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Duration 7 hours
Course Outline
Core Principles of Responsible AI
- Defining responsible AI and its significance in software engineering.
- Key principles: equity, accountability, transparency, and data privacy.
- Case studies illustrating ethical lapses and misuse of AI in codebases.
Bias and Equity in AI-Generated Code
- Mechanisms by which LLMs may perpetuate bias derived from training data.
- Techniques for identifying and correcting biased or unsafe code suggestions.
- Addressing AI hallucinations and the potential for widespread errors.
Licensing, Attribution, and Intellectual Property Issues
- Navigating open-source licenses (including MIT, GPL, and Copyleft).
- Assessing whether LLM outputs necessitate specific attribution.
- Reviewing AI-assisted code for third-party licensing conflicts.
Security and Compliance in AI-Driven Development
- Prioritizing code safety and preventing insecure patterns from LLMs.
- Adhering to internal security protocols and external industry regulations.
- Maintaining auditable records of AI-influenced decision-making processes.
Governance and Policy for Development Teams
- Drafting internal AI usage guidelines for engineering teams.
- Establishing boundaries for acceptable use and identifying warning signs.
- Selecting tools and managing the responsible onboarding of AI assistants.
Assessment and Audit of AI Outputs
- Utilizing checklists to verify the reliability of generated content.
- Performing manual and automated inspections of AI-written code.
- Applying best practices for peer reviews and approval workflows.
Recap and Future Directions
Requirements
- A fundamental grasp of software development workflows.
- General familiarity with Agile, DevOps, or standard software project methodologies.
Target Audience
- Compliance departments.
- Software developers.
- Project managers overseeing software initiatives.
Testimonials (1)
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
