If/Then

4.9 (32)
Management
Biweekly

How do we lead with purpose, make better decisions, and navigate an uncertain future? On If/Then, Stanford GSB faculty break down cutting-edge research on leadership, strategy, and more, exploring enduring questions and the forces reshaping business and society today, from AI to geopolitics. Hosted by senior editor Kevin Cool.

2d ago

Inside the Venture Capital Mindset

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 ifthenpod@stanford.edu. Related Content: Ilya A. Strebulaev faculty profileThe Venture Mindset Chapters: 00:00 Introduction 03:19 Meet Ilya Strebulaev and the Venture Mindset 05:35 Why “Home Runs Matter, Strikeouts Don’t” 10:04 Finding Ideas Outside the Four Walls 12:02 AI, Competition, and Human Connection 14:22 The Power of Saying No 16:35 Decision-Making and the Cost of Missed Opportunities 18:03 Why the Team Comes Before the Idea 20:43 Is Venture Capital Always Good for the World? 22:37 Conclusion See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Oct 28

Think Fast Talk Smart: "Power Play: Successfully Navigate Power, Status, and Influence at Work"

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 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.
Sep 23

An AI@GSB Special: Demis Hassabis Thinks We’re in the ‘Foothills of the Singularity’

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.
Aug 26

Think Fast Talk Smart: "What Other People Teach You About Your Communication"

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 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.
Jul 8

Stanford Legal: "The Importance of Critical Thinking and Civil Discourse in Today's Polarized World"

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 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.
Jun 25

What AI Can’t Do — And Why

“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 profileRead "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.
Jun 10

Our AI Future: From Abundance to Apocalypse

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 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.
May 20

The Art of Friction

“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 ProjectHow 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.

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4.9

out of 5

32 Ratings

Great listen for Data/AI Enthusiast College Students

02/27/2024

Mika_Montonen

Referred by the Me, Myself, and AI podcast team! Loved the connection. Thank you guys
Thought provoking

02/21/2024

Jenny Luna

Fascinating concepts and interesting ways of pointing out how research applies to many facets of the business world. Great music
Applicable insights, refreshingly grounded in research

02/04/2024

J Hankes

This podcast elegantly shares insights and implications drawn from the hard work of building new knowledge from the often-less-than-flashy world of tested research. This is a breath of fresh air to someone eager to be reminded of our capacity to study complexity and discover insights that transcend catchy narratives and myopic agendas. Such a fun listen!

How do we lead with purpose, make better decisions, and navigate an uncertain future? On If/Then, Stanford GSB faculty break down cutting-edge research on leadership, strategy, and more, exploring enduring questions and the forces reshaping business and society today, from AI to geopolitics. Hosted by senior editor Kevin Cool.