Why do our most complex systems—from financial markets to corporate behemoths—consistently produce outcomes that nobody intended, and what forgotten science might hold the key to fixing them?

Dan Davies is an economist and author of the books, Lying for Money: How Legendary Frauds Reveal the Workings of Our World and most recently, The Unaccountability Machine: Why Big Systems Make Terrible Decisions - and How The World Lost its Mind. 

Dan and Greg discuss the complexities of fraud in financial systems and why no individual seems accountable for major financial crises, how the historical and intellectual foundations of cybernetics and systems thinking can be applied to improving organizational design, and the role of information theory in management.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Payment protection insurance
• “Canadian university loses $10m in phishing scam” | BBC
• “A Mathematical Theory of Communication” by Claude Shannon
• Cybernetics: Or Control and Communication in the Animal and the Machine by Norbert Wiener
• Alan Turing 
• Kurt Gödel
• Stafford Beer 
• Alfred D. Chandler, Jr.
• Michael C. Jensen
• W. Ross Ashby

His Work:

• Lying for Money: How Legendary Frauds Reveal the Workings of Our World
• The Unaccountability Machine: Why Big Systems Make Terrible Decisions - and How The World Lost its Mind
• The Brompton: Engineering for Change

Fraud thrives where trust exists

13:58: If you want to commit a big fraud, you don't go somewhere where there's low trust. You go somewhere where, as long as you show up, wear a nice suit, smile, and say please and thank you, people will assume that you're honest. But the thing is, that's what you want to do if you want to run a legitimate business too. So, people always say that the cost of fraud is never the amount of money that's stolen; it's the amount of legitimate business that doesn't get done. And that's just really saying that trust is an incredibly efficient way of organizing your economy compared to checking. Checking and trust are basically the only two kinds of technologies we have to ensure the integrity of information. And of the two of them, trust is a lot more efficient.

How fraud disrupts an economy

03:48: Fraud happens when not only does your assumption of perfect information break down, but there's some actual anti-information there. There's some actively false and misleading information that's been injected intentionally.

Why investors and economists lead in a data-driven era

58:40: A lot of the reason why economists rule the world in policy is the same reason why more and more companies are run by their investors or their investor relations departments. It's because they collect the data, and the economists collect the numbers that are used to make up the world of facts. 

Why have philosophers historically failed to think seriously about privacy? How do invasions of privacy really impact a person? What do we give up when we let our data be freely commoditized by Big Tech companies without being fully aware of how they’re doing it?

Carissa Véliz is an Associate Professor in Philosophy at the Institute for Ethics in AI, a Fellow at Hertford College at the University of Oxford, and the author of multiple books including most recently, The Ethics of Privacy and Surveillance.

Greg and Carissa discuss why philosophers have historically neglected privacy as a subject, the modern implications of privacy in the digital age, and the ethical issues surrounding data collection and targeted advertising. Carissa argues for a nuanced, objective approach to privacy that considers its deep evolutionary and societal roots. They touch on the tension between convenience and privacy, the importance of legal frameworks, and the responsibilities of both individuals and companies in safeguarding personal data.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Louis Brandeis
• Judith Jarvis Thomson
• Rima Basu
• Civil Inattention
• Paul de Man
• 23andMe

Guest Profile:

• CarissaVeliz.com
• Faculty Profile at Hertford College
• Faculty Profile at Oxford University
• Wikipedia Profile
• LinkedIn Profile
• Social Profile on X

Her Work:

• Amazon Author Page
• The Ethics of Privacy and Surveillance
• Privacy Is Power: Why and How You Should Take Back Control of Your Data
• Oxford Handbook of Digital Ethics

The hidden risks of sharing genetic data

34:40: Most people don't really realize what it means to give away your genetic data. Genetic data is something so abstract that I don't think our psychology is built to understand it. It's not something you can touch or you can see. I can't visually show it to you, I mean, except in a very abstract form. And so I don't think people think it through. I think in a society in which we are very respectful of private property, it's very intuitive to think that if we make privacy a question of private property, then we are being respectful towards privacy. And it just doesn't work that way, because when I sell my genetic data to one of these companies, I'm selling the data of my siblings, my parents, my kids, even my very distant kin who might get deported, who could have their insurance denied. So it's not a personal thing.

