unSILOed with Greg LaBlanc

Today's AI has been designed using insights from how humans learn and think about the world. Are there certain psychological lessons we can glean from these artificial minds to further our understanding of human ones? 

Tom Griffiths is a professor of information technology, consciousness, and culture at Princeton University. His books, The Laws of Thought: The Quest for a Mathematical Theory of the Mind and Algorithms to Live By: The Computer Science of Human Decisions, explore how algorithms and mathematics can be used to understand the human mind, and how it differs from AI. 

Tom and Greg discuss the origins of the surprising convergence of psychology and computer science over the last 50 years and delve into the work done by the interdisciplinary minds who made it happen. They also cover how psychology and linguistics impact the current world of machine learning and AI. 

*unSILOed Podcast is produced by University FM.*

How do we build good inductive bias into AI systems?

26:07: How do we build good inductive bias into these systems? And at the moment that is being engineered to some extent by doing things like synthetic pre-training, where you might pre-train on data which is not the human language data but data that you think is quite good data for shaping the kinds of things that your neural network is going to be biased towards. And then there are some other more sophisticated methods for doing that. In my lab, we use a method called metalearning, where you're explicitly creating a neural network that has initial weights, that has some sort of initial associations that it's already formed, that are going to make it easy for that model to be able to learn from small amounts of data.

Neural networks vs. human learners

23:00: One of the big differences between even the fancy neural networks that we have today and human learners is that human learners learn language from far less data than our neural network models do.

What is a neural network?

18:30: The way I think about neural networks is that they're a tool for thinking about computation in spaces, a way of mapping one space to another based on the information that you've received that allows you to then build up to more and more complex computations.

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When the concept of ‘gamifying life’ comes up, scoring is transparent and portable but strips nuance, creating a gap between what’s measurable and what matters. When codifying everything through metrics, massive amounts of nuance is lost, so how can we utilize game theory without reducing everything to a high score?

C. Thi Nguyen is a professor of philosophy at the University of Utah. He is also the author of the books The Score: How to Stop Playing Somebody Else's Game, The Routledge Handbook of Philosophy of Games, and Games: Agency As Art.

Greg and Thi discuss the differences between genuine gameplay and institutional metrics and gamification. Thi explains Huizinga’s “magic circle” concept, where games create a temporary space with altered meanings and low real-world stakes, enabling intense striving without value capture. Drawing also on Bernard Suits, Thi frames games as voluntarily taking on unnecessary obstacles and distinguishes achievement play (valuing winning) from striving play (valuing the struggle), separating these from intrinsic vs extrinsic motivations. 

They discuss how clear scoring is transparent and portable but strips nuance, creating a gap between what’s measurable and what matters; transparency can reduce bias yet undermine expertise. Examples include social media likes, quotas, education metrics, sports rule changes, cooking “recipe vs dish,” and academia’s citation and ranking pressures.

*unSILOed Podcast is produced by University FM.*

The paradox on inefficiency

08:31: To play a game is to voluntarily take on unnecessary obstacles,  to create the possibility of struggling to overcome them, which I find, it’s got to be to be inefficient, but interestingly not fully inefficient. So we're not trying to be as inefficient as possible. One of the ways to put the paradox of games is we take on an inefficiency and then we try to be as efficient as possible inside that inefficiency.

The trap of simple scoring

04:00: One of the biggest differences between real games and the kinds of gamifications of work and education that we find is that gamifications are attempts to modify things into line with simple scoring systems that occur continuously with the rest of life that have direct connections to valuable resources.

Collapsing the magic circle

05:08: Twitter likes and citation rates and gamified work are modifications of something that has preexisting value, preexisting activity. So I think the important thing about Twitter, X, Facebook is those scoring systems don't occur in a magic circle. They don't occur in a space with separated meaning. They modify our activities in the real world and change our attitudes and interactions over real world resources. So I think exactly like this easy glide from games or grudge to like we should gamify everything ignores one of the most crucial elements, which is some version of this magic circle is basically active in a lot of genuine gameplay, but is completely inactive, is completely canceled. We have the superficiality of scoring systems and game-ishness, but deep down we don't have the core guts of transferring into a temporary alternate meaning space whose meanings kind of can be held relatively isolated.

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While philosophers have long wrestled with questions about technology’s impact on humanity, these questions have taken on a whole new level of urgency and significance with the rise of AI, smartphones, and the Internet. It’s more pressing than ever now to ask: What does it mean to be human? 

Christine Rosen is a senior fellow at the American Enterprise Institute and a fellow at the University of Virginia’s Institute for Advanced Studies in Culture. Her latest book, The Extinction of Experience, delves into how modern technologies are reshaping what it means to be human by mediating experience, promising convenience and control while subtly narrowing choices and changing social norms. 

