Foundations of Responsible AI (2022)
2h 31mIntermediate2022-08-02
Authors

Ayodele Odubela
Data Scientist and AI Ethicist
Course details
How well do you understand the issues around algorithmic bias and unfairness? In this course, data scientist and AI ethicist Ayodele Odubela teaches you the principles of responsible AI, as well as the frameworks necessary to apply RAI techniques in AI systems. Ayodele explains modern AI development and problems in machine learning (ML) that differ from software engineering. She discusses big data and where it comes from, then covers several important points of data awareness and literacy. Ayodele goes over ethical frameworks, consequence scanning, fairness, accountability, and more. She also explains fairness-related harms, why they arise, why they matter, and what you can to avoid or mitigate them. Plus, Ayodele offers a detailed description of human rights as related to AI.
Skills covered
Responsible AIArtificial Intelligence FoundationsFoundationsArtificial Intelligence (AI)
Concepts
Introduction
- Understanding responsible AI
Philosophy of AI
- What is AI and how does data enable it
- Modern AI development
- Problems in ML that differ from software engineering
Data Awareness and Literacy
- Big data and where it comes from
- Seeing trends in data
- Building data understanding
- Visualization and comparing data
- Storytelling with data
Ethical Theories
- Introduction to ethical AI
- Ethical frameworks
- Beneficence vs. maleficence
- Calculating consequences
- Consequence scanning
- Common good and equity
Responsible AI Principles
- Fairness
- Transparency
- Accountability
- Explanations
- Interpretability
- Inclusivity
Algorithmic Harm
- Why fairness related harms
- Critical AI incidents and learnings
- Bias in the design and development lifecycle
- Causal reasoning and fairness
- Risk mitigation in AI
- Technical aspects of sociotechnical solutions
Human Rights and AI
- Anonymity and data privacy
- Unintended uses and misuses
- Unethical business cases
- Autonomous systems and society
- Who AI is developed for
Conclusion
- AI regulation and applying responsible AI frameworks