Privacy is a protection against possible abuses of power

06:09: Privacy is a protection against possible abuses of power. And as long as institutions are institutions, and people are people, there will always be that temptation to abuse power. We can see this very clearly because people who are more vulnerable to abuses of power tend to care more about privacy.

Can consent in data co-exist?

50:52: Consent in the data world just doesn't exist because it's not informed. You have no idea what they're doing with your data or where your data is going to end up. And it's not because you're uninformed; no data scientist would know it either. It's because of the way the data market works, and it's not really voluntary because if you say no, then you can't use the service, and not using the service might mean not getting a job or not getting an education. So, we need to change the kind of framework, and I propose an opt-in framework, in which you can opt in to have certain kinds of data collected, and that's effortful, and you only have to do it once.

Navigating privacy in a digitally-driven world

38:07: As long as the data exists, there's already a privacy risk. And that was my point with the iron law of digitization—that when you turn the analog into the digital, it might seem like a very neutral thing to do, but it's not because you turn something that wasn't trackable into something that's taggable, and that means it's being surveilled. That's what it means to surveil, to track something. And so, when we turn the analog into the digital, we're doing something very morally significant.

What effects will generative AI have on coding and software engineering? Will it make anyone a coder? Will it just turn software engineering into copy/paste exercises? How will the top coders use AI to hack their own efficiency and productivity, and why is it so hard for the large tech companies to do the same things that the smaller ones do?

Clive Thompson is a journalist for the New York Times Magazine and Wired as well as the author of multiple books, including Smarter Than You Think: How Technology Is Changing Our Minds for the Better and Coders: The Making of a New Tribe and the Remaking of the World.

Greg and Clive delve into the cultural and societal impacts of the rise of coders, exploring how the coding mindset infiltrates various aspects of life and business. They also discuss the nature of work in software engineering, the shift towards iterative and agile methodologies, and the potential future shaped by generative AI and its implications for the field. Clive explains the paradoxes of efficiency, the challenges of maintenance over creation in coding, and how his life experience and interests converge in his upcoming book about cycling across the United States and the future of mobility. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Max Weber
• Neil Postman
• Samuel Taylor Coleridge
• Paul Graham
• Ray Ozzie
• Jeff Atwood
• Reid Hoffman

Guest Profile:

• CliveThompson.net
• Wikipedia Profile
• Social Profile on X
• Profile on LinkedIn

His Work:

• Amazon Author Page
• Smarter Than You Think: How Technology Is Changing Our Minds for the Better
• Coders: The Making of a New Tribe and the Remaking of the World
• Wired Articles

Why do coders need an intense level of focus? 

If this thing happens [in coding], it will change this other thing. If that thing changes, this thing over here has to happen, and that's also reliant on this other thing. And it's so hard to get the structure of this in your head that you might spend several hours just looking at what you're trying to do, just thinking about it, sort of, getting it in your head. And when it's finally there, then you can begin to do the work. And of course, a couple interesting things fall out of this psychology. One is that you want to stay there. It took you three to four hours to get there, so you don't want to leave. So, you want to stay there for 10, 15, 20, 48 hours. 

The huge problem with managing coders.

[18:15] This is a huge problem with managing coders is that they love learning, in a weird way. You would argue, isn't this an ideal employee? Someone who is eager to learn. Constantly learning new things. Very few employees are like, “I am just omnivorous in my spare time when I'm not being paid, I'm going to do more of this.” I mean, how many accountants at your company go home, and then from eight o'clock at night to two in the morning, do more accounting for fun, just voluntarily? That's a coder, right? And what they're doing is they're going home, and they're doing crazy new forms of software that they're not really allowed to do at work, but they often try and bring that in, and they'll be like, “I'm now obsessed with this framework. Hey, boss, can we use this? And it’s like, “No! That framework is experimental and not reliable, and I want you to do the same old boring thing we've been doing for 30 years, because that is reliable.” And this is just a very hard thing. There's an excitement in the craft that a lot of software developers have that's not what the job requires.