Christine and Greg discuss the trade-offs of this digital age: as friction, risk, boredom, and unstructured time disappear, so do the skills and forms of attention that develop through direct interaction with other people and the world. They argue that many of these technologies offer safe simulations of connection that can weaken real relationships, and explore what a renewed humanism would look like.

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Why technology removes the friction that makes us human

07:37: This is the really seductive thing about these technologies is that they do both at the same time, and they do that by promising us control. And they give us control. If I am having a FaceTime conversation with someone and it gets awkward, or I don't want to continue anymore, I can just press a button and that person disappears. If I'm standing with them face-to-face, I can't really do that. I have to adapt to the situation. I have to deal with it in a completely different way. I would argue a more human way with a lot of friction. So then I learn certain skills of how to be a better human being in those situations. The mediating technology flattens, makes easier, convenient, and more control is promised, and it gives us that.

The hidden value in boredom

28:48: Boredom opens up all kinds of meandering paths in the brain that take you to really interesting places if you let it.

Protecting human relationships in the age of AI

20:44: We are at a crucial moment right now, particularly with the huge push to integrate AI into so many aspects of life, education, work, home, your daily life. I just think that we have this opportunity now to really be clear about what it is we value in human relationships and what makes it unique and distinct and important to protect those relationships.

Why friction and failure are essential for human development

11:21: We learned by failing. We learned with a lot of friction. We learned by having arguments and fights and all that stuff. If kids today don't get that experience as kids in a safe environment with people who love and care for them, when they become adults it is scary because you have to practice. So I would say these are important human skills, and we can no longer take them for granted because there are alternative things to do, like never talk to another human being. But ultimately, I think rates of loneliness and isolation and anxiety suggest that that isn't really the way most people want to live their lives.

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How is modern self-knowledge acquired? In what ways can ‘yoga of the mind’ help you find and explore new thoughts and thought processes, giving you ongoing courage to confront discomfort and realign consciousness beyond ego narratives?

J. Eric Oliver is a professor of political science at the University of Chicago and is also the author of several books. His latest titles are How To Know Your Self: The Art & Science of Discovering Who You Really Are, Democracy in Suburbia, and Enchanted America: How Intuition & Reason Divide Our Politics.

Greg and Eric discuss Eric’s popular Knowing Yourself course, combining neuroscience, Buddhism, philosophy, psychology, and reflective exercises. Eric explains the evolution of the class from abstract texts to practical self-inquiry aimed at expanding students’ vocabulary of lived experience, identifying unhelpful mental loops, and cultivating empathy by seeing the self as layered processes shared with other beings. He connects this work to his earlier research in Enchanted America on intuition, conspiracy beliefs, and the political rise of intuitionism, arguing that weakened institutional authority and information overload amplify anxiety. 

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The Gold Star illusion is not an end all be all

30:15: Most high achieving, intellectually engaged people, I think, are brought up with this Gold Star illusion, which is this thing that if I could just collect all of my gold stars, you know, go to the right schools, get the right job, find the right person, buy the right house, then this sort of happily ever after scenario awaits me. And then what most of us find is that even after we collect all these gold stars, the neurosis and anxieties and miseries don't go away. If anything, they become more profound. And so part of what I'm trying to do, at least with my undergraduates, is sort of say, okay, it's helpful if you can sort of, even if you're going to be on the Gold Star trajectory, because that's so powerfully inculcated into you to begin to realize that that's not going to be the end all be all. Because when you get to the end of that gold star rainbow and you realized, “oh, is this all there is?” You won't be at such a loss, and there won't be necessarily the same level of crisis that awaits you.

There is no self as a noun, we are verbs

36:56: There is no self as a noun. We are verbs, we're processes, so we're continually unfolding. And this is great news because we're not stuck in any way. You're not a bad person, you're not a fixed person.

Why the information age makes us anxious

20:06: With the explosion of our information technologies and the ability for someone who has a conspiracy theory to suddenly post things online and have just enormous reach that 20 years ago they wouldn't have, suddenly floods our discourse space with these alternative paradigms and these alternative ways of understanding the world, and the fact that we are so saturated now with information from around the globe. So how can we not be anxious? 

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What do particle physicists and Wall Street traders have in common? How did finance become more like physics, and how is physics now becoming more like finance?

Emanuel Derman is an emeritus professor at Columbia in financial engineering and the author of several books, including My Life as a Quant: Reflections on Physics and Finance and Models. Behaving. Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life. His work examines the entanglement of physics and finance, using memoir to reveal hidden truths about the theories and models practitioners rely on. 

