Episode 36: AI and the Judgment Problem in Data Science

About this episode

The episode discusses the challenges and transformations in data science and analytics due to AI advancements.

Dawn Woodard (Distinguished Engineer, LinkedIn), Andrés Bucchi (LATAM Airlines), and Jeremy Hermann (CEO & Co-Founder, Delphina) join High Signal for a deep dive into the shifting architecture of data science & analytics in the era of AI. As the industry moves from static dashboards to vibe coding and conversational querying, this panel of industry veterans explores why traditional data fundamentals—strict cataloging, verifiable outputs, and a single source of truth—are suddenly the most critical bottlenecks in the AI era. We dig into the sobering reality of the "source of truth" problem, where the speed of AI-generated code far outpaces our ability to define what "correct" actually looks like in a complex enterprise. The conversation reveals how AI is breaking legacy experimentation platforms, the transition of the data analyst into a "verifier" of AI-generated workflows, and why "headless" security architectures are essential for the next generation of autonomous agents. From the limitations of LLMs in causal reasoning to the challenges of integrating AI into "brownfield" enterprise codebases, this discussion provides a grounded framework for leaders navigating the gap…

People in this episode

Host: Delphina

Guests: Dawn Woodard, Andrés Bucchi, Jeremy Hermann

Topics covered

• AI in data science
• data analytics
• source of truth
• AI-generated workflows
• enterprise codebases
• data fundamentals

Keywords

• AI
• data science
• analytics
• source of truth
• LLMs
• enterprise
• data analyst
• security architectures

Mentioned in this episode

Organizations: LinkedIn, LATAM Airlines, Delphina

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