An interesting analogy between law and coding

That's a great analogy that I'd never heard or thought of before, which is that law needs to be patched the way that software needs to be patched. Because it's the same challenge, which is that [in] writing code and writing law, you're trying to create a system that other people are going to use. Humans are going to use it. And so you, the author of the law, or you, the author of the code, have to try sitting at your desk to imagine all the things that those dozens, hundreds, thousands, millions, or billions of humans will do with this system. And you can't. There's no way you can. So, you have to just put it out there and watch and see what they do, and then fix it as it goes, basically. And, of course, the more critical the system, or the less critical system, the more or less you can get away with.

The mental character of coding is closer to that of an artist than it is to many other forms of engineering.

Coders hate being interrupted, and that's part of why they're regarded as being such irascible weirdos. [It] is like, if you tap them on the shoulder, they'll bite you.There's something delightful about that mentality of focus. There's something maybe even [to] be learned from it. It's one of the reasons why I realized the more I talked to coders about their attentional needs, and the sweep and drama, and a sort of, epic mental toil, that it reminded me of novelists, of artists, of poets, of temperament. The mental character of coding is closer to that of an artist than it is to many other forms of engineering.

What more can be learned about a topic like the origins of economic growth that has been covered so extensively? When pulling back and looking at all the connected threads, is there an order in which things must happen to spark the change?

Mark Koyama is a Professor of Economics at George Mason University, Research Associate at the Centre for Economic and Policy Research (CEPR), and Mercatus Center, Senior Scholar. He is also the co-author of two books, How the World Became Rich: The Historical Origins of Economic Growth and Persecution and Toleration: The Long Road to Religious Freedom.

Greg and Mark discuss the recurring interest in the origins of economic growth and the Industrial Revolution. Mark lays out the various theories and factors that have shaped economic development across different regions and historical periods, such as geography, demography, culture, institutions, and political conditions. Greg asks why some regions like Europe succeeded in industrialization while others did not, and the role of colonialism in shaping global economic dynamics. Mark also offers insights into the ongoing relevance of economic history in understanding contemporary growth and innovation.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Walt Rostow
• Daron Acemoglu
• Demography
• Malthusianism
• Reformed Christianity
• Douglass North
• Mughal Empire
• Paul A. David

Guest Profile:

• Faculty Profile at George Mason University
• Mercatus Center Profile
• Social Profile on X

His Work:

• Amazon Author Page
• How the World Became Rich: The Historical Origins of Economic Growth
• Persecution and Toleration: The Long Road to Religious Freedom
• Newsletter | MarkKoyama.com
• Google Scholar Page

The overlooked challenge of sustaining economic growth

04:45: Once you think about growth, it's hard to think about anything else. It's a question, I think, both for rich countries, which are stagnating. So, I mean, for the US in my view, but if you think about Germany or the UK, these are pretty stagnant economies right now. And so I think these are, you know, it's not just a "Oh, we've had this revolution. Now we can sit on this, wealth gradient.." No, this is an ongoing problem, and I think policymakers in most countries have totally neglected issues of growth. They've focused on all these other issues, which we think are important, and we might say we care about growth, but we really don't act like it. And, similarly, there's a need in developing countries, obviously, to sustain growth. Both the poorest countries in the world, but also middle-income countries, which can stagnate and fall into what's called a middle-income trap.

Geography’s impact on economic hubs

13:55: Geography still has this massive role, basically, even today, in the where, like the location, which locations are going to be economic hubs. But obviously, you can’t explain the why, so it’s going to be insufficient on its own, but it could be interacting with other factors.

On markets and creative destruction

42:06: You need markets, which are flexible and adaptable, so they can be disrupted by new technologies and entrepreneurs. Other people will have a more statist perspective. They’ll think that you need, maybe, the state to do more on basic science, right? Maybe more even on actual innovation to support this. But I tend to think that you need these market institutions, basically, and they need to be sufficiently vibrant.

We learn the skill of talking as toddlers and by the time we’re adults, most of us don’t think twice about the inner workings of a conversation. But the reality is, there’s a science and an art to conversing. And understanding that science could unlock so much potential in your professional and personal life. 

