GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: Pre-Effectuation Review / Targeted Denial Review Models
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Analytics, Review, and Oversight
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: This AI use case identifies high likelihood of error in certain claims and refers them for review. This use case reduces incorrect benefits payment.
12_outputs: Probability scores via an in-line mainframe process
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 1/1/1996
19_date_acq_dev_began: Current model: 2020-2024
20_date_implemented: 12/1/2024
22_dev_method: Developed in-house.
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Models used data from disability program data sets.
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: Age
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: No
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.
51_extension_request: Yes – Agency requested an extension for this use case.
2_use_case_name: Representative Payee Misuse Model
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Analytics, Review, and Oversight
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: This AI use case identifies possible representative payee fraud and flags for review. This use case reduces representative payee fraud.
12_outputs: The system outputs numerical scores based on likelihood of representative payee misuse.
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 1/1/2009
19_date_acq_dev_began: 1/1/2009
20_date_implemented: 9/30/2023
22_dev_method: Developed in-house.
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Models used data from earnings and beneficiary 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: Age, Employment Status, Ability Status
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: No
45_compute_request: Yes
47_timely_resources: Other
47_question_type: We have not needed to allocate resources.
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.
51_extension_request: Yes – Agency requested an extension for this use case.
2_use_case_name: Continuing Disability Review Model
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Analytics, Review, and Oversight
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: This AI use case identifies disability cases with the greatest likelihood of medical improvement and flag them for a continuing disability review to improve the accuracy of CDRs.
12_outputs: The system outputs numerical scores for each disability case: the score represents the likelihood of medical improvements. The probabilities are binned according to low, medium, or high. 
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 1/1/1993
19_date_acq_dev_began: 1/1/1993
20_date_implemented: 9/30/2018
22_dev_method: Developed in-house.
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Model used data from disability program data sets
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: Age, Ability Status
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Other
47_question_type: We have not needed to provision resources.
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.
51_extension_request: Yes – Agency requested an extension for this use case.
2_use_case_name: Social Security Income Redetermination Model
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Analytics, Review, and Oversight
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: This AI use case identifies SSI overpayment cases that have highest expected overpayments for review. This use case contains excess overpayments by prioritizing technician review
12_outputs: The system outputs numerical scores for individuals, comprised of likelihood and amount of overpayment. 
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 1/1/1995
19_date_acq_dev_began: 1/1/1995
20_date_implemented: 9/9/2024
22_dev_method: Developed in-house.
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Model used data from disability program data sets
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: Wages (Employment Status)
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Other
47_question_type: We have not needed to provision resources.
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.
51_extension_request: Yes – Agency requested an extension for this use case.
2_use_case_name: Proactive Triage and Analysis of Hearings (PATH)
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Analytics, Review, and Oversight
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: This AI use case flags high likelihood favorable claims and refers them to human adjudicators for further review to determine eligibility for on-the-record hearing decisions.
12_outputs: The system outputs sorted case listings based on likelihood of favorable hearing decision.
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 1/1/2018
19_date_acq_dev_began: 1/1/2018
20_date_implemented: 11/1/2024
22_dev_method: Developed in-house.
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Model used data from disability program data sets
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: Age
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: No
45_compute_request: Yes
47_timely_resources: Other
47_question_type: We have not needed to provision resources.
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.
51_extension_request: Yes – Agency requested an extension for this use case.
2_use_case_name: Quick Disability Determinations Model
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Retirement and Disability Policy
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: Used to screen initial applications to identify cases where a favorable disability determination is highly likely and medical evidence is readily available to prioritize this workload and expedite case processing. 
12_outputs:  System output consists of probability model scores for each separate scoring service, Scoring Service for Allowance and Scoring Service for Processing Time, and the overall QDD Score.  
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 9/25/2003
19_date_acq_dev_began: 9/15/2004
20_date_implemented: 2/1/2008
22_dev_method: Developed with contracting resources.
23_contract_piids: SS0004400360001
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Model used data from disability program data sets
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: Sex, gender, & age
37_custom_code: Yes
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: eDIB (electronic disability)
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: 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.
51_extension_request: Yes – Agency requested an extension for this use case.
2_use_case_name: Mobile Wage Reporting (MOBWR) 
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of the Chief Information Officer
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: Inputting large amounts of data from paper forms into a digital system using AI.
