Episode 19: Defaults, Decisions, and Dynamic Systems: Behavioral Science Meets AI
Lis Costa, Chief of Innovation and Partnerships at the Behavioural Insights Team, joins High Signal to explore how behavioral science is reshaping public policy, digital platforms, and machine learning.
She explains how defaults influence behavior at scale, why personalization and chatbots are unlocking new kinds of interventions, and what happens when AI systems meet real-world complexity. We also discuss the limits of nudging, the promise of boosting, and why building for human decision-making requires more than just good models.
LINKS
The Behavioral Insights Team (https://www.bi.team/)
Lis Costa on LinkedIn (https://uk.linkedin.com/in/elisabeth-costa-6a5b35248)
High Signal podcast (https://high-signal.delphina.ai/)
Delphina's Newsletter (https://delphinaai.substack.com/)
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Episode 18: High-Stakes AI Systems and the Cost of Getting It Wrong
Sudarshan Seshadri—VP of AI, Data Science, and Foundations Engineering at Alto Pharmacy—joins us to explore what it takes to build high-stakes AI systems that people can actually trust. He shares lessons from deploying machine learning and LLMs in healthcare, where speed, safety, and uncertainty must be carefully balanced. We talk about designing AI to support pharmacist judgment, the shift from bottlenecks to decision backbones, and why great data leaders are really architects of how irreversible decisions get made.
LINKS
Suddu on LinkedIn (https://www.linkedin.com/in/ss01/)
Careers at Alto Pharmacy (https://www.alto.com/careers)
High Signal podcast (https://high-signal.delphina.ai/)
Delphina's Newsletter (https://delphinaai.substack.com/)
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Episode 17: The Incentive Problem in Shipping AI Products — and How to Change It
Roberto Medri, VP of Data Science at Instagram, explains why most experiments fail, how misaligned incentives warp product development, and what it takes to drive real impact with data science. He shares what teams get wrong about launches, why ego gets in the way of learning, and how Instagram turned Reels from a struggling product into a global success. A candid look at product, data, and decision-making inside one of the world’s most influential platforms.
LINKS
Roberto on LinkedIn (https://www.linkedin.com/in/robertomedri/)
High Signal podcast (https://high-signal.delphina.ai/)
Delphina's Newsletter (https://delphinaai.substack.com/)
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Episode 16: How Human-Centered AI Actually Gets Built
Fei-Fei Li—co-director of Stanford’s Human-Centered AI Institute and one of the most respected voices in the field—reflects on AI’s evolution from the early days of ImageNet to the rise of foundation models. She explains why spatial intelligence may be the next major shift, how human-centered design applies in practice, and why AI should be understood as a civilizational technology—one that shapes individuals, communities, and society at large.
LINKS
Stanford HAI (https://hai.stanford.edu/)
World Labs (https://www.worldlabs.ai/about)
"The World I See", Fei-Fei's book (a must read!) (https://us.macmillan.com/books/9781250897930/theworldsisee/)
Fei-Fei on X (https://x.com/drfeifei)
Fei-Fei on LinkedIn (https://www.linkedin.com/in/fei-fei-li-4541247/)
High Signal podcast (https://high-signal.delphina.ai/)
Delphina's Newsletter (https://delphinaai.substack.com/)
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Episode 15: Why Good Metrics Still Lead to Bad Decisions — and How to Fix It
Eoin O'Mahony—data science partner at Lightspeed, former Uber science lead, and one of the early architects of the system that kept NYC’s Citi Bikes available across the city—argues that positive metrics are meaningless if you don’t understand the mechanism behind them. At Uber, he was careful to make sure his launches both looked good on paper and made sense in practice. Now in venture, he’s applying that same rigor to unstructured data—using GenAI to scale a kind of work that’s long resisted systematization.
LINKS
Eoin's page at Lightspeed Ventures (https://lsvp.com/team-member/eoin-omahony/)
Ramesh Johari on How to Build an Experimentation Machine and Where Most Go Wrong (https://high-signal.delphina.ai/episode/ramesh-johari-on-how-to-build-an-experimentation-machine-and-where-most-go-wrong)
Chiara Farronato on Data Science Meets Management: Teamwork, Experimentation, and Decision-Making (https://high-signal.delphina.ai/episode/data-science-meets-management)
Delphina's Newsletter (https://delphinaai.substack.com/)
Welcome to High Signal, the podcast for data science, AI, and machine learning professionals.
High Signal brings you the best from the best in data science, machine learning, and AI. Hosted by Hugo Bowne-Anderson and produced by Delphina, each episode features deep conversations with leading experts, such as Michael Jordan (UC Berkeley), Andrew Gelman (Columbia) and Chiara Farranato (HBS).
Join us for practical insights from the best to help you advance your career and make an impact in these rapidly evolving fields.
More on our website: https://high-signal.delphina.ai/
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