Show Notes
Chances are you’re listening to this on an advanced computer that fits in your pocket, but is really just one tentacle tip of a giant, planet-spanning architecture for the gathering and processing of data. A common sentiment among the smartphone-enabled human population is that we not only don’t own our data, but our data owns us — or, at least, the pressure of responsibility to keep providing data to the Internet and its devices (and the wider project of human knowledge construction) implicates us in the evolution of a vast, mysterious, largely ineffable self-organizing system that has grabbed the reins of our economies and cultures. This is, in some sense, hardly new: since humankind first started writing down our memories to pass them down through time, we have participated in the “dataome” — a structure and a process that transcends, and transforms, our individuality. Fast-forward to the modern era, when the rapidly-evolving aggregation of all human knowledge tips the scales in favor of the dataome’s emergent agency and its demands on us… Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe. This week on Complexity, we talk to Caleb Scharf, Director of Astrobiology at Columbia University, about his book, The Ascent of Information: Books, Bits, Genes, and LIfe’s Unending Algorithm. In this episode, we talk about the interplay of information, energy, and matter; the nature of the dataome and its relationship to humans and our artifacts; the past and future evolution of the biosphere and technosphere; the role of lies in the emergent informational metabolisms of the Internet; and what this psychoactive frame suggests about the search for hypothetical intelligences we may yet find in outer space. Be sure to check out our extensive show notes with links to all our references at complexity.simplecast.com. Note that applications are now open for our Complexity Postdoctoral Fellowships! Tell a friend. And if you value our research and communication efforts, please subscribe, rate and review us at Apple Podcasts or Spotify, and consider making a donation — or finding other ways to engage with us — at santafe.edu/engage. Thank you for listening! Join our Facebook discussion group to meet like minds and talk about each episode. Podcast theme music by Mitch Mignano. Follow us on social media: Twitter • YouTube • Facebook • Instagram • LinkedIn Mentioned and related resources: Caleb’s Personal Website, Research Publications, and Popular Writings Caleb’s Twitter We Are The Aliens by Caleb Scharf at Scientific American We Are Our Data, Our Data Are Us by Caleb Scharf at The Los Angeles Times Is Physical Law an Alien Intelligence? by Caleb Scharf at Nautilus Where Do Minds Belong? by Caleb Scharf at Aeon Autopoiesis (Wikipedia) The physical limits of communication by Michael Lachmann, M. E. J. Newman, Cristopher Moore The Extended Phenotype by Richard Dawkins “Time Binding” (c/o Alfred Korzybski’s General Semantics) (Wikipedia) The Singularity in Our Past Light-Cone by Cosma Shalizi Argument-making in the wild SFI Seminar by Simon DeDeo Coarse-graining as a downward causation mechanism by Jessica Flack If Modern Humans Are So Smart, Why Are Our Brains Shrinking? by Kathleen McAuliffe at Discover Magazine When and Why Did Human Brains Decrease in Size? A New Change-Point Analysis and Insights From Brain Evolution in Ants by Jeremy DeSilva, James Traniello, Alexander Claxton, & Luke Fannin Complexity 35 - Scaling Laws & Social Networks in The Time of COVID-19 with Geoffrey West (Part 1) The Collapse of Networks SFI Symposium Presentation by Raissa D'Souza Jevons Paradox (Wikipedia) What Technology Wants by Kevin Kelly The Glass Cage by Nicholas Carr The evolution of language by Martin Nowak an
More from COMPLEXITY
In the final episode of the season, Abha sits down with Melanie to hear her perspective. They chat about Melanie’s career and research with Douglas Hofstadter, the author of Gödel, Escher, Bach. They also discuss her opinions on LLMs’ current capabilities, what she thinks of existential questions like the alignment problem, how sustainable the industry is, the difficulty of making claims about concepts like “intelligence” and “understanding,” and what she thinks future technological development should focus on.
When it comes to assessing intelligence, people have all kinds of tests — the SAT, IQ tests, and so on. There’s controversy over how fairly these tests really measure human intelligence, but at the very least, we know that they correlate with some general reasoning skills when people take them. That assumption breaks down when we try to assess intelligence in non-humans. What does it mean when a large language model passes an intelligence test meant for humans? Does it actually have the same reasoning skills that a human does, or is it doing something else? In today’s episode, with guests Erica Cartmill and Ellie Pavlick, we investigate the best ways to assess intelligence in non-humans, whether animals or machines.
There’s an argument to be made that if we train AI systems to learn the way babies do, we’ll get them closer to human-like intelligence. But how our own learning development functions in babyhood is still a mystery that researchers are untangling. We know that the information babies absorb is very different from how an LLM learns, and in today’s episode, with guests Linda Smith and Michael Frank we’ll attempt to look at the world through an infant’s eyes and examine why they’re able to do more with, seemingly, less information.
Large language models, like ChatGPT and Claude, have remarkably coherent communication skills. Yet, what this says about their “intelligence” isn’t clear. Is it possible that they could arrive at the same level of intelligence as humans without taking the same evolutionary or learning path to get there? Or, if they’re not on a path to human-level intelligence, where are they now and where will they end up? In this episode, with guests Tomer Ullman and Murray Shanahan, we look at how large language models function and examine differing views on how sophisticated they are and where they might be going.
Complex language is unique to the human species. It’s part of how we evolved, the backbone of our societies, and one of the primary ways we judge others’ intellect. Is it our intelligence that leads to our language abilities, or conversely, does our ability for language enhance our intelligence, or both? How do language and thinking interact? And can one exist without the other? Guests: Evelina Federenko, Steve Piantadosi, and Gary Lupyan.