Understanding bias in algorithmic systems
Thoughtworks Technology Podcast
Thoughtworks
4.5 • 58 Ratings
🗓️ 28 December 2018
⏱️ 21 minutes
🧾️ Download transcript
Summary
For this bonus episode, Rebecca Parsons, ThoughtWorks’ CTO is joined by special guest Danah Boyd, a sociotechnical researcher at Microsoft Research. They explore how bias is introduced in algorithms, the damaging impacts this can have and how this can be mitigated.
Danah is a renowned academic, widely published author and campaigner, with a focus on the intersection between people and technology. She has a strong interest in understanding how contemporary social inequities relate to technology and society more generally.
Transcript
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| 0:00.0 | Hello and welcome to the ThoughtWorks podcast. My name is Rebecca Parsons and I'm the chief technology officer for ThoughtWorks. |
| 0:06.7 | In today's special episode, I sit down with Dana Boyd, principal researcher at Microsoft Research, founder of data in society, and visiting professor at New York University's interactive telecommunications program. |
| 0:18.4 | We discuss everything from the early days of online content |
| 0:21.8 | moderation to bias and AI. I hope you enjoy the conversation as much as Dana and I did. |
| 0:29.4 | Hello, Dana. I'm thrilled to get a chance to talk to you. Thanks for having me. You just spoke to us |
| 0:33.7 | about bias and data and misuse and use. Let's start first with what you have learned |
| 0:40.6 | in dealing with education systems and what that actually implies for businesses and executives. |
| 0:46.1 | One of the blessings and curses of having been with social media since its earliest days |
| 0:51.8 | was the ability to see the good, bad, and ugly |
| 0:55.0 | of how everybody is using these systems. I will never forget in the earliest days of trying |
| 1:00.1 | to do content moderation on social media. We originally were just like, well, if we let anybody |
| 1:05.7 | post their thoughts on the internet, it'll be amazing. They'll share such, you know, sophisticated |
| 1:10.6 | ideas would be great. And, you know, sophisticated ideas would be great. |
| 1:11.6 | And, you know, the first day, are like, oh, porn. Why are people posting porn? And they're like, |
| 1:15.7 | of course people are going to post porn. And then, you know, you start in these moments where you try |
| 1:19.8 | to challenge things. I remember when AOL was concerned that people were talking about |
| 1:25.9 | anorexia in a positive sentiment on their platform, |
| 1:29.2 | and they decided they would ban that term. |
| 1:31.8 | They would just make it, so nobody could post about anorexia, about anything, you know, |
| 1:35.3 | prevention or participation or anything. |
| 1:37.3 | You know, it took less than 24 hours for people to start talking about their best friend to Anna. |
| 1:41.2 | And just being like, oh, you know, I had a great day with Anna and it was |
... |
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