Predicting Responsibly: Claudia Perlich on AI, Bias, and the Art of Data Science

Predicting Responsibly: Claudia Perlich on AI, Bias, and the Art of Data Science

Author: Professor Margot Gerritsen, Chisoo Lyons January 16, 2025 Duration: 46:02
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.

Hosted by Professor Margot Gerritsen and Chisoo Lyons, Women in Data Science Worldwide is a conversation with researchers and practitioners at the forefront of a rapidly evolving field. Each episode moves beyond abstract theory to explore the tangible, often surprising, ways data science is applied. You’ll hear firsthand accounts of analytical work creating change, whether it’s developing new models for patient care, building equitable financial systems, or parsing complex climate datasets. The discussions are grounded in the professional journeys of the guests, who offer practical advice and reflect on the challenges they’ve navigated. This podcast provides a direct audio connection to a global community of experts, highlighting the diverse thought and innovation driven by women in the discipline. Listening reveals the human story behind the algorithms and the collective effort shaping the future of technology across every sector. It’s an ongoing series for anyone curious about the real-world impact of data, from students to seasoned professionals, offering perspective and insight naturally through each guest’s experience.
Author: Language: English Episodes: 59

Women in Data Science Worldwide
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