Alison Wood Brooks is a professor at Harvard Business School and the author of the book, Talk: The Science of Conversation and the Art of Being Ourselves. She also teaches a cutting-edge course at Harvard called Talk where she helps students hone their conversational skills. 

Alison and Greg talk about talking, including why this critical skill should be incorporated into more school curriculums, the complexities of effective communication, and the importance of small talk. Alison also offers tips for enhancing your conversation skills, whether in personal relationships or professional settings. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Alex Pentland
• Jeffrey Pfeffer | Pfeffer on Power podcast
• “Risky business: When humor increases and decreases status” by Alison Wood Brooks, T. Bradford Bitterly, and Maurice Schweitzer
• Nicholas Epley | unSILOed 
• Gong

Guest Profile:

• Faculty Profile at Harvard Business School
• Professional Website
• Professional Profile on Instagram

Her Work:

• Talk: The Science of Conversation and the Art of Being Ourselves

Why aren't people experts at communication?

01:59: Language acquisition starts very early in our lives, and we spend almost all day long, every day of our lives, practicing it. And so we get to adulthood, and we feel like we should be experts at it, that we should be really great at it. And yet, as we all know, based on our own ruminations about our own lives, and from our observations of others, we are far from perfect at communication. And the reason that we're not experts at it is because, when you look under the hood, conversation is a lot more complicated and tricky than it first appears, and it takes some rummaging under the hood to understand what's really going on here and why aren't we—why aren't we perfect at it?

What makes a successful conversation

12:12: A successful conversation is about the combination of prep—what you do ahead of time—and then how well you improvise once you're there. It's the combination of preparation and flexibility.

Small talk is the start not the destination in every conversation

18:01: Small talk is a very important social ritual. You have to do it. You have to start somewhere, especially with strangers and people you haven't seen in a long time. You gotta start with, like, how are you? Like, what's going on? How are you? It'd be weird not to. The mistake that people make is staying there too long, not finding those off-ramps to move up the pyramid to something more meaningful and interesting.

The challenge of explicit goals in conversations

10:49: Often, we don't know what we want, and it might emerge as the conversation goes on or as a relationship proceeds. So that's a big problem, right? Like, we just can't possibly anticipate all of the many things that we might want. The second challenge is by making our goals explicit. Like, if we were to say all the things out loud, it would undermine much of the magic that we're actually looking for. We want a conversation to feel almost magical. [11:27]  We want to get there and do the thing without having to say out loud what our goals are. And the things that go unsaid in a conversation really matter. If we were to make everything explicit, a lot of that delight would disappear.

Where is the line between fact and fiction in the capabilities of AI? Which predictions or promises about the future of AI are reasonable and which are the creations of hype for the benefit of the industry or the company making outsized claims?

Arvind Narayanan is a professor of computer science at Princeton University, the director of the Center for Information Technology Policy, and an author. His latest book is AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference.

Greg and Arvind discuss the misconceptions about AI technology, emphasizing the overestimations of AI's capabilities and the importance of understanding predictive versus generative AI. Arvind also points out the ethical and practical issues of deploying AI in fields like criminal justice and HR. Arvind and Greg also explore the challenges of regulation, the historical context of technological hype, and how academia can play a role in shaping AI's future. Arvind also reflects on his previous work on Bitcoin and cryptocurrency technologies and shares insights into the complexities and future of AI and blockchain.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Deep Learning
• Generative Artificial Intelligence
• AISnakeOil.com | Newsletter
• Bitcoin and Cryptocurrency Technologies | Princeton/Coursera Course

Guest Profile:

• Faculty Profile at Princeton University
• LinkedIn Profile
• Wikipedia Page

His Work:

• Amazon Author Page
• AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference
• Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction
• Fairness and Machine Learning: Limitations and Opportunities
• Google Scholar Page

What can the AI community learn from medicine about testing?

