Ken and I discuss open-endedness, the pursuit of ambitious goals by seeking novelty and interesting products instead of advancing directly toward defined objectives. We talk about evolution as a prime example of an open-ended system that has produced astounding organisms, Ken relates how open-endedness could help advance artificial intelligence and neuroscience, and we discuss a range of topics related to the general concept of open-endedness, and Ken takes a couple questions from Stefan Leijnen and Melanie Mitchell.

Related:

• Ken's website.
• Twitter: @kenneth0stanley.
• The book:
  • Why Greatness Cannot Be Planned: The Myth of the Objective by Kenneth Stanley and Joel Lehman.
• Papers:
  • Evolving Neural Networks Through Augmenting Topologies (2002)
  • Minimal Criterion Coevolution: A New Approach to Open-Ended Search

Some key take-aways:

• Many of the best inventions were not the result of trying to achieve a specific objective.
• Open-endedness is the pursuit of ambitious advances without a clearly defined objective.
• Evolution is a quintessential example of an open-ended process: it produces a vast array of complex beings by searching the space of possible organisms, constrained by the environment, survival, and reproduction.
• Perhaps the key to developing artificial general intelligence is by following an open-ended path rather that pursing objectives (solving the same old benchmark tasks, etc.).

0:00 - Intro 3:46 - Skip Intro 4:30 - Evolution as an Open-ended process 8:25 - Why Greatness Cannot Be Planned 20:46 - Open-endedness in AI 29:35 - Constraints vs. objectives 36:26 - The adjacent possible 41:22 - Serendipity 44:33 - Stefan Leijnen question 53:11 - Melanie Mitchell question 1:00:32 - Efficiency 1:02:13 - Gentle Earth 1:05:25 - Learning vs. evolution 1:10:53 - AGI 1:14:06 - Neuroscience, AI, and open-endedness 1:26:06 - Open AI