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Interviewing Arvind Narayanan on making sense of AI hype
Oct 17, 2024
Arvind Narayanan, a computer science professor at Princeton and director of the Center for Information Technology Policy, delves into the realities of AI amidst the hype. He discusses the pitfalls of AI policy, emphasizing the need for harm-focused research. The conversation covers the risks of open-source foundation models, critiques of traditional AI in risk prediction, and the implications of scaling laws. Narayanan also sheds light on the balance between innovation and societal impact, highlighting the necessary collaboration between researchers and policymakers.
54:21
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Quick takeaways
- The podcast emphasizes the importance of a proactive approach in addressing potential harms from AI to ensure societal benefits are realized.
- Discussions highlight challenges in AI policy, particularly in distinguishing between generative and traditional predictive AI to inform effective regulation.
Deep dives
Optimism Amid Criticism
Despite being labeled as an AI critic, the speaker expresses a profound optimism about technology, particularly in the realm of artificial intelligence. They emphasize that some AI applications, like foundation models and generative AI, have significant potential for positive societal impacts in the long run. However, they underscore the need for researchers and technologists to proactively address the potential harms posed by these technologies rather than simply reacting to them. This proactive stance is seen as essential for guiding policy and ensuring that the benefits of AI are realized while minimizing possible negative consequences.
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Discover
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