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PODCAST

High Signal: Data Science | Career | AI

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

technology

All Episodes

49:25

Episode 29: Why AI Adoption Fails: A Behavioral...

High Signal: Data Science | Career | AI ·

2025/11/28

Liz Costa of the Behavioral Insights Team returns to High Signal to deliver a critical behavioral science playbook for the AI era focused on human and business impact. We discuss why the potential of AI can only be fulfilled by understanding a single bottleneck: human behavior. The conversation reveals why leaders must intervene now to prevent temporary adoption patterns from calcifying into permanent organizational norms, the QWERTY Effect, and how to move organizations past simply automating

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50:34

Episode 28: From Context Engineering to AI Agent...

High Signal: Data Science | Career | AI ·

2025/11/13

Lance Martin of LangChain joins High Signal to outline a new playbook for engineering in the AI era, where the ground is constantly shifting under the feet of builders. He explains how the exponential improvement of foundation models is forcing a complete rethink of how software is built, revealing why top products from Claude Code to Manus are in a constant state of re-architecture simply to keep up.We dig into why the old rules of ML engineering no longer apply, and how Rich Sutton's "bitter

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41:35

Episode 27: Why Your Data Team Doesn't Have a Seat at...

High Signal: Data Science | Career | AI ·

2025/10/30

Paras Doshi (Head of Data, Opendoor; former data leader at Amazon) joins High Signal to unpack the playbook for building an indispensable data function. He shares his experience tackling the classic scaling challenge of fragmented data at Opendoor, where rapid growth led to inconsistent metrics across the business, and turning the data function into a centralized strategic asset.We dive deep into how to earn a true seat at the table, why he believes AI is creating the "100x individual contributor,"

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43:14

Episode 26: Gen AI's True Cost: Why Today's Wins Are...

High Signal: Data Science | Career | AI ·

2025/10/16

Vishnu Ram Venkataraman (Generative AI Executive & Entrepreneur; former AI Leader at Credit Karma and Intuit) joins High Signal to unpack the true cost of generative AI. Having scaled AI solutions impacting over 140 million users, Vishnu reveals why the ease of shipping Gen AI prototypes often masks significant operational and engineering debts, challenging the conventional wisdom of rapid deployment.We dive deep into the strategic shift from traditional ML to Gen AI, discussing why the shelf value

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56:22

Episode 25: How Data-Driven Growth Redefined a Media...

High Signal: Data Science | Career | AI ·

2025/10/02

Sergey Fogelson (VP of Data Science, Televisa Univision) joins High Signal to reveal how the world’s largest Spanish-language media company built a sophisticated data engine from the ground up. This transformation fueled a tenfold expansion of its digital streaming business by redefining how the company connects with 300 million viewers worldwide. At the heart of this success is a proprietary household graph that creates a single, privacy-first view of a massive and culturally diverse audience.We

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49:56

Episode 24: Rebuilding an Airline for the 21st...

High Signal: Data Science | Career | AI ·

2025/09/15

Andrés Bucchi (Chief Data Officer, LATAM Airlines) joins High Signal to unpack how a century-old airline reinvented itself with data and AI—and how that transformation is unlocking value from fuel efficiency to fraud detection. LATAM has built a massive data operation, experimenting across everything from pricing to operations, while customers benefit from a more reliable and secure travel experience.We dig into how LATAM fostered an experimentation culture, why existing data infrastructure is a

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51:17

Episode 23: Why Most AI Agents Fail (and What It...

High Signal: Data Science | Career | AI ·

2025/09/02

Anu Bharadwaj (President, Atlassian) joins High Signal to unpack how humans and AI agents will work together across the enterprise, and how that shift could change the very nature of teamwork. Atlassian employees have already built thousands of agents across product, marketing, engineering, and HR teams, while customers like HarperCollins are cutting manual work by 4x as industries from publishing to finance rethink their workflows.We dig into how Atlassian’s culture enables bottom-up

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46:50

Episode 22: Why a Trillion Dollars of Market Cap Is...

High Signal: Data Science | Career | AI ·

2025/08/19

Tomasz Tunguz (Theory Ventures) joins High Signal to unpack why a trillion dollars of market cap is up for grabs as AI reshapes enterprise software. He explains why workflows are now changing faster than packaged software can keep up, how “liquid software” is redefining CRM and marketing automation, and why background agents will require a new kind of “agent inbox.” We discuss the compounding errors that arise when tools are chained too finely, the hidden AI technical debt accumulating in today’s

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50:38

Episode 21: Why Great Data Still Leads to Bad...

