2_use_case_name: AWS Captcha Solver
3_agency: General Services Administration
3_abr: GSA
4_bureau: GSA IT (IDT)
8_topic_area: Other
8_question_type: AWS Captcha Solver
10_commercial_ai: None of the above.
11_purpose_benefits: As part of a project to automate actions in AWS console using Selenium, we developed an AI model that can solve AWS's captcha so our automated system won't be blocked for being detected as a bot. The model is used in an AWS Lambda that uses a headless Selenium driver. The model was trained from scratch using Tensorflow. We have discussed making a more general form of this solution that could be applied to other AI/ML problems.
12_outputs: It outputs the solution to a captcha.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 1/1/2022
19_date_acq_dev_began: 1/1/2022
20_date_implemented: 1/1/2022
22_dev_method: Developed in-house.
24_hisp_support: No
25_hisp_name: Public Experience Portfolio – GSA 
26_public_service: Enable increased self-service through an expansion of digital costumer service tools
27_public_info: No
28_iqa_compliance: Non-public
29_contains_pii: No
30_saop_review: No
31_data_catalog: Yes
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.
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
39_code_link: The source is in GSA's GitHub repository.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: No
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.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: No
53_real_world_testing: Benchmark evaluation: Testing of the AI model has involved the use of benchmarks (either publicly available or internally created) to estimate performance in real-world settings, but has not been tested in an operational environment. 
55_independent_eval: Planned or in-progress
56_monitor_postdeploy: No monitoring protocols have been established: Necessary infrastructure needed to perform monitoring of AI systems in production is not available and/or a plan to monitor models has not yet been established.
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Other 
59_question_type: Was used internally for root password rotation only. No external users.
61_adverse_impact: No
63_stakeholder_consult: None of the above
65_appeal_process: No – Law, operational limitations, or governmentwide guidance precludes an opportunity for an individual to appeal.
66_no_appeal_reason: Law, operational limitations, or governmentwide guidance precludes an opportunity for an individual to appeal.
67_opt_out: No – This AI use case is not subject to the opt-out requirement because the AI functionality is solely used for the prevention, detection, and investigation of fraud or cybersecurity incidents, or the conduct of a criminal investigation.