If/Then

What makes one workplace hierarchy motivating and another toxic?

This week on If/Then, we’re sharing a conversation between two Stanford GSB colleagues: Think Fast, Talk Smart host Matt Abrahamsand organizational behavior professor Nir Halevy.

Drawing on research from his new book, Level Up: Why Hierarchies Are Broken and How to Fix Them, Nir explains why some hierarchies become overly competitive, unfair, or unstable — and why the answer isn’t necessarily to get rid of them. Matt and Nir explore how everyday communication can help repair unhealthy dynamics, why recognizing different kinds of contribution can strengthen teams, and how leaders can create environments where competition and collaboration can coexist.

It’s a conversation about the structures that shape how we work, and the role each of us can play in making them work better.

Related Content:

• Think Fast Talk Smart, the podcast
• Matt Abrahams
• Nir Halevy

Chapters:

00:00 Introduction

01:22 Understanding Hierarchies

03:43 Signs of Broken Hierarchies

05:43 Fixing Unhealthy Hierarchies

06:56 Building Healthy Hierarchies

10:05 Competition and Collaboration

11:29 Communication and Hierarchies

14:03 Construal Fit

17:36 Humor and Competence

19:47 The Final Three Questions

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

When Demis Hassabis pitched DeepMind to a few venture capitalists back in 2010, the business plan was almost comically audacious. “Step one: Solve intelligence. Step two: Use it to solve everything else,” he recalls in a conversation at Stanford Graduate School of Business with Stanford University President Jonathan Levin. “And people were quite confused. But we really meant it.”

Sixteen years later, the “broad arcs” of that plan have gone “unbelievably well,” says Hassabis, a chess prodigy turned video game developer turned neuroscientist turned Nobel Prize-winning AI pioneer. Today he’s on a mission to create “the ultimate tool for science,” building on his decision to give away AlphaFold, the groundbreaking AI system that predicts the structures of proteins. The future, Hassabis says, is just around the corner: “Ten years from now, I think we’ll realize that we were standing in the foothills of the singularity now.”

Chapters:

00:00:00 Introduction

00:03:31 A career built around one big question

00:06:19 Building DeepMind and pursuing AGI

00:10:09 The breakthroughs that made AI feel possible

00:14:48 From AlphaGo to scientific discovery

00:17:15 Why AlphaFold was given away for free

00:24:00 The “foothills of the singularity”

00:26:41 Public concern, disruption, & AI’s promise

00:29:59 How AI could reshape work and entrepreneurship

00:34:12 Competition, safety, & regulating frontier AI

00:41:19 Expanding AI’s benefits globally

00:45:28 Preparing society for AGI

00:48:21 What should AI leave untouched?

00:51:01 Advice for the first AI-native generation

00:54:19 Conclusion

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What if purpose is what drives us to act, but meaning comes from how those actions affect other people?

This week on If/Then, we’re sharing a conversation between two Stanford GSB colleagues: Think Fast, Talk Smart host Matt Abrahams and organizational behavior professor Brian Lowery.

Recorded live at Stanford’s LEAD Me2We event, Matt and Brian explore the difference between purpose and meaning, why meaning is rooted in our relationships with others, and how the way we show up shapes the people around us. They also discuss sincerity, leadership, and how to give feedback that helps people feel seen rather than judged.

It’s a conversation about the ripple effects of our interactions — and what they mean for how we work, lead, and connect with others.

Related Content:

• Think Fast Talk Smart, the podcast
• Matt Abrahams
• Brian Lowery

Chapters:

00:00:00 Introduction

00:01:14 Meaning vs. purpose

00:02:14 How to find purpose

00:02:50 Finding meaning through service to others

00:04:49 How relationships shape identity

00:05:54 The leader’s role in shaping others

00:09:32 Self-awareness and psychological safety

00:11:10 Respecting perspectives you don’t share

00:12:23 Sincerity vs. authenticity

00:13:28 Giving feedback that people can hear

00:17:47 What it means to be a better human

00:18:57 Conclusion

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

How do you engage effectively across deep disagreement without shutting down the conversation?

This week on If/Then, we’re sharing an episode from our colleagues at Stanford Legal, the podcast from Stanford Law School that looks at the cases, questions, and conflicts shaping public life.

