Kenneth Stanley, an influential artificial intelligence researcher and author, discusses the pitfalls of setting rigid objectives in this engaging conversation. He argues that over-fixation on ambitions can stifle true progress and innovation. Stanley emphasizes the importance of modest goals and the serendipity of unexpected discoveries that can lead to breakthroughs. He also critiques traditional peer review processes, advocating for a restructured approach that encourages creativity. Ultimately, he promotes a mindset that values experimentation and adaptability over conventional achievements.

Kenneth Stanley, a Professor in Computer Science and neuroevolution pioneer, challenges conventional goal-setting in his insightful discussion. He argues that rigid objectives may hinder true innovation and stresses the importance of embracing unexpected opportunities. The conversation highlights how serendipity fuels creativity, showcasing examples like Picbreeder's individual creativity versus consensus voting. Stanley emphasizes exploration, courage, and gratitude in fostering innovation, advocating for a mindset that prioritizes curiosity over strict goals.

Discover how Professor Kenneth Stanley created a unique social network focused on interests rather than popularity, inspired by his book 'Why greatness cannot be planned'. Explore the philosophy and technology behind the Serendipity network, challenging traditional optimization systems and promoting creativity through dynamic interest discovery. Dive into the paradox of setting objectives in AI research and the complexity of human intelligence contrasted with AI models. Learn about cultivating serendipity, fostering genuine interactions, and balancing user engagement in social networking design.

Professor Kenneth Stanley is currently a research science manager at OpenAI in San Fransisco. We've Been dreaming about getting Kenneth on the show since the very begininning of Machine Learning Street Talk. Some of you might recall that our first ever show was on the enhanced POET paper, of course Kenneth had his hands all over it. He's been cited over 16000 times, his most popular paper with over 3K citations was the NEAT algorithm. His interests are neuroevolution, open-endedness, NNs, artificial life, and AI. He invented the concept of novelty search with no clearly defined objective. His key idea is that there is a tyranny of objectives prevailing in every aspect of our lives, society and indeed our algorithms. Crucially, these objectives produce convergent behaviour and thinking and distract us from discovering stepping stones which will lead to greatness. He thinks that this monotonic objective obsession, this idea that we need to continue to improve benchmarks every year is dangerous. He wrote about this in detail in his recent book "greatness can not be planned" which will be the main topic of discussion in the show. We also cover his ideas on open endedness in machine learning.  00:00:00 Intro to Kenneth  00:01:16 Show structure disclaimer  00:04:16 Passionate discussion  00:06:26 WHy greatness cant be planned and the tyranny of objectives  00:14:40 Chinese Finger Trap   00:16:28 Perverse Incentives and feedback loops  00:18:17 Deception  00:23:29 Maze example  00:24:44 How can we define curiosity or interestingness  00:26:59 Open endedness  00:33:01 ICML 2019 and Yannic, POET, first MSLST  00:36:17 evolutionary algorithms++  00:43:18 POET, the first MLST   00:45:39 A lesson to GOFAI people  00:48:46 Machine Learning -- the great stagnation  00:54:34 Actual scientific successes are usually luck, and against the odds -- Biontech  00:56:21 Picbreeder and NEAT  01:10:47 How Tim applies these ideas to his life and why he runs MLST  01:14:58 Keith Skit about UCF  01:15:13 Main show kick off  01:18:02 Why does Kenneth value serindipitous exploration so much  01:24:10 Scientific support for Keneths ideas in normal life  01:27:12 We should drop objectives to achieve them. An oxymoron?  01:33:13 Isnt this just resource allocation between exploration and exploitation?  01:39:06 Are objectives merely a matter of degree?  01:42:38 How do we allocate funds for treasure hunting in society  01:47:34 A keen nose for what is interesting, and voting can be dangerous  01:53:00 Committees are the antithesis of innovation  01:56:21 Does Kenneth apply these ideas to his real life?  01:59:48 Divergence vs interestingness vs novelty vs complexity  02:08:13 Picbreeder  02:12:39 Isnt everything novel in some sense?  02:16:35 Imagine if there was no selection pressure?  02:18:31 Is innovation == environment exploitation?  02:20:37 Is it possible to take shortcuts if you already knew what the innovations were?  02:21:11 Go Explore -- does the algorithm encode the stepping stones?  02:24:41 What does it mean for things to be interestingly different?  02:26:11 behavioral characterization / diversity measure to your broad interests  02:30:54 Shaping objectives  02:32:49 Why do all ambitious objectives have deception? Picbreeder analogy  02:35:59 Exploration vs Exploitation, Science vs Engineering  02:43:18 Schools of thought in ML and could search lead to AGI  02:45:49 Official ending 

Support us! https://www.patreon.com/mlst   MLST Discord: https://discord.gg/aNPkGUQtc5 We are honoured to welcome Dr. Joel Lehman, an eminent machine learning research scientist, whose work in AI safety, reinforcement learning, creative open-ended search algorithms, and indeed the philosophy of open-endedness and abandoning objectives has paved the way for innovative ideas that challenge our preconceptions and inspire new visions for the future. Dr. Lehman's thought-provoking book, "Why Greatness Cannot Be Planned" penned with with our MLST favourite Professor Kenneth Stanley has left an indelible mark on the field and profoundly impacted the way we view innovation and the serendipitous nature of discovery. Those of you who haven't watched our special edition show on that, should do so at your earliest convenience! Building upon this foundation, Dr. Lehman has ventured into the domain of AI systems that embody principles of love, care, responsibility, respect, and knowledge, drawing from the works of Maslow, Erich Fromm, and positive psychology. YT version: https://youtu.be/23-TXgJEv-Q http://joellehman.com/ https://twitter.com/joelbot3000 Interviewer: Dr. Tim Scarfe TOC: Intro [00:00:00] Model [00:04:26] Intro and Paper Intro [00:08:52] Subjectivity [00:16:07] Reflections on Greatness Book [00:19:30] Representing Subjectivity [00:29:24] Nagal's Bat [00:31:49] Abstraction [00:38:58] Love as Action Rather Than Feeling [00:42:58] Reontologisation [00:57:38] Self Help [01:04:15] Meditation [01:09:02] The Human Reward Function / Effective... [01:16:52] Machine Hate [01:28:32] Societal Harms [01:31:41] Lenses We Use Obscuring Reality [01:56:36] Meta Optimisation and Evolution [02:03:14] Conclusion [02:07:06] References: What Is It Like to Be a Bat? (Thomas Nagel) https://warwick.ac.uk/fac/cross_fac/iatl/study/ugmodules/humananimalstudies/lectures/32/nagel_bat.pdf Why Greatness Cannot Be Planned: The Myth of the Objective (Kenneth O. Stanley and Joel Lehman) https://link.springer.com/book/10.1007/978-3-319-15524-1  Machine Love (Joel Lehman) https://arxiv.org/abs/2302.09248  How effective altruists ignored risk (Carla Cremer) https://www.vox.com/future-perfect/23569519/effective-altrusim-sam-bankman-fried-will-macaskill-ea-risk-decentralization-philanthropy Philosophy tube - The Rich Have Their Own Ethics: Effective Altruism https://www.youtube.com/watch?v=Lm0vHQYKI-Y Abandoning Objectives: Evolution through the Search for Novelty Alone (Joel Lehman and Kenneth O. Stanley) https://www.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/lehman_ecj11.pdf