What does it mean to create beneficial artificial intelligence? How can we expect to align AIs with human values if humans can't even agree on what we value? Building safe and beneficial AI involves tricky technical research problems, but it also requires input from philosophers, ethicists, and psychologists on these fundamental questions. How can we ensure the most effective collaboration? Ariel spoke with FLI's Meia Chita-Tegmark and Lucas Perry on this month's podcast about the value alignment problem: the challenge of aligning the goals and actions of AI systems with the goals and intentions of humans.
Anthony Aguirre of the Future of Life Institute discusses A Better Path for AI, arguing against races to replace people and for purpose-built AI tools with human control, guardrails, accountability, and international cooperation.
Charlie Bullock discusses radical optionality, a framework for governing advanced AI under uncertainty. The episode covers transparency, evaluations, cybersecurity, technical hiring, and tensions between private and government oversight.
Peter Wildeford discusses methods for forecasting AI progress and why he sees AI as neither a bubble nor a normal technology, covering economic effects, national security, cyber capabilities, robotics, export controls, and prediction markets.