11_purpose_benefits: Uses AI to extract text/data from scanned images/documents representing pay stubs or payroll information to enable faster processing.
12_outputs: Gross pay and pay date from the paystub image
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 11/4/2020
19_date_acq_dev_began: 3/1/2021
20_date_implemented: 5/14/2022
22_dev_method: Developed with contracting resources.
23_contract_piids: 6801, 10128, 10191, 10325
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: No
33_agency_data: No Agency data used for training
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. 
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Supplemental Security Income Record Maintenance System (SSIRMS)
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 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: SSA 800# Public Question & Answer Bot
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Transformation
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: The bot answers caller’s questions using approved FAQs found on SSA.GOV. Support is provided in both English and Spanish. 

Calls answered solely by the bot reduce the wait for other callers needing agent service.
12_outputs: Returns the answer snippet content for the applicable FAQ topic that should contain the same language as if the askers were to navigate to the FAQs webpage themselves on ssa.gov.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 2/13/2023
19_date_acq_dev_began: 4/3/2023
20_date_implemented: 6/5/2023
22_dev_method: Developed with contracting resources.
24_hisp_support: Yes
25_hisp_name: Social Security Administration - SSA
26_public_service: Filing for Social Security retirement benefits
27_public_info: Yes
28_iqa_compliance: N/A - Information Correction actions are not supported.
29_contains_pii: No
30_saop_review: No
31_data_catalog: Yes
33_agency_data: The ssa.gov FAQs webpage content is exported to be sourced by the FAQ Question & Answer bot.
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.
37_custom_code: Yes
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Enterprise Contact Center
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 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: 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: Generative AI for Analytic Insights
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of Analytics, Review, and Oversight
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: None of the above.
11_purpose_benefits: Generative AI model to analyze SSA's National 800 Number transcripts to provide insights into caller intent, call resolution, and call topics. These insights could highlight pain points in SSA’s policies and processes and focus efforts to improve customer service, deflect callers whose business cannot be resolved using the 800 Number, and ultimately decrease wait times.
12_outputs: Varies by use case
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 10/1/2022
19_date_acq_dev_began: 10/1/2022
20_date_implemented: 9/30/2023
22_dev_method: Developed with contracting resources.
24_hisp_support: Yes
25_hisp_name: Social Security Administration – SSA 
26_public_service: Obtaining audit disability benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: No
33_agency_data: No Agency data used for training
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. 
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: *** Provisional ATO in progress
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: 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: PolicyNet Plain Language Search Engine
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of the Chief Information Officer
8_topic_area: Government Services (includes Benefits and Service Delivery)
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: Search will employ learning to rank functionality based on user entered thumbs up/thumbs down data (data capture began in FY24 - learning to rank will be implemented in FY25).  Users across all internal SSA components and offices may use the system to find relevant information on SSA policies, procedures or instructions. Learning to rank will help users find relevant results faster, which supports better customer service. 

12_outputs: Based on the user thumbs up/thumbs down selections, search results will be ranked higher (or lower) within the results output.  
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 3/1/2024
19_date_acq_dev_began: 8/19/2024
20_date_implemented: 9/21/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: ITSSC
24_hisp_support: Yes
25_hisp_name: Social Security Administration - SSA
26_public_service: Filing for Social Security retirement benefits
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: No
33_agency_data: Model used disability program regulations and user provided 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.
37_custom_code: Yes
38_code_access: Yes – source code is publicly available.
39_code_link: https://solr.apache.org/
40_has_ato: Yes
41_system_name: 21st Century PolicyNet 
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: Speech to Text Video Transcription
3_agency: Social Security Administration
3_abr: SSA
4_bureau: Office of the Chief Information Officer
8_topic_area: Mission-Enabling
10_commercial_ai: Transcribing and summarizing a recorded meeting or interview using AI.
11_purpose_benefits: Generate transcript from recorded audio of disability hearings
12_outputs: Transcript
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 10/1/2023
19_date_acq_dev_began: 10/1/2023
20_date_implemented: 5/6/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: Microsoft/Accenture
24_hisp_support: Yes
25_hisp_name: Social Security Administration - SSA
26_public_service: Filing for Social Security retirement benefits
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: No
33_agency_data: No Agency data used for training
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. 
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Hearing Recording and Transcription
43_infra_provisioned: Yes
45_compute_request: Other
45_question_type: Model is SaaS 
47_timely_resources: Other
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.