Join Barton Poulson for an in-depth discussion in this video Seeing the wrong thing, part of AI Accountability Essential Training.
- [Instructor] In 2017, a deep learning project claimed…to be able to predict a person's sexuality…from a profile photo.…They were able to do this…with a certain amount of precision,…higher than chance, and the researchers attributed this…to the affect of prenatal hormones…on facial morphology, among other attributes.…Not surprisingly, this study raised a huge number…of social and ethical red flags,…but one of the most interesting was a critique…in which secondary research found…that non-physical attributes,…like the use of makeup for women,…the presence of facial hair for men,…wearing glasses, or the angle…at which people took their selfies,…those were predictive of a person's sexuality…with no need for a biological explanation.…
The point of this is that, while it may be possible…to get some clue as to a person's sexuality…from looking at a photo, and the AI is able to do that,…it's really important to be careful…about interpreting what's going on,…and saying what it is that they AI is reacting to,…'cause it might be something entirely different…
- 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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