The Need for Auditing AI Models and the Role of Third-Party Auditing

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This chapter discusses the importance of auditing AI models and the need for a thriving third-party auditing ecosystem and insurance ecosystem. It explores the risks of not ensuring robust and safe models and the incentives for labs to outsource auditing work. The chapter also addresses the challenges of determining standards for deployment and the role of government and open source in making decisions.

In this episode, Marius Hobbhahn, CEO of Apollo Research, sits down with Nathan Labenz to discuss Apollo’s research in AI deception, interpretability, and affordances. If you need an ecommerce platform, check out our sponsor Shopify: https://shopify.com/cognitive for a $1/month trial period.

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TIMESTAMPS:

(00:00:00) - Episode Preview

(00:05:40) - Understanding the Role of Apollo Research

(00:08:02) - The Evolution of AI Safety

(00:11:30) - Apollo’s Framework

(00:15:10) - Sponsors: Shopify

(00:16:49) - Understanding AI Affordances and Resulting Interactions in the World

(00:31:00) - Sponsors: Omneky

(00:39:00) - Interpretability and deceptive alignment

(00:45:55) - Why might deception arise in the first place?

(00:47:46) - Understanding deceptive alignment

(00:57:49) - New Architectures

(01:02:23) - Interpretability at deployment phase

(01:03:35) - Deception in AI | A Case Study

(01:09:03) - Deceptive AI Stock Trader

(01:18:51) - Impact of discouragement on unethical AI behaviour

(01:19:45) - Giving the AI a Reasoning Scratchpad and Impact on Deception

(01:21:06) - Double-edged sword of removing the scratchpad

(01:23:00) - Analyzing impact of model size on insider training

(01:28:00) - Challenges and necessity of 3rd Party Auditing

(01:31:00) - Role of government in regulation

(01:52:17) - How can individuals get involved in red teaming?

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