Ken Stanley

Today, most machine learning algorithms use the same paradigm: set an objective, and train an agent, a neural net, or a classical model to perform well against that objective. That approach has given good results: these types of AI can hear, speak, write, read, draw, drive and more. But they’re also inherently limited: because they optimize for objectives that seem interesting to humans, they often avoid regions of parameter space that are valuable, but that don’t immediately seem interesting to human beings, or the objective functions we set. That poses a challenge for researchers like Ken Stanley, whose goal is to build broadly superintelligent AIs — intelligent systems that outperform humans at a wide range of tasks. Among other things, Ken is a former startup founder and AI researcher, whose career has included work in academia, at UberAI labs, and most recently at OpenAI, where he leads the open-ended learning team. Ken joined me to talk about his 2015 book Greatness Cannot Be Planned: The Myth of the Objective, what open-endedness could mean for humanity, the future of intelligence, and even AI safety on this episode of the TDS podcast.

Julian Togelius, an NYU Associate Professor and co-founder of model.ai, teams up with Ken Stanley from OpenAI, who leads research on open-endedness. The duo dives into the intersection of AI and games, emphasizing how games serve as a testing ground for AGI. They discuss the need for diversity in AI, tackling challenges in integrating different learning approaches. The conversation also touches on the balance between creativity and technology, and the philosophical debates shaping AI's future.

Prof. Ken Stanley, a pioneer in the study of open-endedness and author of 'Why Greatness Cannot Be Planned,' challenges conventional goal-setting. He argues that rigid objectives often stifle creativity, advocating for a focus on subjectivity and serendipity. The discussion spans artificial intelligence's link to art, the deceptive nature of ambitious objectives, and the unexpected paths innovation can take. By embracing uncertainty, Stanley posits that we can unlock profound creative insights and truly understand the interplay between intelligence and artistic expression.