Artificial Intelligence continues to penetrate our lives. As it does so, we should be wary of its ethical and social implications.
Osonde Osoba, an engineer at the RAND Corporation and a professor at the Pardee RAND Graduate School, joins Sheana Ahlqvist in today’s episode of Innovation For All Podcast to talk about fairness in Artificial Intelligence and Machine Learning. AI has the ability to seriously impact our lives, which is why Osonde is pushing for systems that are accurate, unbiased, and flexible.
Discover what areas we should be wary when handing over the decision-making to AI’s, why this isn’t just a technical issue, but also political, and who should we put in charge of these systems. Learn also the importance of accountability, ethics, privacy, and regulation in AI systems.
IN THIS EPISODE YOU’LL LEARN:
- The difference between Machine Learning and Artificial Intelligence
- Should AI systems intentionally be made to ‘align with our comfort’?
- What roles do the legislators, policy makers, etc. do?
- Strategies to protect Data Privacy in AI and ML models
- Regulatory rules between the developers and the users
- If technology changes so rapidly, how can regulators keep up?
- How can we build accountability into AI & ML?
- Osonde Osoba’s TEDx Talk: Making AI Fair
- RAND Corporation
- Fairness, Accountability, and Transparency in Machine Learning (FAT/ML)
- Fairness and Machine Learning by Solon Barocas, Moritz Hardt & Arvind Narayanan
- Pareto Principle
- Bell Curve
- Trolley Problem
- AI Fairness 360
- Jutta Trevarinus
- Steven Pinker
- Luciano Floridi
- Joanna Bryson
CONNECT WITH OSONDE