In a world where confidence is rewarded and humility can feel like a liability, Stanford Law professor Robert MacCoun argues for something radical: fewer unwavering opinions, more critical reflection, and a better way to disagree. On Stanford Legal, MacCoun joins co-hosts Pam Karlan and Diego Zambrano for a conversation about how “habits of mind” borrowed from science can help citizens, lawyers, and policymakers think more clearly, listen more carefully, and build better public debate around difficult questions that don’t have easy answers.

Trained as a social psychologist, MacCoun's work sits at the intersection of law, science, and public policy, with decades of research on decision-making, bias, and the social dynamics that shape how evidence is interpreted. In the episode, he draws on his most recent book, Third Millennium Thinking: Creating Sense in a World of Nonsense, co-authored with Nobel Prize–winning physicist Saul Perlmutter and philosopher John Campbell, to explain why probabilistic thinking, intellectual humility, and what he calls an “opinion diet” are essential tools for modern civic life.

Related Content:

• Robert MacCoun faculty profile
• Third Millenium Thinking
• Stanford Legal Podcast

Chapters:

00:00:00 Introduction

00:01:23 The course, the book, & what motivated it

00:04:06 Habits of mind for better decision-making

00:06:20 Probabilistic thinking and intellectual humility

00:09:57 An “opinion diet”

00:12:16 Reasonable doubt, community, & collective judgment

00:14:13 Scientific optimism and the problem of cynicism

00:17:31 Why trust in science has eroded

00:20:10 Law, science, & the value of procedure

00:22:50 Steel-manning the other side

00:24:58 Public policy as provisional problem-solving

00:30:07 Deliberative democracy and informed public debate

00:32:03 Conclusion

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

“Humans manage to do so much with surprisingly little,” says Douglas Guilbeault, an assistant professor of organizational behavior at Stanford Graduate School of Business. “Whereas AI, by comparison, is doing relatively little, but with so much power, so much compute, so many resources, and by comparison, relatively fewer constraints.”

On a bonus episode of the If/Then podcast, Guilbeault describes the implications of his recent work. Although he readily acknowledges that AI is “increasingly able to do quite a lot,” Guilbeault and his colleagues believe they have identified a key principle that distinguishes human intelligence from machine intelligence — and one which illuminates the limitations of machine thinking.

Although some researchers and AI boosters believe both humans and AI learn via optimization, Guilbeault and his colleagues have shown that another process more accurately captures how people distill the seemingly infinite complexity of the world and act based on limited information.

“You encounter a lot of noise, a lot of chaos, a lot of randomness,” Guilbeault says. “We somehow figure out how to make meaning and establish strong understandings from within that.”

What limitations have you encountered in your work with AI? Share your story with us at ifthenpod@stanford.edu.

Related Content:

• Douglas Guilbeault faculty profile
• Read "A Simple Threshold Captures the Social Learning of Conventions" here

Chapters:

00:00:00 Introduction

00:01:40 Why human learning matters for AI

00:05:03 Satisficing and the limits of optimization

00:06:41 Why LLMs learn differently from humans

00:09:58 The stakes of AI hype

00:13:11 “Humanity has had a good run”

00:15:19 Intuition, insight, & conceptual leaps

00:17:38 Beyond statistics: metaphor, vibes, & reasoning

00:19:39 A simple rule for social learning

00:21:18 Is there a ceiling for AI?

00:23:00 Randomness, disorder, & the path to insight

00:25:00 What an optimization mindset leaves out

00:27:54 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Chad Jones, a professor of economics at Stanford Graduate School of Business, recently published a paper, “AI and Our Economic Future.” Using more than 100 years of economic data, he modelled several potential AI-infused economic futures we may experience. These include the good (abundance, we never work again), the not-so-bad (business more or less as usual), and the ugly (a superintelligence that turns on us, among other catastrophic options). Cheery stuff, Jones acknowledges, but essential to face.

“I think the ability for an AI to do everything on a computer that the best software engineer can do, that seems like it’s either here now or will be here within five years easily,” Jones says. “Hacking the electric grid, hacking the financial system, these kinds of scenarios are things that we definitely have to worry about. The good news is, I think if we get through that, the ability of AI to transform the economy for good, it is really there and present. And, that would be a very great and bright future.”

