If/Then

Ilya Strebulaev, a professor of finance at Stanford Graduate School of Business and Alex Dang, MS ’14, a tech executive and innovation advisor, didn’t write their book, The Venture Mindset: How to Make Smarter Bets and Achieve Extraordinary Growth, for venture capitalists. “We wrote it for people who are located far away from Silicon Valley, thousands of miles away, and for people whose day-to-day professional job has nothing to do with Silicon Valley, with technology, with startups,” Strebulaev says on a new episode of the If/Then podcast. “Our world is changing very fast, and the future [will] require a very different type of decision-making.”For example: Instead of trying to avoid failure, VCs succeed by making numerous bets, ensuring that a few big successes can cover the many losses. “‘Home runs matter; strikeouts don’t’ is the first, and I would say foundational, principle of the venture mindset,” Strebulaev explains. Strebulaev also discusses why VCs look for ideas “outside the four walls” and why they bet on teams before ideas. In a volatile world, he recommends all leaders add the venture mindset to their toolbox. “I believe that many — not just small businesses, but many large companies — will be displaced, and soon, unless their leaders realize that they need to change their paradigm, how they think,” Strebulaev says. “This is where the venture mindset is particularly helpful.”Have concepts from one aspect of your life influenced another? Share your story with us at [email protected] Content:Ilya A. Strebulaev faculty profileThe Venture MindsetChapters:00:00 Introduction03:19 Meet Ilya Strebulaev and the Venture Mindset05:35 Why “Home Runs Matter, Strikeouts Don’t”10:04 Finding Ideas Outside the Four Walls12:02 AI, Competition, and Human Connection14:22 The Power of Saying No16:35 Decision-Making and the Cost of Missed Opportunities18:03 Why the Team Comes Before the Idea20:43 Is Venture Capital Always Good for the World?22:37 ConclusionSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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 Abrahams and 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 podcastMatt AbrahamsNir HalevyChapters:00:00 Introduction01:22 Understanding Hierarchies03:43 Signs of Broken Hierarchies05:43 Fixing Unhealthy Hierarchies06:56 Building Healthy Hierarchies10:05 Competition and Collaboration11:29 Communication and Hierarchies14:03 Construal Fit17:36 Humor and Competence19:47 The Final Three QuestionsSee 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 ConclusionSee 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 podcastMatt AbrahamsBrian LoweryChapters:00:00:00 Introduction00:01:14 Meaning vs. purpose00:02:14 How to find purpose00:02:50 Finding meaning through service to others00:04:49 How relationships shape identity00:05:54 The leader’s role in shaping others00:09:32 Self-awareness and psychological safety00:11:10 Respecting perspectives you don’t share00:12:23 Sincerity vs. authenticity00:13:28 Giving feedback that people can hear00:17:47 What it means to be a better human00:18:57 ConclusionSee 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 profileThird Millenium ThinkingStanford Legal PodcastChapters:00:00:00 Introduction00:01:23 The course, the book, & what motivated it00:04:06 Habits of mind for better decision-making00:06:20 Probabilistic thinking and intellectual humility00:09:57 An “opinion diet”00:12:16 Reasonable doubt, community, & collective judgment00:14:13 Scientific optimism and the problem of cynicism00:17:31 Why trust in science has eroded00:20:10 Law, science, & the value of procedure00:22:50 Steel-manning the other side00:24:58 Public policy as provisional problem-solving00:30:07 Deliberative democracy and informed public debate00:32:03 ConclusionSee 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 [email protected] Content:Douglas Guilbeault faculty profileRead "A Simple Threshold Captures the Social Learning of Conventions" hereChapters:00:00:00 Introduction00:01:40 Why human learning matters for AI00:05:03 Satisficing and the limits of optimization00:06:41 Why LLMs learn differently from humans00:09:58 The stakes of AI hype00:13:11 “Humanity has had a good run”00:15:19 Intuition, insight, & conceptual leaps00:17:38 Beyond statistics: metaphor, vibes, & reasoning00:19:39 A simple rule for social learning00:21:18 Is there a ceiling for AI?00:23:00 Randomness, disorder, & the path to insight00:25:00 What an optimization mindset leaves out00:27:54 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 profileWhat’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 Introduction00:01:32 The difference between now & previous periods of innovation00:02:29 Two scenarios for AI-driven growth00:06:18 The case for business-as-usual00:11:06 Weak links and the limits of automation00:17:53 What the models are showing about growth00:19:58 The economics of abundance00:25:29 The weak-link model’s timing & possible adaptations00:27:51 Who gains in an AI economy?00:29:55 Catastrophic risk and the downside of acceleration00:34:31 The downsides of the weak link model00:36:38 Meaning, identity, and human value00:39:55 Leisure in a post-work world00:41:43 What the next generation may inherit00:44:07 ConclusionIf/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 [email protected] Content:Huggy Rao faculty profile The Friction ProjectHow to become a friction fixerChapters:00:00:00 Airport baggage claim, waiting, & good friction00:03:20 Introduction00:03:48 What friction means in organizations00:05:42 Where friction comes from00:07:52 Scaling through smart subtraction00:08:24 DropBox’s approach to meetings00:10:45 The problem with meetings00:13:53 What good friction looks like00:16:56 Friction, trust, & institutional legitimacy00:19:31 Why Huggy Rao started studying friction00:22:20 ConclusionSee 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 [email protected] 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 thinking00:03:18 Introduction00:04:24 Questioning conventional wisdom00:04:57 Rethinking the debt-to-GDP ratio00:08:21 A finance perspective on national debt00:10:36 Why theory matters before alarm00:12:38 Regulation, charlatans, & consumer interests00:16:22 Licensing, certification, & competition00:19:51 The cost of pushing back00:21:16 Building organizations that welcome dissent00:24:59 ConclusionIf/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 [email protected] Content:Christian Wheeler faculty profile In a Polarized World, an Open Mind Can Hurt Your ReputationYou May Not Be Who You Think You AreClass Takeaways — How to Build Connection Through Better ListeningChapters:00:00:02 Tattoos, identity, & personal evolution00:03:26 Introduction00:03:59 Why identity matters00:04:56 Identity relevance & its implications00:08:03 Why openness to the other side gets punished00:10:57 Identities vs. opinions00:13:53 The power of individuation00:15:53 How to break the cycle of polarization 00:19:41 Organizational applications00:23:26 ConclusionIf/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.