Episode 7: What Lies Beyond Machine Learning and AI: Decision Systems and the Future of Data Teams - LLMs - High Signal

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LLMs Machine Learning Data science GenAI

Episode notes

In this episode of High Signal, Chris Wiggins - Chief Data Scientist at The New York Times, Professor at Columbia University, and co-author of How Data Happened - shares how organizations can move beyond prediction to actionable decision systems. Drawing on his work at The New York Times and in academia, Chris explains how to scale data teams, optimize systems, and align data science with organizational impact. Key topics from the conversation include: • From Prediction to Prescription: Why organizations need to focus on interventions that drive outcomes, illustrated with insights like, “Imagine a hospital prescribing treatments instead of just diagnosing conditions.” • The AI Hierarchy of Needs: Foundational practices, such as data logging and engineering, that enable advanced machine learning and AI. • Personalization and Optimization: How reinforcement learning and exploration-exploitation methods help optimize KPIs and adapt to user context. • Scaling Data Teams: Strategies for attracting and retaining talent by emphasizing autonomy, mastery, and purpose.

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