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In this episode of "A Beginner's Guide to AI," we delve into the intriguing and somewhat ominous concept of P(doom), the probability of catastrophic outcomes resulting from artificial intelligence. Join Professor GePhardT as he explores the origins, implications, and expert opinions surrounding this critical consideration in AI development.
We'll start by breaking down the term P(doom) and discussing how it has evolved from an inside joke among AI researchers to a serious topic of discussion. You'll learn about the various probabilities assigned by experts and the factors contributing to these predictions. Using a simple cake analogy, we'll simplify the concept to help you understand how complexity and lack of oversight in AI development can increase the risk of unintended and harmful outcomes.
In the second half of the episode, we'll examine a real-world case study focusing on Anthropic, an AI research organization dedicated to building reliable, interpretable, and steerable AI systems. We'll explore their approaches to mitigating AI risks and how a comprehensive strategy can significantly reduce the probability of catastrophic outcomes.
Want to get in contact? Write me an email: [email protected]
This podcast was generated with the help of ChatGPT and Mistral. We do fact check with human eyes, but there still might be hallucinations in the output. Please keep this in mind while listening and feel free to verify any information that you find particularly important or interesting.
Music credit: "Modern Situations" by Unicorn Heads
3
4242 ratings
In this episode of "A Beginner's Guide to AI," we delve into the intriguing and somewhat ominous concept of P(doom), the probability of catastrophic outcomes resulting from artificial intelligence. Join Professor GePhardT as he explores the origins, implications, and expert opinions surrounding this critical consideration in AI development.
We'll start by breaking down the term P(doom) and discussing how it has evolved from an inside joke among AI researchers to a serious topic of discussion. You'll learn about the various probabilities assigned by experts and the factors contributing to these predictions. Using a simple cake analogy, we'll simplify the concept to help you understand how complexity and lack of oversight in AI development can increase the risk of unintended and harmful outcomes.
In the second half of the episode, we'll examine a real-world case study focusing on Anthropic, an AI research organization dedicated to building reliable, interpretable, and steerable AI systems. We'll explore their approaches to mitigating AI risks and how a comprehensive strategy can significantly reduce the probability of catastrophic outcomes.
Want to get in contact? Write me an email: [email protected]
This podcast was generated with the help of ChatGPT and Mistral. We do fact check with human eyes, but there still might be hallucinations in the output. Please keep this in mind while listening and feel free to verify any information that you find particularly important or interesting.
Music credit: "Modern Situations" by Unicorn Heads
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