Greg and Emanuel discuss his transition from physics to Wall Street, revealing that he found finance to be more social and creative. They also explore how early quant work required both theory and hands-on programming, what distinguishes models from theories, and why, despite some superficial similarities, the fields of finance and physics couldn’t be more different.

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Financial models require confidence without hubris

29:29: In my life as a quant, I think I said you had to be cocky when you were using models and push them as far as you possibly could, but stop short of hubris, and I think that's important. You ought to understand that your model isn't going to be correct. In the end, the world is going to violate it.

When physics meets social sciences

09:35: I think to some extent they [psychists] confuse accuracy with point of view. Even progressive theories get more and more accurate. Newton's laws aren't as accurate as relativity, but they still, both theories, the one just does better than the other, but they still have this nature of saying, let me describe the way the world works rather than, let me make an analogy.

Why model builders must explain where models fail

30:46: There's a clear distinction between concentrators to tell the people that use it that this is where it's going to fail, as best I can see. And they'll use it in this regime. And these are the assumptions I'm making. Don't just let them run wild with the formula. I think traders are smarter now and more numerate and maybe understand this better, but I think that's important.

Why financial engineers need perspective beyond mathematics 

28:13: I don't think one should be teaching philosophy necessarily, but I think one should learn enough to know about the history of finance and to be able to back off a little and look at what you're doing. Not just, I don't know. I have a feeling more and more of the programs focus on mathematics and behavioral psychology.

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Romantic relationships are something uniquely human — we form attachments and perceive compatibility in ways no other species does. So what explains the idiosyncratic preferences people have for one potential partner over another? And why have popular conceptions based on evolutionary psychology been wrong about when it comes to how humans choose their mates? 

Psychology professor Paul Eastwick is the head of UC Davis’ Social-Personality Psychology program and the director of the Attraction and Relationships Research Lab. His book, Bonded by Evolution: The New Science of Love and Connection, challenges society’s core assumptions about attraction and compatibility, and presents new findings on the key to long-lasting commitment. He also co-hosts the podcast, Love Factually, with his colleague Eli Finkel, which explores the science of relationships through film. 

Paul and Greg discuss how a distorted view of evolutionary psychology has perpetuated inaccurate ideas about dating and relationships, the effect online dating has had on intensifying competition and gender differences, and some key tips for building strong, long-lasting connections. 

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Why dating apps can’t replace real romantic connections

39:57: The apps make you think like a romantic connection is right there. Like maybe it will be tonight. I would encourage people instead to think about what is it like just to hang out with other people and give the romantic possibilities some time to fall out of those networks a little bit more organically, a little bit more naturally. It takes a while. Like it can take quite a long time, especially like if we haven't been tending to our networks recently, but nevertheless, like this is at least an approach that people should be supplementing with their online dating if, if they're going to continue to use the apps.

​​Why are some couples happy and some are not?

22:46: Compatibility, how well two people fit together. That is probably explaining the lion’s share of why some couples are happy and some couples are not. Rather than this idea that like, oh, you got a good long-term partner, that's probably not the best way to think about it.

Compatibility is something couples build together

25:17: Compatibility can be many, many things. It can be like, we seem to get along and coordinate well. It could be about our easy flowing conversation, but it also could be about how we get through the day. And often that's what relationships are. It's an interdependent web of goals and preferences and values that two people negotiate together. And it's very hard for people to know how that negotiation is going to turn out until they really dig in and start to try to do it.

The evolutionary mismatch behind modern dating

45:44: What I think is deeply ironic is that some of the earliest evolutionary psychological findings happened to be the ones that reinforced the view that really fits this hierarchy idea, the mismatch component of it. So it's like, I love the idea of the evolutionary mismatch, thinking deeply about the environment in which we evolved. My problem is like a lot of the early ev psych ideas actually weren't doing that all that, all that well, that in reality, right? We evolved in small groups. You got to know a limited number of potential partners. There were going to be other people involved trying to shape, you know, who you spent time with and who you got to meet. It wasn't this dramatic marketplace of inequality.

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What if the tale of Genesis were reframed as a story of humanity’s ascent into awareness of mortality and entropy? How are both connectedness and a “mattering project” key to flourishing as an individual?

Rebecca Goldstein is the author of several fiction and non-fiction books, including The Mattering Instinct: How Our Deepest Longing Drives Us and Divides Us, 36 Arguments for the Existence of God: A Work of Fiction, Plato at the Googleplex: Why Philosophy Won't Go Away, and The Mind-Body Problem.

