![The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) artwork](https://is1-ssl.mzstatic.com/image/thumb/Podcasts113/v4/39/58/c6/3958c6ce-86e4-3b80-bfb9-840e1dfd7e4b/mza_491361902049110775.png/100x100bb.jpg)
Unbiased Learning from Biased User Feedback with Thorsten Joachims - TWiML Talk #207
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
English - December 07, 2018 19:04 - 40 minutes - ★★★★★ - 323 ratingsTechnology News Tech News machinelearning artificialintelligence datascience samcharrington tech technology thetwimlaipocast thisweekinmachinelearning twiml twimlaipodcast Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: Language Parsing and Character Mining with Jinho Choi - TWiML Talk #206
Next Episode: Trust and AI with Parinaz Sobhani - TWiML Talk #208
In the final episode of our re:Invent series, we're joined by Thorsten Joachims, Professor in the Department of Computer Science at Cornell University. We discuss his presentation “Unbiased Learning from Biased User Feedback,” looking at some of the inherent and introduced biases in recommender systems, and the ways to avoid them. We also discuss how inference techniques can be used to make learning algorithms more robust to bias, and how these can be enabled with the correct type of logging policies.