow implementation for the IRS) is to utilize natural language to respond to common user questions about IRWorks knowledge base (KB) articles and service catalogue items in the IRWorks Employee Center. This AI element is interpretive.
At a high level, this is accomplished by using language models to train the Virtual Agent (a ServiceNow product) to respond to user questions.
The decision/judgement that this AI element uses is to search existing Knowledge Base (KBs)/service catalogue items, in conjunction with the user's defined access within IRWorks, to automate Tier 1 support by outputting (in natural language) answers and/or associated links that align to the customer's (natural language) query.
Yes, humans are involved in reviewing the output - the AI element does not produce actionable items but produces information or links that are provided to the querying user for them to review and/or take manual actions.
The anticipated benefits of this AI element of the IRWorks platform are to reduce costs of Tier 1 support and provide a better user experience. 
The direct/ultimate impact of this decision is to reduce costs of Tier 1 support and provide a better user experience.
The population impacted by this decision is all IRWorks users, about 90K+ IRS employees.
12_outputs: Improve efficiency and optimize outputs for end users requesting services/information from within ServiceNow.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 4/30/2023
19_date_acq_dev_began: 4/30/2023
20_date_implemented: 4/30/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 47QTCA22D00B2; GS35F0414R; 47QTCA22D00B2
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: IRS IRWorks Knowledge Management
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
37_custom_code: No
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: IRWorks
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Re-use production level code and/or data products: This use case re-uses production level code as well as data products that have been published or made widely available for data science teams for within the agency.
50_internal_review: Limited documentation for review: Some information regarding the model’s performance on specific benchmarks are available or have been shared with specific stakeholders within the agency.
2_use_case_name: Ask-CFO Research Aide
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Ask-CFO is an extension of the Research Aide developed using the Certara Composer platform originally designed for the Joint Committee on Taxation Research Aide (JCR) and Internal Revenue Manual Research Aid (IRMA) use cases. It is a Retrieval Augmented Generation (RAG) search on a number of Chief Financial Officer (CFO) specific documents. In addition to the existing research aide capability and user interface (UI), extensions will be developed to incorporate AI Agents that can perform actions such as document summary comparison over fiscal year, or extract information from tables.
12_outputs: This system uses an embedding model to produce a vector representation of texts for contextual searching, and Large Language Model to generate a response to user inquiries. Outputs of the tool include the model generated response to a user's inquiry, as well as the text from relevant documents identified in the retrieval stage and used by the model in generating said response.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 8/1/2024
19_date_acq_dev_began: 8/1/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 2032H823F00166
24_hisp_support: No
31_data_catalog: No
33_agency_data: Our team was provided with a sample of documents and reports used and produced by the office of the CFO. Text from these documents is used in this use-case.
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
40_has_ato: Yes
41_system_name: RAS-1
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Other
45_question_type: We do not train any models associated with this use case. The LLMs are downloaded pretrained and hosted in the Certara tools.
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Documentation has been developed: Complete documentation detailing model performance across a range of benchmarks, architecture, relevant features and information regarding the appropriate use of the model for predictive tasks has been created.
2_use_case_name: Intelligent Document Management System (IDMS)
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: IDMS is a vendor managed cloud platform solution which will provide an enterprise capability to process, store, retrieve, manage, and share a variety of documents.  Utilizing a Platform-as-a-Service (PaaS) model, this robust cloud-hosted platform will improve the overall document management user experience, utilizing artificial intelligence and machine learning to automate extraction, processing, and analyzing of critical data from multiple structured and unstructured formats.  In this way, IDMS will minimize the need for manual document processing, scaling to rapidly process large volumes of data accurately, reducing data processing costs and swiftly delivering responses with detailed and relevant information.  This allows the customer to review the AI output to enhance their decision-making process.  The initial customer is the Office of Chief Counsel. IDMS will integrate with existing and future critical business platforms to provide a seamless end-to-end user experience.
12_outputs: Output of the model is usually a JavaScript Object Notation (JSON) text payload resulting from the Inference Application Programming Interface (API) calls with unique id referencing the document source
16_dev_stage: Initiated
17_impact_type: Rights-Impacting
2_use_case_name: Taxpayer 90 (Palantir prototype)
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Palantir AIP will interact with synthetic data and public information (e.g. IRM and tax forms) to summarize documentation and parse through information more quickly. AIP is enabled within SaaS platform (only within SaaS, no firewall changes/proxy exceptions needed), shared with Selection aNd Analytic Platform (SNAP), but AIP is only permissioned to users with the Taxpayer 90 Business Entitlement Access Request System (BEARS) entitlement. Data is contained within the Software as a Service (SaaS) tenant.
12_outputs: Summary of synthetic data and public information (e.g. Internal Revenue Manual (IRM) and tax forms).
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 10/30/2024
19_date_acq_dev_began: 9/4/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 2032H5-18-A-00029
24_hisp_support: No
31_data_catalog: No
33_agency_data: Test data provided only for prototype development
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
40_has_ato: Yes
41_system_name: SNAP-TP90
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Documentation has been published: Complete documentation has been published to a repository or data catalog within the agency and is made accessible to other data science teams for review and feedback.
2_use_case_name: Expanded Systran Translation Software
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Internal Revenue Service-Criminal Investigation (IRS-CI) is looking to acquire a high-volume enterprise license for Systran.  This is the same product that Research, Applied Analytics and Statistics (RAAS) currently uses, but will be expanded to allow high volume processing through multiple Graphic Processing Units (GPUs), enabling large quantities of documents to be translated in a relatively short time.  IRS-CI needs this capability to translate seized data in foreign languages.  
12_outputs: The output is a PDF document containing the translation of the documents.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 3/15/2024
19_date_acq_dev_began: 11/5/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: No contract number as acquisition is still pending
24_hisp_support: No
31_data_catalog: Other
31_question_type: Not needed.  
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
40_has_ato: Yes
41_system_name: CI-1, CI-2
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Other
45_question_type: not applicable.  
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
50_internal_review: No documentation is available: No documentation detailing model performance metrics, model architecture, features and intended use of the models have been created or are currently accessible to other data science teams within the agency.
54_key_risks: Secure storage of content at rest and in flight, we are using Google Cloud resource that will be hardened and secured in the IRS environment for production deployment
2_use_case_name: Transcription -- Evidence.com
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: Transcribing and summarizing a recorded meeting or interview using AI.
11_purpose_benefits: Evidence.com provides an accurate AI based transcription tool for law enforcement recordings.
12_outputs: The evidence.com site produces a word document.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
2_use_case_name: Digital Forensics Chatbot for IRS Employees
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: a chatbot style question/answer application for all things digital forensics. This could help examiners with new and emerging technology when encountered in the field, help write bash and python scripts to manage data, basically anything digital forensics. Currently examiners have to rely on google and other open source information to get answers to questions that arise.
12_outputs: Output would include information as to specific hex or code sequences, location of stored data on various system, information as to the access or known exploits of encountered systems to name a few. 
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither