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Duration 7 hours
Course Outline
Core Principles of Ethical AI
- Defining responsible AI and its significance within the software engineering domain
- Core pillars: fairness, accountability, transparency, and data privacy
- Case studies highlighting ethical lapses and misuse of AI in codebases
Addressing Bias and Fairness in AI-Generated Code
- How Large Language Models (LLMs) may propagate biases derived from training datasets
- Strategies for identifying and correcting biased or unsafe code suggestions
- Mitigating the risks of AI hallucinations and large-scale error introduction
Licensing, Attribution, and Intellectual Property
- Navigating open-source license types (MIT, GPL, Copyleft)
- Determining the need for attribution in LLM-generated outputs
- Performing audits on AI-assisted code to identify third-party licensing conflicts
Security and Regulatory Compliance in AI-Assisted Workflows
- Safeguarding code integrity by avoiding insecure patterns suggested by LLMs
- Adhering to internal security standards and broader industry regulations
- Maintaining auditable records of decision-making processes involving AI
Governance and Policy Formulation for Development Teams
- Drafting internal guidelines for AI usage within software teams
- Establishing clear acceptable use boundaries and identifying warning signs
- Selecting appropriate tools and responsibly onboarding AI assistants
Assessment and Audit of AI Outputs
- Utilizing structured checklists to evaluate the reliability of generated content
- Executing both manual and automated reviews of AI-written code
- Adopting best practices for peer review and approval processes
Recap and Future Directions
Requirements
- Foundational knowledge of standard software development workflows
- Working familiarity with Agile, DevOps, or general software project methodologies
Target Audience
- Compliance officers and teams
- Software developers
- Project managers in software engineering
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