High Signal: Data Science | Career | AI ·

2025/08/05

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,

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1:03:13

Episode 20: Incentives, Accountability, and the Data...

High Signal: Data Science | Career | AI ·

2025/07/22

Daragh Sibley, Chief Algorithms Officer at Literati and former Director of Data Science at Stitch Fix, joins High Signal to unpack how machine-learning moves from slide-deck promise to bottom-line impact. He walks through his shift from academic research on how kids learn to read to owning inventory and personalization algorithms that decide which five books land in every child’s box. We dig into the moment a data leader stops advising and starts owning P&L-critical calls, why some problems deserve

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54:08

Episode 19: Defaults, Decisions, and Dynamic Systems:...

High Signal: Data Science | Career | AI ·

2025/07/03

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

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58:45

Episode 18: High-Stakes AI Systems and the Cost of...

High Signal: Data Science | Career | AI ·

2025/06/19

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

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53:52

Episode 17: The Incentive Problem in Shipping AI...

High Signal: Data Science | Career | AI ·

2025/05/29

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

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47:22

Episode 16: How Human-Centered AI Actually Gets Built

High Signal: Data Science | Career | AI ·

2025/05/13

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

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54:17

Episode 15: Why Good Metrics Still Lead to Bad...

High Signal: Data Science | Career | AI ·

2025/04/24

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

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51:58

Episode 14: Barr Moses on Why Most Companies Aren’t...

High Signal: Data Science | Career | AI ·

2025/04/10

Barr Moses—co-founder and CEO of Monte Carlo—thinks we’re headed for an AI reckoning. Companies are building fast, but most are still managing data like it’s 2015. In this episode, she shares high-stakes failure stories (like a $100M schema change), explains why full-stack observability is becoming essential, and breaks down how LLM agents are already transforming data debugging. From culture to tooling, this is a sharp look at what real AI readiness requires—and why so few teams have it.LINKS 2024

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1:23:09

Episode 13: The End of Programming As We Know It

High Signal: Data Science | Career | AI ·

2025/03/27

Tim O’Reilly—founder of O’Reilly Media and one of the most influential voices in tech—argues we’re not witnessing the end of programming, but the beginning of something far bigger. He draws on past computing revolutions to explore how AI is reshaping what it means to build software, why real breakthroughs come from the edge—not incumbents—and what it takes to learn, teach, and build responsibly in the age of AI.LINKS The End of Programming as We Know It by Tim <--- Read this

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54:40

Episode 12: Your Machine Learning Solves The Wrong...

High Signal: Data Science | Career | AI ·

2025/03/13

Stefan Wager—Professor at Stanford and expert on causal machine learning—has worked with leading tech companies including Dropbox, Facebook, Google, and Uber. He challenges the widespread assumption that better predictions mean better decisions. Traditional machine learning excels at prediction, but is prediction really what your business needs? Stefan explores why predictive models alone often fail to answer critical “what-if” questions, how causal machine learning bridges this gap, and provides

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1:05:44

Episode 11: What Comes After Code? The Role of...

High Signal: Data Science | Career | AI ·

2025/02/27

Peter Wang—Chief AI Officer at Anaconda and a driving force behind PyData—challenges conventional thinking about AI’s role in software development. As AI reshapes engineering, are we moving beyond writing code to orchestrating intelligence? Peter explores why companies are fixated on models instead of integration, how AI is breaking traditional software workflows, and what this shift means for open source. He also shares insights on the evolving role of engineers, the commoditization of AI models,

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59:42

Episode 10: AI Won't Save You But Data Intelligence Will

High Signal: Data Science | Career | AI ·

2025/02/12

Ari Kaplan—Global Head of Evangelism at Databricks and a pioneer in sports analytics—explains why businesses fixated on AI often overlook the real advantage: making better decisions with their own data. He shares lessons from his work building analytics teams for Major League Baseball, advising McLaren’s F1 strategy, and helping companies apply AI where it actually works—without falling into hype-driven traps.SHOW NOTES Ari on LinkedIn (https://www.linkedin.com/in/arikaplan/) The Data Intelligence

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