Related Content:

• Chad Jones faculty profile
• What’s the Price Tag for Preventing an AI Apocalypse?
• At What Point Do We Decide AI’s Risks Outweigh Its Promise?

Chapters:

00:00:00 Introduction

00:01:32 The difference between now & previous periods of innovation

00:02:29 Two scenarios for AI-driven growth

00:06:18 The case for business-as-usual

00:11:06 Weak links and the limits of automation

00:17:53 What the models are showing about growth

00:19:58 The economics of abundance

00:25:29 The weak-link model’s timing & possible adaptations

00:27:51 Who gains in an AI economy?

00:29:55 Catastrophic risk and the downside of acceleration

00:34:31 The downsides of the weak link model

00:36:38 Meaning, identity, and human value

00:39:55 Leisure in a post-work world

00:41:43 What the next generation may inherit

00:44:07 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

“Friction for us has to do with obstacles,” says Hayagreeva “Huggy” Rao, a professor of organizational behavior at Stanford Graduate School of Business. “Obstacles can disable you. Obstacles can enable you.”

Rao compares friction to cholesterol: Some is good, but some is bad. “Good friction actually slows you down, gets you to pause, and most of all, gets you to reflect,” he explains. “But there’s also friction that overwhelms you, exhausts you, confuses you.”

On this episode of If/Then, Rao explores how to cultivate the productive kind of friction, reduce the unhelpful kind, and manage your team’s most precious resource. “Great leaders are people who think of themselves as trustees of other people's time,” he says.

Do you have any favorite examples of good or bad friction? Share one with us at ifthenpod@stanford.edu.

Related Content:

• Huggy Rao faculty profile
• The Friction Project
• How to become a friction fixer

Chapters:

00:00:00 Airport baggage claim, waiting, & good friction

00:03:20 Introduction

00:03:48 What friction means in organizations

00:05:42 Where friction comes from

00:07:52 Scaling through smart subtraction

00:08:24 DropBox’s approach to meetings

00:10:45 The problem with meetings

00:13:53 What good friction looks like

00:16:56 Friction, trust, & institutional legitimacy

00:19:31 Why Huggy Rao started studying friction

00:22:20 Conclusion

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

“I don’t see things like anybody else,” says Jonathan Berk, a professor of finance at Stanford Graduate School of Business. “And so I can see things people don't see.”

On this episode, Berk explores recent research that pushes against conventional wisdom, from questioning the utility of the debt-to-GDP ratio to asking whether regulation is actually in the best interests of the consumer.

“If you disagree with me… You have to write down a convincing theoretical model and analyze [it].”

Berk admits his unique lens doesn’t always make life easy. But on the other hand, “it confers an enormous advantage” — and he believes that organizations which are able to harness the power of unconventional thinking can gain a competitive edge.

“It’s allowed me to solve problems that other people couldn't solve,” he says.

Has seeing the world differently helped you resolve a conundrum? Tell us more at ifthenpod@stanford.edu.

Related Content:

• Jonathan Berk faculty profile
• What If We’re Looking at the National Debt All Wrong?

Chapters:

00:00:00 The Fosbury Flop, innovation, & unconventional thinking

00:03:18 Introduction

00:04:24 Questioning conventional wisdom

00:04:57 Rethinking the debt-to-GDP ratio

00:08:21 A finance perspective on national debt

00:10:36 Why theory matters before alarm

00:12:38 Regulation, charlatans, & consumer interests

00:16:22 Licensing, certification, & competition

00:19:51 The cost of pushing back

00:21:16 Building organizations that welcome dissent

00:24:59 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

“When people come to view attitudes and opinions towards, say, political policies or issues as relevant to their identities, they become more extreme in their attitudes,” says Christian Wheeler, the StrataCom Professor of Management and Professor of Marketing at Stanford Graduate School of Business. “I become more positive or negative towards an issue the moment it becomes relevant to who I view myself as being.”

Wheeler’s research offers insight into our increasingly polarized politics. However, his work has also yielded ideas for bridging divisions — beginning with how we listen to each other and how we see the people we disagree with.

