Trends in Fairness and AI Ethics with Timnit Gebru

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we keep the 2019 AI Rewind series rolling with friend-of-the-show Timnit Gebru, a research scientist on the Ethical AI team at Google.

A few weeks ago at NeurIPS, Timnit joined us to discuss the ethics and fairness landscape in 2019. In our conversation, we discuss diversification of NeurIPS, with groups like Black in AI, WiML and others taking huge steps forward, trends in the fairness communities’ perspective, quite a few papers, and much more. Check out the rest of the series at twimlai.com/rewind19!

We want to hear from you! Send your thoughts on the year that was 2019 below in the comments, or via Twitter at @samcharrington or @twimlai.

To follow along with the 2019 AI Rewind Series, head over to the series page!

About Timnit

Mentioned in the Interview

  • #88 – Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru
  • Black in AI
  • LatinX in AI
  • Jews in ML
  • Queer in AI
  • New in ML
  • {Dis}Ability in AI
  • Women in ML
  • Opportunity Hub
  • Paper: Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
  • Paper: Towards a Critical Race Methodology in Algorithmic Fairness
  • Project: Gender Shades
  • Presentation: Emily Denton – Critical Perspectives on Computer Vision
  • Paper: This Thing Called Fairness: Disciplinary Confusion Realizing a Value in Technology
  • The Reductive Seduction of Other People’s Problems
  • Paper: Model Cards for Model Reporting
  • Paper: Datasheets for Data Sets
  • Paper: Data Statements for NLP
  • Google Cloud AI Explainable AI Toolkit
  • About ML – Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles
  • Facets – Know Your Data
  • #110 – Trust in Human-Robot/AI Interactions with Ayanna Howard
  • Check it out

    “More On That Later” by Lee Rosevere licensed under CC By 4.0

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