Join Barton Poulson for an in-depth discussion in this video Justice and AI, part of AI Accountability Essential Training.
- [Instructor] I previously talked about…three different forms of justice…and I want to show how they relate to artificial intelligence.…We'll start with the first one,…distributive justice and AI.…And what distributive justice is looking at…is how fair is the allocation.…When a person finally gets this much money…or this much money, how happy are they?…And the AI algorithm allocates money,…time, attention, access or any other limited resource…to various people.…Now in most situations the default approach…is proportional equity.…
That a person gets something in proportion…to what goes into it.…And that makes a lot of sense,…it seems like a very rational thing…but distributing by equality is a different…but valid model where everybody gets exactly…the same amount.…And need is a third option,…where people get what they need regardless…of what they put in.…And so these are different competing methods…for determining whether an allocation is fair…or appropriate.…And so while equity is usually taken as the quote,…best or most efficient approach to distribution…
- Bias in AI
- Navigating the social challenges of AI
- Moral reasoning and relational ethics
- General Data Protection Regulation (GDPR) and AI
- Discrimination in data
- Liability and AI
- AI in life-and-death situations
- Confronting the challenges of AI as a developer, executive, and consumer
Skill Level Intermediate
1. The Context for AI
2. Technical Challenges of AI
3. Social Challenges of AI
4. Legal Challenges of AI
5. Safety Challenges of AI
AI in the military4m 36s
6. Confronting the Challenges of AI
Next steps2m 52s
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