GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: EDGAR Filing Certification Review Solution 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of Information Technology (OIT)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Inputting large amounts of data from paper forms into a digital system using AI.
11_purpose_benefits: Identifies potentially non-compliant 302 certifications of EDGAR filings.
12_outputs: Tables containing potentially non-compliant filing data.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 23-Jan
19_date_acq_dev_began: 23-Apr
20_date_implemented: 23-Dec
22_dev_method: Developed with contracting resources.
23_contract_piids: 503102-20-F-0059
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: EDGAR filing data
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: AI Disclosure Analytics (AIDA)
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: 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: Evaluating Cybersecurity Alerts
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of Information Technology (OIT)
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Enhances identification of anomalous cybersecurity alerts for review. 
12_outputs: Tables containing anomalous cybersecurity alerts.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 24-May
2_use_case_name: EDGAR Filing Audit Report Solution 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of Information Technology (OIT)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Inputting large amounts of data from paper forms into a digital system using AI.
11_purpose_benefits: Utilizing a tool to identify audit reports included in EDGAR filings that are potentially non-compliant with SEC Rules and Regulations.
12_outputs: Tables containing potentially non-compliant filing data.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 24-Feb
19_date_acq_dev_began: 24-Apr
20_date_implemented: 25-Feb
22_dev_method: Developed with contracting resources.
23_contract_piids: 503102-20-F-0059
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: EDGAR filing data
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: AIDA
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: 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: Public Filing Disclosure Review
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of the Chief Data Officer (OCDO)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: None of the above.
11_purpose_benefits: Summarizes public filing disclosures and identifying differences and similarities between disclosures.

12_outputs: Summaries of disclosures and answers to user-selected questions.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 24-Aug
19_date_acq_dev_began: 24-Aug
20_date_implemented: 24-Oct
22_dev_method: Developed with contracting resources.
23_contract_piids: 50310224F0089
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Other
31_question_type: Not Applicable
33_agency_data: Not Applicable
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.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Other
45_question_type: Not Applicable
47_timely_resources: Other
47_question_type: Not Applicable
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: 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: EDGAR Technical Support Public Chatbot
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: EDGAR Business Office (EBO)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Provides public users quick answers to technical questions about accessing EDGAR. 
12_outputs: Responses or links to existing technical documentation. 
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 24-Nov
2_use_case_name: EDGAR Filing Signature Review Solution 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of Information Technology (OIT)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Inputting large amounts of data from paper forms into a digital system using AI.
11_purpose_benefits: Identifies when required signatures are potentially missing in EDGAR filings.
12_outputs: Tables containing potentially non-compliant filing data.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 23-Oct
19_date_acq_dev_began: 23-Dec
20_date_implemented: 25-Feb
22_dev_method: Developed with contracting resources.
23_contract_piids: 503102-20-F-0059
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: EDGAR filing data
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: AIDA
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: 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: EDGAR Filing Risk Disclosure Review Solution 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of Information Technology (OIT)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Inputting large amounts of data from paper forms into a digital system using AI.
11_purpose_benefits: Analyzes earnings call transcripts and EDGAR filing disclosure of risk factors.
12_outputs: Table of summarized earnings call data and EDGAR filing comparison.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 23-Dec
19_date_acq_dev_began: 23-Dec
20_date_implemented: 25-Feb
22_dev_method: Developed with contracting resources.
23_contract_piids: 503102-20-F-0059
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: EDGAR filing data
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: AIDA
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: 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: Testing Developer Workflows
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Strategic Hub for Innocation and Financial Technology (FinHub)
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Tests workflows to inform guidance for future AI use case development.
12_outputs: In planning phase - TBD
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 24-Nov
2_use_case_name: Exploring AI Products for Enterprise Use
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Office of Information Technology (OIT)
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Tests web-based AI features. 
12_outputs: In planning phase - TBD
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 24-Nov
2_use_case_name: Name Matching
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: None of the above.
11_purpose_benefits: Identifies certain similarities in names across data sources. This allows staff to more easily compare information across data sources. 
12_outputs: The system outputs a number which measures how closely names match.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 18-Feb
19_date_acq_dev_began: 18-Jan
20_date_implemented: 18-Feb
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: SECHQ16A0013
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Other
31_question_type: Use case already developed
33_agency_data: Registrant data
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.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: NEAT
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
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: 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: Parsing of Plain Language Descriptions to Machine-Readable Notations
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: None of the above.
11_purpose_benefits: Automates conversion of plain-language text into machine-readable standardized notations.  This permits ease of analysis.
12_outputs: The system outputs machine-readable notations.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 22-Feb
19_date_acq_dev_began: 21-Oct
20_date_implemented: 22-Feb
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: 50310220D0012
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Other
31_question_type: Use case already developed
33_agency_data: Registrant data
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. 
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: NEAT
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
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: 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: Identification of Potentially Manipulative Trading Activity in Registrant Data
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Identifies potentially manipulative trading activity for further review by an examination team.
12_outputs: The system identifies activity of interest.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 22-Mar
19_date_acq_dev_began: 21-May
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: 50310220D0012
24_hisp_support: No
31_data_catalog: Yes
33_agency_data: Registrant data
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: Not Applicable
40_has_ato: Yes
41_system_name: HALSI
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
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: 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: Testing of Various AI Algorithms and Models 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Summarizing the key points of a lengthy report using AI.
11_purpose_benefits: Experimentation using technology to determine if appropriate to enhance examiner efficiency, productivity, or effectiveness.
12_outputs: In planning phase - TBD
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 24-Apr
2_use_case_name: Using Natural Language Processing Techniques to Search and Analyze Certain Filings 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Helps search and analyze a corpus of unstructured filings. Staff may consider the results of these efforts in their examination efforts.
12_outputs: This system allows for search and analysis of certain filings.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 20-Apr
2_use_case_name: Using Machine Learning/Artificial Intelligence Techniques to Predict Entities With Certain Risk Characteristics
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: None of the above.
11_purpose_benefits: Analyze data to predict entities with certain risk characteristics. Staff may consider the results of these efforts in their examination efforts. 
12_outputs: This system provides predictive information.  
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 14-Jan
19_date_acq_dev_began: 14-Jan
20_date_implemented: 15-Apr
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: SECHQ113A0004
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Filings and examination data
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. 
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: EDW
42_dev_tools_wait: 6-12 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: 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.
2_use_case_name: Developed Parsing Logic for Filings 
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: None of the above.
11_purpose_benefits: Help staff more efficiently search and analyze disclosure text contained in various filings.
12_outputs: These efforts will help to search and analyze certain filings.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 20-Jan
19_date_acq_dev_began: 23-May
20_date_implemented: 24-Jul
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: 50310219D0008
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Filings
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. 
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: AI Filing Parser
42_dev_tools_wait: More than 12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: No
49_existing_reuse: Re-use production level code from a different use-case: This use case re-uses production level code and/or internally developed code libraries for model development from existing AI systems or repositories inside 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: Identification of Potentially Manipulative Activity in Certain Accounts
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Examinations (EXAMS)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Identifies accounts with certain activity of interest for further review by an examination team.
12_outputs: The system identifies activity of interest.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 21-Oct
19_date_acq_dev_began: 20-Oct
20_date_implemented: 24-May
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: 50310220D0012
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Registrant and market data
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: NEAT
42_dev_tools_wait: 6-12 months
43_infra_provisioned: Yes
45_compute_request: Yes
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.