Course Outline

Foundations of Responsible AI

  • An overview of responsible AI and its significance in software development for government.
  • Key principles: fairness, accountability, transparency, and privacy.
  • Case studies highlighting ethical failures and misuse of AI in codebases.

Bias and Fairness in AI-Generated Code

  • How large language models (LLMs) can perpetuate bias through training data for government applications.
  • Methods for detecting and addressing biased or unsafe code suggestions in government systems.
  • The phenomenon of AI hallucination and the associated risk of introducing errors at scale in public sector operations.

Licensing, Attribution, and IP Considerations

  • Understanding open-source licenses such as MIT, GPL, and Copyleft for government use.
  • Determining whether LLM-generated outputs require attribution in government projects.
  • Strategies for auditing AI-assisted code to ensure compliance with third-party licensing requirements for government.

Security and Compliance in AI-Assisted Development

  • Best practices for ensuring code safety and avoiding insecure patterns generated by LLMs in government systems.
  • Adhering to internal security guidelines and industry regulations for government software development.
  • Maintaining auditable documentation of AI-assisted decision-making processes for government oversight.

Policy and Governance for Development Teams

  • Developing internal AI usage policies tailored to software teams in the public sector.
  • Defining acceptable use parameters and identifying potential red flags in AI-assisted development for government.
  • Guidelines for selecting appropriate tools and responsibly onboarding AI assistants within government agencies.

Evaluating and Auditing AI Output

  • Utilizing checklists to assess the trustworthiness of generated content in government applications.
  • Conducting both manual and automated reviews of AI-generated code for government projects.
  • Best practices for peer-review and sign-off processes in government software development.

Summary and Next Steps

Requirements

  • Fundamental knowledge of software development processes
  • Experience with Agile, DevOps, or other software project methodologies

Audience for Government

  • Compliance teams
  • Developers
  • Software project managers
 7 Hours

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