As AI capabilities grow, the field faces a choice in how to define success. We argue that the primary objective of AI research should be Human Amplification -- aiming for systems that augment human abilities and preserve human agency. While the current focus on intelligent agents drives significant progress, treating replication of human agency as the ultimate metric of success emphasizes delegation over augmentation. We discuss how this presents distinct challenges regarding control and power d…
Read moreAs AI capabilities grow, the field faces a choice in how to define success. We argue that the primary objective of AI research should be Human Amplification -- aiming for systems that augment human abilities and preserve human agency. While the current focus on intelligent agents drives significant progress, treating replication of human agency as the ultimate metric of success emphasizes delegation over augmentation. We discuss how this presents distinct challenges regarding control and power dynamics. By contrast, anchoring AI development in the service of human agency opens up a much broader design space that blurs the distinction between non-agentic tools and sophisticated delegates. This shift directs research toward cognitive extensions that ideally spark a virtuous cycle of recursive human amplification, where advances in AI further empower us to build safer and more beneficial systems.