28:51: Let's talk about what we can learn from medicine and what maybe we shouldn't take from them. I think that the community internalized a long time ago that the hard part of innovation is not the building, but the testing. And the AI community needs to learn that. Traditionally, in machine learning, the building was the hard part, and everybody would evaluate on the same few sets of benchmarks. And that was okay because they were mostly solving toy problems as they were building up the complexities of these technologies. Now, we're building AI systems that need to do things in the real world. And the building, especially with foundation models, you build once and apply it to a lot of different things. Right? That has gotten a lot easier—not necessarily easier in terms of technical skills, but in terms of the relative amount of investment you need to put into that, as opposed to the testing—because now you have to test foundation models in a legal setting, medical setting, [and] hundreds of other settings. So that, I think, is one big lesson.

Replacing broken systems with AI can escalate the problem

08:36: Just because one system is broken doesn't mean that we should replace it with another broken system instead of trying to do the hard work of thinking about how to fix the system. And fixing it with AI is not even working because, in the hiring scenario, what's happening is that candidates are now turning to AI to apply to hundreds of positions at once. And it's clearly not solving the problem; it's only escalating the arms race. And it might be true that human decision-makers are biased; they're not very accurate. But at least, when you have a human in the loop, you're forced to confront this shittiness of the situation, right? You can't put this moral distance between yourself and what's going on, and I think that's one way in which AI could make it worse because it's got this veneer of objectivity and accuracy.

Foundation models lower costs and could shift AI research back to academia

27:22: The rise of foundation models has meant that they've kind of now become a layer on top of which you can build other things, and that is much, much less expensive. Then, building foundation models themselves—especially if it's going to be the case that scaling is going to run out—we don't need to look for AI advances by building 1 billion models and 10 billion models; we can take the existing foundation models for granted and build on top of them. Then, I would expect that a lot of research might move back to academia. Especially the kind of research that might involve offbeat ideas. 

Raising boys in post-MeToo times is beyond challenging. So how do moms balance societal pressures with the desire to raise happy, healthy, and emotionally intelligent boys?

Ruth Whippman is a journalist and author of the books, BoyMom: Reimagining Boyhood in the Age of Impossible Masculinity and America the Anxious: How Our Pursuit of Happiness Is Creating a Nation of Nervous Wrecks. In BoyMom, she weaves personal anecdotes with data and reporting to capture the complexities of raising emotionally healthy boys in today’s world. 

Ruth and Greg discuss the cultural expectations and modern pressures around parenting, the problem with labeling traits either feminine or masculine, the nurturing gap for boys, and why patriarchy harms men just as much as women. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• G.I. Joe
• Incel
• Jordan Peterson
• We Can Do Better Than ‘Positive Masculinity’ by Ruth Whippman [New York Times]

Guest Profile:

• Professional Website
• Profile on LinkedIn

Her Work:

• BoyMom: Reimagining Boyhood in the Age of Impossible Masculinity
• America the Anxious: How Our Pursuit of Happiness Is Creating a Nation of Nervous Wrecks

Can we just allow everyone to be fully human without gendered traits?

39:02: I think there's all these attempts to rehabilitate masculinity and redefine it. And it's just like, can we just give it a rest and just allow everybody to be fully human? Stop assigning a gender to human traits and values. Every human needs power, agency, strength, and courage, and every human needs nurturing and relationships and care, those feminine-coded virtues. Why are we splitting them up? And when we try to say, oh, well, actually, caregiving is masculine, what are we even doing there? I mean, at what point does it just become meaningless? And we should just give up on those things altogether. At what point is it just reinforcing this idea that it's so important to be masculine that we come up with any kind of logical hack to make it work, to preserve it?

Are boys missing out on feminine-coded values that impact well-being?

08:24: Before you can encourage boys to take on those more feminine-coded attributes, you have to truly believe that those attributes have value. But I do believe that boys are genuinely missing out. I do believe that those feminine-coded values have huge worth and are hugely important for our psychological well-being and for living a happy, healthy life. And so I feel like this project of realizing that boys and men are losing out in this system is a really big part of what we need to do here.

Should we stop reinforcing masculinity as the be-all and end-all?

40:38: We should stop trying to push this positive masculinity framework. And it's not because I think it's great if people present as masculine; if they naturally like to embody all those virtues, if they come, if that's who they want to be, great. There's nothing wrong with masculinity per se. It's just that when we keep reinforcing it as the be-all and end-all of how a boy or man should be.

