Predicting Responsibly: AI, Bias, and the Art of Data Science
Head of Strategic Data Science, Investment Management, Two Sigma
About this episode
Claudia Perlich, a leading expert in predictive modeling shares about her work and views on the challenges of using AI and machine learning systems. Perlich discusses the importance of understanding the uncertainty and biases inherent in these models, and the need for careful evaluation and testing before deploying them, especially in high-stakes domains. She emphasizes the collective responsibility of data scientists, domain experts, and decision-makers to ensure these systems are used responsibly and equitably. She also shares insights on the skills and mindset needed for a successful career in predictive modeling, highlighting the value of data curiosity, scientific thinking, and effective communication.
Highlights
- Predictive Modeling (4:15)
- Human judgement and processes (14:06)
- Imperfection in models (21:40)
About the Guest
Claudia Perlich is Managing Director and Head of Strategic Data Science for Investment Management at Two Sigma, where she has worked for seven years. In this role, Claudia is responsible for developing innovative alpha strategies at the intersection of alternative data, thematic hypotheses and machine learning in public markets. Claudia joined Two Sigma from Dstillery, an AI ad targeting company, where she worked as Chief Scientist. Claudia began her career in data science at the IBM Watson Research Center, concentrating on research in data analytics and machine learning for complex real-world domains and applications.
Since 2011, Claudia has served as an adjunct professor teaching Data Mining in the M.B.A. program at New York University’s Stern School of Business. Claudia received a Ph.D. in Information Systems from Stern School of Business, New York University, holds an M.S. of Computer Science from Colorado University and a B.S. in Computer Science from Technical University Darmstadt, Germany.
About the Host
Margot Gerritsen
Stanford Professor [Emerita] Margot Gerritsen is the Executive Director and co-founder of Women in Data Science Worldwide (WiDS) and born and raised in the Netherlands. Margot received her MSc in Applied Mathematics from Delft University of Technology before moving to the US in search of sunnier and hillier places. In. 1996 she completed her PhD in Scientific Computing & Computational Mathematics at Stanford University and moved further West to New Zealand where she spent 5 years at the University of Auckland as a lecturer in Engineering Science. In 2001, she returned to Stanford as faculty member in Energy Resources Engineering. Margot was the Director of the Institute for Computational & Mathematical Engineering (ICME) at Stanford from 2010-2018 and the Senior Associate Dean for Educational Affairs in Stanford’s School of Earth Sciences from 2015-2020. In 2022, Margot took Emerita status to devote herself to WiDS full time. Margot is a Fellow of the Society of Industrial & Applied Mathematics, and received honorary doctorates from Uppsala University, Sweden, and the Eindhoven University of Technology in the Netherlands. She now lives in Oregon with her husband Paul.
Connect with Margot Gerritsen on Twitter (@margootjeg) and LinkedIn.
Find out more about Margot on her Stanford Profile.