The moment we see someone as an individual rather than a category, we become more likely to find common ground. “Instead of viewing you as a Democrat or a Republican, I can view you as an individual,” Wheeler recommends. “Anything that humanizes you and moves you away from this simple category will help me to view you as an individual and less as just an interchangeable member of a category.”

How much do your opinions define who you are? Tell us more at ifthenpod@stanford.edu.

Related Content:

• Christian Wheeler faculty profile
• In a Polarized World, an Open Mind Can Hurt Your Reputation
• You May Not Be Who You Think You Are
• Class Takeaways — How to Build Connection Through Better Listening

Chapters:

00:00:02 Tattoos, identity, & personal evolution

00:03:26 Introduction

00:03:59 Why identity matters

00:04:56 Identity relevance & its implications

00:08:03 Why openness to the other side gets punished

00:10:57 Identities vs. opinions

00:13:53 The power of individuation

00:15:53 How to break the cycle of polarization

00:19:41 Organizational applications

00:23:26 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

“Masculinity is my new frontier,” says Ashley Martin, an associate professor of organizational behavior at Stanford Graduate School of Business. Martin, whose work examines why gender plays such a central role in how we perceive and make sense of others, has been looking at how traits associated with masculinity are simultaneously organizationally rewarded even as they’re personally harmful to men.

“We spend a lot of time talking about gender inequality through the lens of women’s disadvantage,” she says. “I think that many of the problems that we’re seeing today… are actually bound up in masculinity.”

What impact do you think masculinity and femininity have on our work and our world? Tell us more at ifthenpod@stanford.edu.

Related Content:

• Ashley Martin faculty profile
• Is that Self-Driving Car a Boy or a Girl?
• Why Taking Gender Out of the Equation Is So Difficult

Chapters:

00:00 How movies shape our ideas about masculinity

04:02 Introduction

05:15 How Ashley Martin got into studying gender

05:58 When gender is removed from hiring

07:10 The “pet rock” study

10:35 The universal use of gender

13:02 Gendering objects

15:12 How masculinity affects men

18:13 The current implications of Martin’s research

20:41 What healthier models of masculinity might look like

23:47 Ashley’s next frontier: masculinity, material culture, and social problems

25:07 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Steven Callander has spent years building a mathematical framework to answer the question of how people learn from experience. “Here in Silicon Valley, the expression that you learn from failure is very widespread and very intuitive. But the question is… what do you learn? How do you optimally learn from that experience?”

In this episode, Callander, the Herbert Hoover Professor of Public and Private Management and Professor of Political Economy at Stanford Graduate School of Business, explains the hidden, deceptively simple logic of correlated learning — and it may change how you think about finding the right job, the right market, or the right strategy.

“It fascinates me and I can't stop thinking about it,” he says.

Has theory made an impact on your life? Tell us more at ifthenpod@stanford.edu.

Related Content:

• Steven Callander faculty profile
• How to Turn Old Ideas Into Creative Solutions to Modern Problems
• What We’re Still Learning from Silicon Valley’s Bank Collapse

Chapters:

00:00 Ann Miura-Ko on learning and the search for patterns in Venture capital

02:51 Introduction

05:23 What is correlated learning?

06:40 Where does this research apply in the real world?

09:28 Brownian Motion

12:45 Steven Callander’s Framework

15:25 Examples of correlated learning when seeking expert advice

20:53 Applying correlated learning

23:57 Why correlated learning research?

24:51 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Seemingly unrelated activities — like taking a soccer penalty kick or crafting an online dating profile — involve an embedded economics.

“Understanding and applying economic logic can be valuable in pretty much any job or any other endeavor in your life,” says Paul Oyer, a professor of economics at Stanford Graduate School of Business.

On this episode, Oyer digs into the shared economic logic of online dating and the labor market, explains why pro athletes and sports fans think like economists, and explores how AI has reduced the beneficial friction that was once a part of job searches.

Got a question about the economics of dating, sports, or the job market? Ask us at ifthenpod@stanford.edu.

Related Content:

• Paul Oyer faculty profile
• Utility Player: Paul Oyer Explains How Economics Can Make Sports More Fun

Chapters:

00:00 Strategic decision-making in air traffic control

03:06 Introduction

03:27 Why sports are a useful lens for understanding economics

09:53 Why economics matters far beyond money

10:54 Economics & online

14:36 Applications of game theory

16:54 How AI is reshaping hiring and the labor market

22:25 The labor market challenge economists still have not solved

24:18 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

When should we leap instead of take the obvious next step? Why do we instinctively see gender everywhere? When do our opinions begin to feel less like ideas and more like our identity?

