Episode 21: Why Great Data Still Leads to Bad Decisions (And How to Fix It)
Amy Edmondson (Harvard Business School) and Mike Luca (Johns Hopkins) join High Signal to unpack what actually drives good decisions in data‑rich organizations. Using contrasts like the Bay of Pigs vs. the Cuban Missile Crisis and product cases such as Airbnb’s work on measuring discrimination, they show how decision quality tracks conversation quality—framing options, surfacing uncertainty, and challenging assumptions. We cover common failure modes (correlation vs. causation, anchoring, hierarchy, false precision), practical meeting designs that raise the signal, and where algorithms and LLMs help or hinder human judgment.
High Signal: Data Science | Career | AI
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Show Notes
Amy Edmondson (Harvard Business School) and Mike Luca (Johns Hopkins) join High Signal to unpack what actually drives good decisions in data‑rich organizations. Using contrasts like the Bay of Pigs vs. the Cuban Missile Crisis and product cases such as Airbnb’s work on measuring discrimination, they show how decision quality tracks conversation quality—framing options, surfacing uncertainty, and challenging assumptions. We cover common failure modes (correlation vs. causation, anchoring, hierarchy, false precision), practical meeting designs that raise the signal, and where algorithms and LLMs help or hinder human judgment.
LINKS
- Amy on LinkedIn
- Mike on LinkedIn
- Where Data-Driven Decision-Making Can Go Wrong: Five pitfalls to avoid by Michael Luca and Amy C. Edmondson
- Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results
- Trillion Dollar Coach by Eric Schmidt, Jonathan Rosenberg, and Alan Eagle
- Delphina's Newsletter