2_use_case_name: ChatCDC - CDC Enterprise Generative AI Chatbot (Software Development)
3_agency: Department of Health and Human Services
3_abr: HHS
4_bureau: CDC
8_topic_area: Mission-Enabling (internal agency support)
10_commercial_ai: None of the above.
11_purpose_benefits: CDC has an internal productivity tool available to all CDC staff which can be used in a variety of ways. This use case covers staff who will be using this general purpose to assist with the development of software code which can be used for research, data analysis, software development, or other such systems. Currently, CDC has internal Generative AI guidance determining how this tool can be used, and individual Centers, institutes, or Offices may implement their own policy to ensure safe and responsible AI. 

When the AI chatbot is being used for coding assistance or software development, it affects several business processes related to agency operations and core task structures. Specifically, it can be utilized by various personnel within an organization such as the CDC, including software programmers using AI-specific code, those involved in encoding for software development, data analysts, scientific researchers conducting data analysis, data scientists implementing and testing new models, and software engineers developing or updating applications.
The chatbot enhances productivity and efficiency across these roles by providing coding assistance and acting as a learning tool. For instance, data engineers may use the chatbot to generate PySpark code for their data transformation scripts within a larger pipeline. Additionally, individuals new to programming languages like Python can leverage the chatbot as a tutor to help them with tasks such as cleaning up datasets for evaluation purposes.
In summary, the AI chatbot impacts business processes by aiding staff members in performing complex analytical tasks more efficiently and supporting their development work through guided coding assistance. This ultimately contributes to enhancing overall operations within the agency by streamlining research activities and internal process workflows.
12_outputs: This chatbot, powered by Azure OpenAI Large Language Models, will generate responses to questions asked by the user, in this case about either some software code, software code documentation, code concepts, or to help generate software code. The chatbot's output can then be copied and pasted or manually entered into the appropriate testing process by the staff to ensure any code used from the chatbot's output meets the criteria of the current task.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 10/1/2023
19_date_acq_dev_began: 11/1/2023
20_date_implemented: 2/1/2024
21_date_retired:  
22_dev_method: Developed with both contracting and in-house resources.
24_hisp_support:  
25_hisp_name:  
26_public_service:  
27_public_info: No
28_iqa_compliance:  
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: Yes. A series of pilot projects was conducted to evaluate the performance of this chatbot and these pilot projects are included within this inventory.
34_data_docs: Documentation is widely available
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
39_code_link:  
40_has_ato: Yes
41_system_name: Enterprise Data Analytics and Visualization (EDAV) Platform
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.