Navigating the Uncertainties of AI Forecasting

On this episode, Daniel Kokotajlo joins me to discuss why artificial intelligence may surpass the transformative power of the Industrial Revolution, and just how much AI could accelerate AI research. We explore the implications of automated coding, the critical need for transparency in AI development, the prospect of AI-to-AI communication, and whether AI is an inherently risky technology. We end by discussing iterative forecasting and its role in anticipating AI's future trajectory.  

You can learn more about Daniel's work at: https://ai-2027.com and https://ai-futures.org  

Timestamps:  

00:00:00 Preview and intro 

00:00:50 Why AI will eclipse the Industrial Revolution  

00:09:48 How much can AI speed up AI research?  

00:16:13 Automated coding and diffusion 

00:27:37 Transparency in AI development  

00:34:52 Deploying AI internally  

00:40:24 Communication between AIs  

00:49:23 Is AI inherently risky? 

00:59:54 Iterative forecasting