2_use_case_name: Credential Authentication Technology with Camera System (CAT-2) and AutoCAT (CAT-2 in an e-gate form factor)
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: TSA
8_topic_area: Transportation
10_commercial_ai: None of the above.
11_purpose_benefits: The Transportation Security Administration (TSA) uses AI-based, one-to-one (1:1) facial matching technologies at some checkpoints to assist human reviewers with traveler identity verification. The purpose and expected benefits of the technology include increased speed and accuracy of identity verification at the checkpoint while improving detection of imposters.
12_outputs: The system produces an recommendation to the Transportation Security Officer (TSO) to indicate if person presenting the identity document is similar to the face on the photo ID document.  In the event of a non-match, the TSO is responsible for additional identity verification steps to verify the identity of the traveler.
16_dev_stage: Operation and Maintenance
17_impact_type: Rights-Impacting

18_date_initiated: 1/1/2022
19_date_acq_dev_began: 7/1/2023
20_date_implemented: 9/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 70T04023D7672N0001
24_hisp_support: Yes
25_hisp_name: Transportation Security Administration – DHS 
26_public_service: Completing TSA passenger screening
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: No
33_agency_data: N/A - The Agency does not own any of the data used to train, fine-tune, and/or evaluate performance of the model(s) 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.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: STIP/CAT
42_dev_tools_wait: 6-12 months
43_infra_provisioned: No
45_compute_request: No
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: 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.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: Yes
53_real_world_testing: Impact evaluation in operational environment: The AI use case has been tested in an operational environment before being fully implemented as a solution and has utilized randomized experiments with a control group or other counterfactual, social systems analysis, or other rigorous research methodologies to evaluate impact and identify potential harm to users as well as broader groups of people.
54_key_risks: In the event of a non-match, the traveler may make a second attempt or TSA may perform additional identity verification steps to verify the identity of the traveler. This process may add between 20 seconds or a few minutes to the identity verification and security screening process. This is mitigated through T&E and continuous monitoring.  
55_independent_eval: Yes – by the CAIO
56_monitor_postdeploy: Automated and Regularly Scheduled Updates: Some aspects of the plan to monitor the AI system post-deployment are automated including re-training of models after detecting drift; however, data science teams are still significantly involved in the monitoring and re-deployment process.
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Online - in the terms or instructions for the service.,In-person,Other
59_question_type: TSA Website
61_adverse_impact: No
62_disparity_mitigation: Test and Evaluation and continuous monitoring.
63_stakeholder_consult: Direct user testing
65_appeal_process: Yes
67_opt_out: Yes