使用Player FM应用程序离线!
156 | Visualizing Fairness in Machine Learning with Yongsu Ahn and Alex Cabrera
Manage episode 255291234 series 2313435
In this episode we have PhD students Yongsu Ahn and Alex Cabrera to talk about two separate data visualization systems they developed to help people analyze machine learning models in terms of potential biases they may have. The systems are called FairSight and FairVis and have slightly different goals. FairSight focuses on models that generate rankings (e.g., in school admissions) and FairVis more on comparison of fairness metrics. With them we explore the world of “machine bias” trying to understand what it is and how visualization can play a role in its detection and mitigation.
[Our podcast is fully listener-supported. That’s why you don’t have to listen to ads! Please consider becoming a supporter on Patreon or sending us a one-time donation through Paypal. And thank you!]
Enjoy the show!
Links:
- Alex Cabrera
- Yongsu Ahn
- FairSight
- FairVis
- Google: “Attacking Discrimination with Smarter Machine Learning”
- Nicky Case: “Parable of Polygons”
Related episodes
章节
1. Welcome to Data Stories! (00:00:33)
2. Our podcast is listener-supported, please consider making a donation (00:01:07)
3. Our topic today: Bias and fairness in machine learning (00:01:41)
4. Our guests: Alex Cabrera (00:02:48)
5. and Yongsu Ahn (00:03:14)
6. How to define 'fairness' and 'bias' in machine learning? (00:03:54)
7. Examples of discriminitation in machine learning (00:08:49)
8. What is FairSight? (00:13:22)
9. What is FairVis? (00:17:00)
10. Do you have advice on how to get started with the topic? (00:38:32)
11. Get in touch with us and support us on Patreon (00:52:10)
170集单集
Manage episode 255291234 series 2313435
In this episode we have PhD students Yongsu Ahn and Alex Cabrera to talk about two separate data visualization systems they developed to help people analyze machine learning models in terms of potential biases they may have. The systems are called FairSight and FairVis and have slightly different goals. FairSight focuses on models that generate rankings (e.g., in school admissions) and FairVis more on comparison of fairness metrics. With them we explore the world of “machine bias” trying to understand what it is and how visualization can play a role in its detection and mitigation.
[Our podcast is fully listener-supported. That’s why you don’t have to listen to ads! Please consider becoming a supporter on Patreon or sending us a one-time donation through Paypal. And thank you!]
Enjoy the show!
Links:
- Alex Cabrera
- Yongsu Ahn
- FairSight
- FairVis
- Google: “Attacking Discrimination with Smarter Machine Learning”
- Nicky Case: “Parable of Polygons”
Related episodes
章节
1. Welcome to Data Stories! (00:00:33)
2. Our podcast is listener-supported, please consider making a donation (00:01:07)
3. Our topic today: Bias and fairness in machine learning (00:01:41)
4. Our guests: Alex Cabrera (00:02:48)
5. and Yongsu Ahn (00:03:14)
6. How to define 'fairness' and 'bias' in machine learning? (00:03:54)
7. Examples of discriminitation in machine learning (00:08:49)
8. What is FairSight? (00:13:22)
9. What is FairVis? (00:17:00)
10. Do you have advice on how to get started with the topic? (00:38:32)
11. Get in touch with us and support us on Patreon (00:52:10)
170集单集
所有剧集
×欢迎使用Player FM
Player FM正在网上搜索高质量的播客,以便您现在享受。它是最好的播客应用程序,适用于安卓、iPhone和网络。注册以跨设备同步订阅。