COMPLEXITY

Tina Eliassi-Rad on Democracies as Complex Systems

COMPLEXITY

Show Notes

Democracy is a quintessential complex system: citizens’ decisions shape each other’s in nonlinear and often unpredictable ways; the emergent institutions exert top-down regulation on the individuals and orgs that live together in a polity; feedback loops and tipping points abound. And so perhaps it comes as no surprise in our times of turbulence and risk that democratic processes are under extraordinary pressure from the unanticipated influences of digital communications media, rapidly evolving economic forces, and the algorithms we’ve let loose into society. In a new special feature at PNAS co-edited by SFI Science Board Member Simon Levin, fifteen international research teams map the jeopardy faced by democracies today — as Levin and the other editors write in their introduction to the issue, “the loss of diversity associated with polarization undermines cooperation and the ability of societies to provide the public goods that make for a healthy society.” And yet humankind has never been more well-equipped to understand the problems that we face. What can complex systems science teach us about this century’s threats to democracy, and how to mitigate or sidestep them? How might democracy itself transform as it adapts to our brave new world of extremist partisanship, exponential change, and epistemic crisis? 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 speak with SFI External Professor Tina Eliassi-Rad, Professor of Computer Science at Northeastern University, about her complex systems research on democracy, what forces stabilize or upset democratic process, and how to rigorously study the relationships between technology and social change. If you value our research and communication efforts, please subscribe to Complexity Podcast wherever you prefer to listen, rate and review us at Apple Podcasts, and/or consider making a donation at santafe.edu/give. Please also be aware of our new SFI Press book, The Complex Alternative, which gathers over 60 complex systems research points of view on COVID-19 (including those from this show) — and that PhD students are now welcome to apply for our tuitionless (!) Summer 2022 SFI GAINS residential program in Vienna. Learn more at SFIPress.org and SantaFe.edu/Gains, respectively. 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 Related Reading & Listening: Tina’s Website & Google Scholar Page “What science can do for democracy: a complexity science approach” Tina Eliassi-Rad, Henry Farrell, David Garcia, Stephan Lewandowsky, Patricia Palacios, Don Ross, Didier Sornette, Karim Thébault & Karoline Wiesner “Stability of democracies: a complex systems perspective” K Wiesner, A Birdi, T Eliassi-Rad, H Farrell, D Garcia, S Lewandowsky, P Palacios, D Ross, D Sornette and K Thébault “Measuring algorithmically infused societies” Claudia Wagner, Markus Strohmaier, Alexandra Olteanu, Emre Kıcıman, Noshir Contractor & Tina Eliassi-Rad 1 - David Krakauer on The Landscape of 21st Century Science 7 - Rajiv Sethi on Stereotypes, Crime, and The Pursuit of Justice 35 - Scaling Laws & Social Networks in The Time of COVID-19 with Geoffrey West 38 - Fighing Hate Speech with AI & Social Science (Garland, Galesic, Olsson) 43 - Vicky Yang & Henrik Olsson on Political Polling & Polarization: How We Make Decisions & Identities 51 - Cris Moore on Algorithmic Justice and The Physics of Inference “Stewardship of global collective behavior” - Joe Bak-Coleman et al. Michelle Girvan - Harnessing Chaos & Predicting The Unpredictable with A.I.

Transmission T-015: Anth

More from COMPLEXITY

Dec 4, 2024

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.

Nov 20, 2024

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.

Nov 6, 2024

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.

Oct 23, 2024

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.

Oct 9, 2024

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.

See all episodes →