How Smart Is AI? (Part Two) with Meredith Broussard

Getting Curious with Jonathan Van Ness

Sony Music

Science, Self-improvement, Comedy, Education, Society & Culture

4.9 • 21.5K Ratings

🗓️ 16 March 2023

⏱️ 54 minutes

🔗️ Recording | iTunes | RSS

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Summary

We’re back with the second half of our special two-part episode about algorithms and artificial intelligence, featuring returning guest Meredith Broussard. Yesterday, we got the T on ChatGPT, and learned why we can’t trust algorithms to be fair or objective. Today, Jonathan and Meredith get personal about their encounters with algorithms, and consider what an equitable tech industry could look like. Plus, deepfakes, TikTok, the Supreme Court, and Jonathan’s take on M3GAN! Meredith Broussard is Associate Professor at the Arthur L. Carter Journalism Institute of New York University and Research Director at the NYU Alliance for Public Interest Technology. She is the author of Artificial Unintelligence: How Computers Misunderstand the World (MIT Press). Her work has been featured in the New Yorker, the New York Times, the Atlantic, BBC, Wired, the Economist, and more. She appears in the 2020 documentary Coded Bias and serves on the advisory board for the Center for Critical Race & Digital Studies. Make sure to check out Meredith’s new book More Than A Glitch, out now from MIT Press. You can follow Meredith on Instagram and Twitter @merbroussard, and at meredithbroussard.com. MIT Press is on Instagram and Twitter @mitpress. Curious for more? Here’s a list of people, projects, and other resources mentioned in this episode: Algorithmic Justice League (Joy Buolamwini) Algorithms of Oppression (Safiya Noble) Blueprint for an AI Bill of Rights DAIR Institute (Timnit Gebru) Deb Raji’s work Design Justice (Sasha Costanza-Chock) Melissa Murray’s work Mimi Onuoha’s work Race After Technology + Viral Justice (Ruha Benjamin) Rumman Chowdhury’s work Take My Hand (Dolen Perkins-Valdez) The Gender Shades Project The Markup (Julia Angwin) Under the Skin (Linda Villarosa) Weapons of Math Destruction + ORCAA (Cathy O’Neil) Follow us on Instagram and Twitter @CuriousWithJVN to join the conversation. Jonathan is on Instagram and Twitter @JVN and @Jonathan.Vanness on Facebook. Transcripts for each episode are available at JonathanVanNess.com. Our executive producer is Erica Getto. Our editor is Andrew Carson. Our theme music is “Freak” by QUIÑ; for more, head to TheQuinCat.com.

Transcript

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0:00.0	Welcome to Getting Curious, I'm Jonathan Van Ness, and every week I sit down for a gorgeous
0:04.0	conversation with a Barrilean expert to learn all about something that makes me curious.
0:09.6	On today's episode I am so freaking excited because we are joined again by Meredith Brussard
0:14.4	for part two of our conversation about artificial intelligence.
0:18.8	If you have not had a chance to listen to part one, I'd recommend revisiting it. It's just
0:23.1	the one literally before this. We talk AI Basics, Chat GBT, and that fucker Frances Galton.
0:29.3	Today we're going more in depth on algorithmic bias and what the future holds for artificial
0:34.5	intelligence. Let's get into that part of the story. Here's part two of our conversation
0:39.5	where we are asking, how smart is AI? Part two.
0:45.5	So in our gender episode of Getting Curious on Netflix, we did a sketch that ripped on a computer
0:51.0	not being able to break free of the gender binary. Is our world, even though I already know
0:55.7	this is true, but just in case you need a literal NYU professor to explain it,
1:01.7	is our tech really hardwired for a gender binary and cisgender norms?
1:07.8	100% yes. The reason for this is that our tech reflects basically 1950s ideas about gender,
1:19.6	because that's when computers were made. Our systems like NYU core university systems,
1:26.1	like our student management systems were developed in the 60s. They have these really
1:33.2	retro ideas about gender. NYU has done a really good job of updating its computer systems so that
1:41.8	now our students can have a range of gender options. Also, our students get identified to professors,
1:50.5	librarians and what have you using their preferred name, not necessarily their legal name.
1:56.8	This was an extremely expensive and time consuming change that only happened in the past couple
2:02.5	of years because people recognized a weight. We should not be dead naming our students in these
2:09.0	systems. We should not be forcing students to identify as one of only two genders because
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