Ethical Machines A Crash Course on the AI Ethics Landscape
Apr 17, 2025
Dive into the intricate world of AI ethics, exploring the vital distinctions between 'AI for good' and 'AI for not bad.' Discover the challenges of bias and discrimination arising from flawed training data, and understand the implications of privacy concerns in AI. The conversation sheds light on managing ethical risks and the importance of balanced training to prevent biased outcomes. Plus, gain insights on automation bias and the necessity of ethical practices for beneficial AI technology.
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Two Faces of AI Ethics
- AI ethics divides into AI for good and AI for not bad.
- AI for good pursues ethical goals, while AI for not bad manages risks in business AI use.
Understand AI Ethics Content First
- AI risks come from its nature as software that learns by example.
- Solutions must address these inherent risks before jumping to mitigation structures.
Pepe the Dog AI Example
- AI that learns to recognize your dog needs many varied photos of Pepe.
- Without diverse examples, AI fails on new or different images.
