About the Project
This toolkit provides practical frameworks, assessment checklists, and real-world case studies, plus a minimal prototype to help engineering teams evaluate and govern AI systems. It translates ethics into actionable practices that integrate into the software lifecycle, moving beyond theory to deliver tangible outcomes.
Key Resources
Ethics Framework
Principles and structured guidance to evaluate ethical impact across the AI lifecycle.
Responsibility Guidelines
Clear ownership and accountability practices for AI-driven systems.
Assessment Checklist
Practical audit checklist for ethical and responsible AI compliance.
Case Studies
Real-world scenarios mapping ethical risks to mitigation strategies, governance controls, and practical case analyses.
Policy Checker Demo
Live prototype demonstrating automated policy compliance checks using your policy definitions.
Policy Checker (Python)
Minimal reference implementation for JSON-based policy checks.
Ethical AI Flow
How to Use in Practice
- Start with the Ethics Framework to identify relevant risk dimensions.
- Apply the Assessment Checklist during design and review phases.
- Use the Policy Checker prototype to validate governance rules.
- Reference case studies when defining mitigation strategies.
Academic Context
This project was developed in an academic context to explore how ethical and responsible AI principles can be operationalized within software engineering practices. It aligns with contemporary discussions on AI governance, accountability and transparency, emphasizing the role of engineers in identifying risks, implementing safeguards and continuously monitoring AI-driven systems throughout their lifecycle.