If/Then, from Stanford Graduate School of Business, is back with a new season of sharp, surprising conversations that deepen our understanding of business and leadership.

Each episode brings you into the room with a Stanford GSB faculty member as they discuss their research and how it challenges conventional wisdom, sharpens judgment, and reframes the way we approach complex decisions.

Join us on Wednesdays for a new season of If/Then.

What do you want to hear on If/Then? Email us at ifthenpod@stanford.edu.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on If/Then we’re sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business’s Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs as Stanford GSB celebrates its first century and looks around the corner to what the next 100 years may hold.

On this episode of GSB at 100, you’ll experience Centennial Day, hear Dean Sarah A. Soule honor the past, celebrate the present, and look to what the future may hold. GSB at 100 depicts a school defined not only by its innovation and impact, but by its people: curious students, devoted faculty, and accomplished staff — a community of thinkers, dreamers, and doers.

Learn more about the Stanford GSB Centennial

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on If/Then we’re sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business’s Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs as Stanford GSB celebrates its first century and looks around the corner to what the next 100 years may hold.

On this episode of GSB at 100, you’ll step inside the classrooms where teaching sparks transformation.

Learn more about the Stanford GSB Centennial

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on [If/Then or View From The Top] we’re sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business’s Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs as Stanford GSB celebrates its first century and looks around the corner to what the next 100 years may hold.

On this episode of GSB at 100, you’ll hear from the dedicated and accomplished staff members who work behind the scenes to make Stanford GSB a community unlike anywhere else in the world.

Learn more about the Stanford GSB Centennial

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on If/Then, we’re sharing an episode of What’s Your Problem?, a show from Pushkin Industries where entrepreneurs, engineers, and scientists talk about the future they’re trying to build—and the problems they must solve to get there. Hosted by former Planet Money co-host Jacob Goldstein, each conversation explores the challenges and breakthroughs shaping the next wave of innovation.

In this episode, Goldstein speaks with Fei-Fei Li, Stanford computer scientist, former Chief Scientist of AI and Machine Learning at Google, and one of the most influential figures in the field of computer vision. Li reflects on her pioneering work developing ImageNet, the massive dataset that helped spark the modern AI revolution, and the “north star” questions that have guided her research from neuroscience to machine learning.

Together, they trace how a single insight about how humans see the world led to a paradigm shift in artificial intelligence—and how Li’s vision continues to shape the way we teach machines to see, learn, and collaborate with us.

More Resources:

• Fei Fei Li

• Stanford Institute for Human-Centered Artificial Intelligence (HAI)

• ImageNet

• What’s Your Problem?

If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society.

Chapters:

(00:00:00) Introducing “What’s Your Problem?”

Kevin Cool introduces the Pushkin Industries podcast hosted by Jacob Goldstein.

00:00:45 — What Is Computer Vision?

Jacob Goldstein and Fei-Fei Li explain how machines learn to see and interpret images.

00:03:18 — Real-World Uses of AI Vision

Li shares examples from healthcare, robotics, and environmental science.

00:05:06 — Discovering the Science of Seeing

How human vision research inspired Li’s lifelong “north star” in AI.

00:09:56 — Creating ImageNet

Li builds a massive image database that transforms computer vision research.

00:13:29 — Defining 30,000 Visual Concepts

How cognitive science helped shape ImageNet’s massive scale.

00:16:41 — Building the Dataset by Hand

Li's team uses global crowdsourcing to label millions of images.

00:19:38 — The 2012 Breakthrough

Jeff Hinton’s neural network shatters records and sparks the deep learning era.

00:22:19 — Data Meets Hardware

Li reflects on how big data and GPUs converged to power modern AI.

00:24:55 — Lightning Round with Fei-Fei Li

Quick insights on resilience, mentorship, and the future of human-AI collaboration.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on If/Then, we’re sharing an episode of GSB at 100, a limited audio series created especially for Stanford Graduate School of Business’s Centennial. GSB at 100 presents a scrapbook of memories, ideas, and breakthroughs, as the GSB celebrates its first century and looks around the corner to what the next hundred years may hold.

