

Episode 7: What Lies Beyond Machine Learning and AI: Decision Systems and the Future of Data Teams
4 snips Dec 19, 2024
Chris Wiggins, Chief Data Scientist at The New York Times and a Columbia University professor, discusses the transition from predictive to prescriptive analytics. He emphasizes the importance of actionable decision systems, highlighting how hospitals could benefit from prescription-based treatments. Wiggins introduces the AI Hierarchy of Needs, outlines strategies for scaling data teams, and underlines the necessity of empathy in data science for effective collaboration. His insights help bridge the gap between advanced technology and practical organizational applications.
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Joining The Times
- Chris Wiggins joined The New York Times after a sabbatical where he experimented with machine learning for subscription services.
- This led to building a data science team at the Times, transitioning from writing code to writing emails.
Prescriptive Analytics over Predictions
- Predicting outcomes is insufficient; focus on prescribing actions to optimize them.
- Shift from descriptive and predictive analytics towards prescriptive analytics, focusing on interventions.
Software-Driven Decisions
- Many companies operate within software, making decisions at scale.
- Product interventions can be framed as code, allowing for stochastic optimization.