Episode One: Should Data Scientists decide what’s good AI practice alone?
There are many obstacles for Data Scientists in effectively governing the use of AI. Firstly, overcoming the bias inherent in historical data. Secondly, agreeing on the boundaries of governing AI with the business and thirdly, and perhaps most importantly, ensuring the adoption of good AI practices across the organisation.
Join us for the first episode of this three-part series on Governing AI in which David Graus, Helen Hulsker, and Triveni Gandhi will address the obstacles to effective governance of AI, how to orchestrate efforts with internal stakeholders to overcome these, and what the effects will be of the new EU AI Act in this domain. David, Lead Data Scientist, and Helen, Senior Lawyer International Legal, will set the stage around implementing AI in a high-risk domain from a technical/practical and jurisdictional perspective. The webinar will be hosted by Triveni Gandhi, Dataiku’s Senior Industry Data Scientist specialising in Governing AI.
Speaker Bios:
David Graus
David is Lead Data Scientist at Randstad Groep Nederland, where he heads the data science chapter with over a dozen data scientists who work on a wide variety of projects including recommender systems, information extraction from resume and vacancy data, and knowledge graphs. He obtained his PhD in Information Retrieval in 2017 at the University of Amsterdam.
Helen Hulsker TBC
Triveni Gandhi
Triveni is a Senior Industry Data Scientist, focusing on Life Sciences and Responsible AI at Dataiku. She builds and implements custom solutions in the pharmaceutical and healthcare industry, and supports all industry clients in their efforts to develop best practices and education on responsible uses of AI. Previously, Triveni worked as a Data Analyst with a large non-profit dedicated to improving education outcomes in NYC and holds a Ph.D in Political Science from Cornell University.