The first episode of the series begins where the GSB begins: in 1925, Herbert Hoover, a Stanford alum and future U.S. president, had an idea. “A graduate School of Business Administration is urgently needed upon the Pacific Coast,” he wrote.

One hundred years later, what has Stanford Graduate School of Business accomplished, and what might its future hold? Listen in as professors reflect on founding principles, frontier technologies, and the magic that makes the GSB the place it is — and shapes what it aspires to be.

If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society. Each episode features an interview with a Stanford GSB faculty member.

Learn more about the Stanford GSB Centennial

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week on If/Then, we’re sharing an episode of View From The Top: The Podcast, an audio series featuring leaders from around the world in conversation with MBA students. Recorded live at the CEMEX Auditorium at Stanford Graduate School of Business, episodes feature insights on effective leadership, the values that guide it, and lessons learned along the way.

Lisa Su, the chair and CEO of Advanced Micro Devices (AMD), leads one of the world’s most influential technology companies, a pioneer in high-performance computing and designer of chips that power everything from cellphones to supercomputers.

Su joins Michael Liu, MBA ’25, to talk about what it takes to stay on the cutting edge of technology, the tremendous potential of artificial intelligence, and why her superpower may be her commitment to learning.

“Careers are very much by chance,” Su says. “The nice thing about my early career is I was lucky enough to have bosses who asked me all the time, ‘What do you want to be when you grow up?’ And I was like, ‘I don't know. Let me think about [it]...what I like to believe is the ability to learn at each step was what really helped me in my career.”

This conversation was recorded on February 24, 2025.

More Resources:

• Lisa Su

• GSB Insights

• View From The Top

If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society.

Chapters:

(00:00:00) Introduction

Kevin Cool introduces a summer spotlight on other podcasts, featuring View from the Top.

(00:00:59) Meet Lisa Su

Michael Liu introduces Lisa Su, AMD CEO, and highlights her career transformation.

(00:04:13) Growing Up & MIT Years

Lisa reflects on her immigrant upbringing and her journey through three degrees at MIT.

(00:05:43) Discovering Semiconductors

A part-time lab job at MIT ignites Lisa’s passion for chip technology.

(00:07:21) From Engineer to Leader

Lisa describes her transition from technical work to managing people and projects.

(00:11:19) Tackling Hard Problems

How curiosity and teamwork help Lisa embrace high-stakes technical challenges.

(00:13:40) Betting on Talent

Lisa recounts moments when she was given a chance—and how she now pays that forward.

(00:17:03) Becoming CEO at AMD

What brought Lisa to AMD and the unexpected call to lead the company.

(00:21:51) Strategy in a Turnaround

How AMD focused on high-performance computing and long-term bets.

(00:25:41) Cultural Shift at AMD

Lisa outlines how AMD’s culture became collaborative, ambitious, and learning-driven.

(00:27:19) AI & Global Tech Politics

The complex intersection of AI innovation and geopolitical regulation.

(00:32:37) Open vs. Closed AI Platforms

AMD’s open-source AI approach with NVIDIA’s more vertical model.

(00:38:54) Future Vision & Final Reflections

Lisa offers advice to MBAs and shares what she wants her legacy at AMD to be.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

As we celebrate the conclusion of the second season of the If/Then podcast, we present a bonus episode featuring Deborah H. Gruenfeld, the Joseph McDonald Professor and Professor of Organizational Behavior and a Senior Associate Dean for Academic Affairs at Stanford Graduate School of Business.

Gruenfeld, who appeared on the first season of If/Then in an award-winning episode about hierarchies and the nature of power, returned to the studio to share her thoughts on the value of academic research and its impact on individuals and organizations.

“The nice thing about research is that it provides tools and methods and an approach to learn about what’s true in the world, taking into account that what we learn from firsthand experience is not reliable,” she says. “Research helps us build a body of knowledge about what's actually true that we can trust.”

This episode was recorded on July 16, 2025.

Related Content:

• Deborah H. Gruenfeld, faculty profile
• Why Research Matters
• Why I Research: Findings Fueled by the Head and the Heart

If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society. Each episode features an interview with a Stanford GSB faculty member.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.