« Leveraging ML Models for Content Moderation: Equity Challenges (remote)
Leveraging ML Models for Content Moderation: Equity Challenges (remote)
May 11, 2022, 5:15 PM - 6:00 PM
Location:
The Heldrich Hotel & Conference Center
10 Livingston Avenue
New Brunswick, NJ 08901
https://www.theheldrich.com/directions/
Click here for map.
Nitesh Goyal, Google
Machine learning models are commonly used to detect toxicity in online conversations. These models are trained on datasets annotated by human raters. We are exploring how raters’ self-described identities impact how they annotate toxicity in online comments, can create more inclusive machine learning models, and such specialized rarer pools provide more nuanced ratings than those by random raters. Using these models to empower targets to self-manage their online harassment is another direction we continue to explore, by developing a PMCR (Prevention-Monitoring-Crisis-Recovery) harassment framework of user needs, and launching tools that can be used in the wild like Harassment Manager.
Bio:
Tesh (Nitesh) Goyal is the Head of User Research on Responsible AI Tools at Google Research. His work at Google has led to launch of ML based tools like Harassment Manager to empower targets of online harassment, ML based moderation to reduce online toxic content production on platforms like OpenWeb, and multiple NLP based tools that reduce biased sensemaking in criminal justice. He received his MSc in Computer Science from UC, Berkeley and RWTH Aachen, prior to receiving his PhD from Cornell University in Information Science. His research has been supported by German Govt. Fellowship, National Science Foundation, and MacArthur Genius Grant. He has published in top-tier HCI conferences and journals (CHI, CSCW, JASIST, ICTD, ICIC and Ubicomp/IMWUT), received two best paper honorable mention awards (CHI, CSCW), one nomination (ICTD Journal) and has been covered in popular press (eg. TheVerge, Everything in Moderation).
Tesh has served on the Organization Committee for ACM SIGCHI conferences including Tech Program Chair for coming CHI 2023, GDI Chair at CHI 2021, Doctoral Consortium Chair at IMX 2021, D&I Lunch Chair at CHI 2018-2020, and over 10 times as Associate Chair at multiple CHI and CSCW conferences since 2016. Tesh has also been appointed as Adjunct Professor at NYU Computer Science Department.