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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
Testimonials (1)
Lecturer's knowledge in advanced usage of copilot & Sufficient and efficient practical session