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Duration 7 hours
Course Outline
The Foundations of Responsible AI
- Defining responsible AI and its significance in software development
- Core principles: fairness, accountability, transparency, and privacy
- Case studies of ethical failures and AI misuse in codebases
Bias and Fairness in AI-Generated Code
- How LLMs may perpetuate bias derived from training data
- Techniques for detecting and remediating biased or unsafe code suggestions
- Addressing AI hallucination and the potential for large-scale error introduction
Licensing, Attribution, and IP Implications
- Interpretation of open-source licenses (MIT, GPL, Copyleft)
- Determining if LLM-generated outputs necessitate attribution
- Reviewing AI-assisted code for third-party licensing conflicts
Security and Compliance in AI-Assisted Development
- Verifying code safety and preventing insecure patterns generated by LLMs
- Adhering to internal security protocols and industry regulations
- Maintaining auditable records of AI-assisted decision-making
Policy and Governance for Development Teams
- Formulating internal AI usage policies for software teams
- Outlining acceptable use cases and identifying red flags
- Selecting tools and onboarding AI assistants responsibly
Evaluating and Auditing AI Output
- Applying checklists to verify the reliability of generated content
- Performing manual and automated reviews of AI-generated code
- Best practices for peer review and approval workflows
Summary and Next Steps
Requirements
- A fundamental grasp of software development workflows
- Familiarity with Agile, DevOps, or standard software project methodologies
Target Audience
- Compliance teams
- Developers
- Software project managers
Testimonials (2)
The session was highly interactive and applicable to the business.
Jorge Boscan - Chevron Global Technology Services Company
Course - Advanced GitHub Copilot & AI for Projects and Infrastructure
Machine Translated
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
