Computing Up

Professor Tina Eliassi-Rad of Northeastern's Network Science Institute talks with Michael and Dave about topics ranging from graph structures and machine learning to AI ethics and the nature of democracy. [Title image courtesy of Tina Eliassi-Rad]

Dave is feeling glum about technology -- and by extension about the impacts of computer science, the exploitation of science in general, and the hope for sustainability and truth in society. Michael helps sort it all out.

Michael and Dave talk to Heather J. Lynch, Associate Professor of Ecology and Evolution at Stony Brook University, about awards and leaving physics, about saving penguins and the planet, and more.

Heather Lane, machine learning researcher and senior architect at athenahealth, joins Dave and Michael in a talk of many things, of the thermodynamics of life, of the US healthcare industry and life after academia, of coming out as transgender.

Fil Menczer, professor and director of the Observatory on Social Media at Indiana University, joined Michael and Dave on the day after the 2020 USA presidential election. Fil revealed how his 1990s Artificial Life research set the stage for his current work, focusing not just on the facts of disinformation and hoaxes and conspiracy theories and social bots, but also how to identify and fight them. [Title image based on photograph licensed CC BY-SA 3.0 by Tracey Theriault]

Jeff Bigham, an Associate Professor at Carnegie-Mellon's Human-Computer Interaction Institute, joins Michael and Dave in a wide-ranging discussion of human-computer interactions, AI threats and opportunities, and systems and organizations made of both computers and humans. [Episode transcript (PDF)] [Cover photo courtesy of Jeff Bigham]

Michael and Dave discuss the meaning of the reward function, and its consequences for AI and human society.

Dave tries to explain his "We are coders" approach to cognition to Michael, as part of developing the second lecture in the "Introduction to Classical Hyperspace" series. First lecture

Computer scientists Emma Brunskill of Stanford and Phil Thomas of UMass Amherst join Michael and Dave in a four-way discussion of safety and fairness in AI and machine learning. [The primary paper discussed, Preventing undesirable behavior of intelligent machines, is by Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Stephen Giguere, Yuriy Brun, and Emma Brunskill, and can be accessed for free via paper in Science ]

Michael and Dave talk with UC Berkeley sociologist Jenna Burrell about topics ranging from algorithmic fairness and transparency, to anthropology and epistemology, to viral tweets and why small is beautiful. [Title image courtesy of Jenna Burrell]