Greg and Rebecca discuss how the ideas in her new book, The Mattering Instinct, trace back to her novel, The Mind-Body Problem. Rebecca details a long-developed theory of human motivation: beyond survival and pleasure, humans are “creatures of matter who long to matter,” driven to justify themselves in their own eyes (homo justificans). To Rebecca, this is linked to self-reflection, theory of mind, and existential “absurdity.” This episode will outline some mattering strategies and also discuss personality links, ethics, and concerns about AI.

*unSILOed Podcast is produced by University FM.*

We are creatures of matter who long to matter

08:21: What we are are creatures of matter who long to matter. I love that we can do that in English. You know, we can't do it; it can't be replicated in other languages. But thank goodness for English, two amazing words: the noun matter and the verb matter.

Why everyone needs to feel like they matter

04:23: Look, everybody needs to feel like they matter. Then there's a great diversity of ways in which we might try to prove to ourselves that we matter.

The human search for values

15:11: Entering into this world of entropy, where everything eventually runs out of energy and does die, the universe itself will run out of energy and thermal equilibrium that awaits the universe, with that stepping out of paradise. They took on the burden, but the dignity of being human, of trying to justify becoming Homo Justific, becoming creatures who are in search of values that will justify them in their own eyes. We come up with a whole bunch of values, and we disagree tremendously about these values, but there's something so grand about being creatures who need values in order to be able to  live with themselves, even if they're bad values, but that we bring values into the universe because we are creatures longing to matter.

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A key precondition for democracy is civic trust and commitment to common goods; polarization and party identity undermine this, worsened by modern communication technologies that enable separate realities.

Josiah Ober is a professor of Political Science and Classics at Stanford University and also the author and co-author of several books about Athens, Civics, and Ancient Democracy. His latest title is The Civic Bargain: How Democracy Survives. 

Greg asks Josiah about his work linking ancient Athens to modern democracy and organizational design. Josiah argues that political science necessarily blends positive and normative theory, joining rational self-interest with ethical reasoning to secure both stability and the good. He also compares firms and states as purposeful organizations governed by rules, incentives, and norms, noting that democracies struggle to scale but can outperform hierarchies by aggregating dispersed knowledge if institutions align incentives and citizens share information. Josiah emphasizes civics as teachable skills—listening, bargaining, and positive-sum compromise. He makes an appeal for renewed civics education informed by history and classical thinkers, including a rehabilitated view of the sophists and strategic reasoning.

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Why democracies know more than hierarchies

14:58: The democratic system, intrinsically, knows more than a highly hierarchical boss centered system, simply because those who see themselves as citizens have reason to share what they know. Those who are subjects have reasons to not share what they know. Therefore, it is possible for a democracy for reasons that, you know, Friedrich Hayek talked about in terms of why markets work, because all of that information comes together in, you know, producing a price, it is possible for well-structured democracies to bring in a great deal of information. From a great deal of people who have very different experiences, know different things, to solve the problems that they need to solve.

Does democracy only work when the design is right?

15:45: You have to have the right kind of organization, not only of, sort of voting and so on, but of incentives for people to bring what they know to the right place at the right time, not to the wrong place at the wrong time. And that is hard to do. You get it right and you get this tremendous success. You get it wrong and it does not work very well. 

Politics should work like buying a car

32:22: When we go into the political regime space nowadays, it's that, well, compromise is bad now. We gave up, they won. The imagination now of politics is something like a football game in which there's a winner and a loser, and the winners cheer and the losers cry. But that's not what politics is. It is much more like buying a used car.

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How important are relationships and the feeling of being loved to human happiness? How have the fields of happiness studies and relationship studies converged? 

Sonja Lyubomirsky is a professor of psychology at the University of California, Riverside. She is also the author or co-author of the books How to Feel Loved: The Five Mindsets That Get You More of What Matters Most, The How of Happiness: A New Approach to Getting the Life You Want, and The Myths of Happiness: What Should Make You Happy, but Doesn't, What Shouldn't Make You Happy, but Does.

Greg and Sonja discuss her shift from happiness research to her co-authored book with Harry Reis, How to Feel Loved. Sonja explains that many happiness interventions (gratitude letters, kindness practices, and variations like texting gratitude vs. social media posting vs. private writing) work largely because they increase feelings of love and connection

They also discuss why listening is difficult, with Sonja sharing her experience in a Tel Aviv listening workshop, and the need for compassion and a growth mindset. Other themes include the Michelangelo effect (helping others become who they aspire to be), balancing sharing and listening (avoiding monologues or interrogations), appropriate vulnerability and gradual self-disclosure, and the “multiplicity” mindset of seeing people as complex quilts of good and bad traits to reduce harsh judgment. 

