How AI Creates Racial Disparities In The Justice System
Brian Lehrer: A Daily Politics Podcast
WNYC Studios
4.4 • 675 Ratings
🗓️ 15 March 2021
⏱️ 24 minutes
🧾️ Download transcript
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| 0:00.0 | This is Brian Lair's Daily Politics podcast from WNYC Studios. |
| 0:09.9 | It's Monday, March 15th. |
| 0:14.9 | I'm Bridget Bergen, politics reporter for WNYC and Gothamist filling in for Brian today. |
| 0:22.4 | And now we go to Brian's weekly series with the green space called Punishment and Profit. It's all about the business side of the |
| 0:28.1 | prison industry. The question guiding these segments is, who profits when people get put away? |
| 0:34.1 | Every Tuesday evening through May 4th, the green space in partnership with the advocacy group, |
| 0:38.6 | Worth Rises, is holding a virtual panel discussion about one aspect of the business side of the |
| 0:44.4 | prison industry. And Brian previews those weekly discussions here on the show. Last week, |
| 0:50.2 | Brian talked about companies who provide the physical stuff to prisons, like furniture and |
| 0:54.7 | restraint equipment. Today, we're going to talk about something less tangible, but equally as |
| 1:00.1 | essential to the lifeblood of mass incarceration. That's data and surveillance technology, |
| 1:05.8 | things like facial recognition, fingerprinting, and software that law enforcement uses to set bail or identify |
| 1:12.3 | supposed gang affiliations. This kind of technological surveillance is a billion-dollar industry, |
| 1:19.2 | and it's only growing. With me now are Bianca Tylek, executive director of the nonprofit |
| 1:24.8 | advocacy organization worth rises, and Albert Foxcon, the founder |
| 1:30.8 | and executive director of the Surveillance Technology Oversight Project at the Urban Justice Center, |
| 1:36.8 | a New York-based Civil Rights and Privacy Group. He's also a fellow at the Engelberg Center |
| 1:41.7 | for Innovation Law and Policy at NYU School of Law. |
| 1:45.9 | Bianca Albert, welcome back to WNYC. |
| 1:49.4 | Thank you so much for having. |
| 1:50.6 | Hi, how are you? |
| 1:51.4 | Very nice to be with you this morning. |
... |
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