Wednesday, September 23, 2020

82 - What should we do about facial recognition technology?

Brenda Leong

Facial recognition technology has seen its fair share of both media and popular attention in the past 12 months. The runs the gamut from controversial uses by governments and police forces, to coordinated campaigns to ban or limit its use. What should we do about it? In this episode, I talk to Brenda Leong about this issue. Brenda is Senior Counsel and Director of Artificial Intelligence and Ethics at Future of Privacy Forum. She manages the FPF portfolio on biometrics, particularly facial recognition. She authored the FPF Privacy Expert’s Guide to AI, and co-authored the paper, “Beyond Explainability: A Practical Guide to Managing Risk in Machine Learning Models.” Prior to working at FPF, Brenda served in the U.S. Air Force. 

You can listen to the episode below or download here. You can also subscribe on Apple PodcastsStitcherSpotify and other podcasting services (the RSS feed is here). 

Show notes

Topics discussed include:
  • What is facial recognition anyway?
  • Are there multiple forms that are confused and conflated?
  • What's the history of facial recognition? What has changed recently?
  • How is the technology used?
  • What are the benefits of facial recognition?
  • What's bad about it? What are the privacy and other risks?
  • Is there something unique about the face that should make us more worried about facial biometrics when compared to other forms?
  • What can we do to address the risks? Should we regulate or ban?

Relevant Links

Friday, September 18, 2020

81 - Consumer Credit, Big Tech and AI Crime

In today's episode, I talk to Nikita Aggarwal about the legal and regulatory aspects of AI and algorithmic governance. We focus, in particular, on three topics: (i) algorithmic credit scoring; (ii) the problem of 'too big to fail' tech platforms and (iii) AI crime. Nikita is a DPhil (PhD) candidate at the Faculty of Law at Oxford, as well as a Research Associate at the Oxford Internet Institute's Digital Ethics Lab. Her research examines the legal and ethical challenges due to emerging, data-driven technologies, with a particular focus on machine learning in consumer lending. Prior to entering academia, she was an attorney in the legal department of the International Monetary Fund, where she advised on financial sector law reform in the Euro area.

You can listen to the episode below or download here. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).

Show Notes

Topics discussed include:

  • The digitisation, datafication and disintermediation of consumer credit markets
  • Algorithmic credit scoring
  • The problems of risk and bias in credit scoring
  • How law and regulation can address these problems
  • Tech platforms that are too big to fail
  • What should we do if Facebook fails?
  • The forms of AI crime
  • How to address the problem of AI crime

Relevant Links

Post Block Status & visibility Visibility Public Publish September 18, 2020 1:09 pm Stick to the top of the blog Author John Danaher Enable AMP Move to trash 9 Revisions Permalink Categories Uncategorized Podcast Add New Category Tags Add New Tag Separate with commas or the Enter key. Featured image Excerpt Discussion Open publish panel NotificationsCode editor selected