The episode also considers whether people can feel loved without being loved, including AI companions that can mimic excellent listening but lack a genuine open heart, and the risk that some people may substitute simulated relationships for real ones. 

*unSILOed Podcast is produced by University FM.*

What’s the distinction between being loved and feeling loved?

07:42: A lot of us are loved, but we do not feel loved. So we might have, we might know that our partner loves us or child, or a family member or friend or colleague. But we do not really feel loved. And when you think about it, feeling loved is what really matters even more, right? Because if, you know, if you love me, but I do not feel loved by you, it is almost like you do not love me, right? Like, because I am not really sensing that, and so feeling loved is really important. That is what really matters to happiness.

The key to feeling loved is really to be known and to know the other

10:16: The key to feeling loved is really to be known and to know the other, and we get known by taking the wall down a little bit. And I get to know you if I help you take your wall down. How do I help you take your wall down? By showing curiosity. Then hopefully you will start to open up a little bit. I show even more curiosity. I ask you questions and I l truly listen, not really just try to fix it or help you or tell my own story. I just listen to learn.

The first step to feel more loved

09:11: If I want to feel more loved, the first step, which may sound counterintuitive, is to help the other person feel loved first. You go first. I go first. The first step is to show genuine curiosity in the other person, in their inner life and the details of their day, their dreams, goals, values, fears. We all want that. We want to be seen, we want to be heard, and we do not get genuine curiosity very often. When was the last time you remember telling a story about yourself and the other person was so curious they could not wait for you to finish the sentence? It is rare. When it happens, it is priceless. That is such a gift to someone, to show authentic curiosity in them. It has to be authentic because you cannot fake it. That is the first step. You help the person be seen by showing curiosity in them, and that helps them open up more.

Real connection requires both listening and sharing

18:48: If you only share, it is a monologue. You are spouting off. If you only listen, then it is an interview. It is an interrogation sometimes. You really need to do both. They go together. That is where the emotional intelligence comes in. Because when you are sharing, the entire time you are sharing, and we all know people who do not do this, they go off and they seem to not see any cues that the other person is not interested in continuing the story.

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How could AI shift medical value toward primary care relationships if pattern-recognition specialties are more automatable? What would people prefer if given the choice between discussing their problems with a human or with non-judgmental empathic AI?

Allison J. Pugh is a Professor of Sociology at Johns Hopkins University and the author of several books. Her most recent works are The Last Human Job: The Work of Connecting in a Disconnected World and The Tumbleweed Society: Working and Caring in an Age of Insecurity.

Greg and Allison discuss Allison’s newest book and her concept of “connective labor,” defined as the relational practice of seeing another person and having them feel seen. They also contrast this idea with more individual-centered ideas like EQ. Allison argues that this type of work is reciprocal, widespread across roles (therapists, teachers, chaplains, primary care, managers, service work), and increasingly important as the economy shifts toward requiring more “feeling.” Allison also talks about how AI is being used in new ways to help automate different aspects of different jobs, and along with that come connected effects like the rise of automated medical scribes amongst the medical community, but also the drastic reduction of interns and the near elimination of that valuable aspect of education and job training for an intern’s future professional life. They also discuss how the different efficiency tools can backfire because of the increased need to oversee and validate automated output.

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Why friction is essential to human connection

17:26: Part of the relationship with another human being involves the friction of not being able to control what they say, of running up against their disagreement or conflict or even tension, or they have their own ideas, their own desires. And that is part of making our way through this world, and it is a really important part of being in community, in relationship with other human beings. And that is what chatbots do not give us. They give us no friction.

AI is mirror, not a relationship

17:08: So with chatbots, you are not really experimenting how to be with another human being. You are instead experimenting with a mirror, and that is just not going to have the same powerful impact.

Who gets humans, and who gets machines?

12:27: The idea that technology will be better than nothing, I am afraid, will not lead to greater opportunities to be seen, for less advantaged people. Instead, they will just have machines seeing them, and the rich people get humans seeing them, and that is an inequality that I find kind of tragic.

Seeing people is a leadership skill

49:52: When people have a chance to kind of express their values at work, figure out who they are and have their values kind of enacted in their work and kind of basically attach a purpose to what they are doing, a more transcendent purpose than just kind of earning the paycheck, it translates into a kind of deep meaningfulness, and that is part of the outcome of connective labor. And so it is really worth it for managers to get good at this because it enables people, the people they are seeing, to figure out what matters to them and to find that in relationships at work. That is a path to meaningfulness that can be very important.

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