Understanding the invisible cultural baggage around gender

04:09: I think with kids, there's this sort of superficial idea that you can just choose whatever gender you are, but there's so much invisible cultural baggage going on in the lives of kids and adults with what we're all doing in terms of gender, all the invisible things and baggage that we bring to this project. [04:44] We're operating with this idea that we have this huge amount of control over all of these things. And both culturally and biologically, and in all kinds of different ways, we have far less control than we think we do.

What brought about the rise of cryptocurrencies, and whats the difference between tokens and money? How are some of these modern concepts of currency much older than people may think, with older and older examples being unearthed in different parts of the world?

Rachel O’Dwyer is a writer and lecturer in Digital Cultures in the National College of Art and Design, Dublin. She’s also the author of Tokens: The Future of Money in the Age of the Platform. It’s all about how more and more traditional mone is being replaced by tokens, but this has been happening in societies for a long time.

Greg and Rachel discuss the complex and interdisciplinary nature of tokens and their relationship to money, exploring the history, regulatory implications, and the current cultural significance of token-based economies. They also examine the role of digital tokens in various sectors, from gaming to social media, and their impact on financial activities and personal relationships. Rachel explains the rise of cryptocurrencies, the metaverse, and how these new forms of money shape modern culture and societal norms.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Friedrich Hayek
• Karl Polanyi
• John Searle

Guest Profile:

• RachelODwyer.com
• Faculty Profile at National College of Art and Design Dublin
• Social Profile on Instagram
• Social Profile on X

Her Work:

• Tokens: The Future of Money in the Age of the Platform

Where do we draw the regulatory line around money?

05:09: What I find quite interesting with tokens is that, increasingly, as we're seeing these sort of nonbank entities emerging and issuing money-like things, the token becomes a sort of regulatory sleight of hand. It becomes a way for platforms to issue money-like things, but say, well, hey, because this isn't real money, I'm not really a bank, so I'm doing everything that banks do, but because I don't have a financial license, I'm not processing payments. I'm doing everything that an employer does, but because I'm not handling money, I'm not officially an employer; therefore, I don't have any duty or responsibilities towards these people working or making a living on my platform. So there's all that sort of regulatory uncertainty sort of happening when we're dealing with tokens as opposed to money, but also, I think, as we saw in 2022 with the collapse of so many exchanges and stablecoins as well, there's this regulatory uncertainty around, what is legitimate financial activity and what is like a scam, and where do we draw the lines around those sorts of things?

Should tokens be seen as less than money?

17:25: When we start thinking about tokens as being less than money, there are all sorts of strings attached—all kinds of prescriptions, all sorts of controls attached to welfare payments, refugee payments—and all kinds of ways in which we can control prescribed behaviors when we issue tokens as opposed to "fungible," I suppose, cash or money.

Is scrip a double exploitation of workers?

23:29: I guess scrip is kind of a catch-22 because you're potentially being exploited when whoever's employing you is getting a profit—they're earning more than it costs to pay you and to sort of buy maybe the materials that it costs to produce whatever you're making. But scrip is double exploitation because they're paying you in their own special token that you can only redeem, basically, in the company store.

Programmable money ties payments to identity, unlike anonymous cash

38:56: A lot of what's happening with programmable money is tying the means of payment to your identity or to particular sorts of credentials. And I think with CBDCs, we're seeing more and more proposals for money that can be programmed, as they're saying, at issuance—that when that money is issued, there are potentially various terms and conditions hard-coded into it versus your dumb cash, which is just an anonymous, dumb bearer instrument that doesn't care and doesn't know who's holding it, who's bearing it, so long as it's bared up.

With more and more data available about each of us all the time, what are the consequences of rapid data-driven decision making by organizations, and what are the implications of it for democracy and social well being?

William Davies teaches Politics at Goldsmiths University of London and is the author of several books, including Nervous States: Democracy and the Decline of Reason.

Greg and William discuss how the ongoing crises are misunderstood by elites, and reasons behind the decline in public trust toward experts. William goes over the impact of advancements in behavioral economics, and how modern political and economic phenomena are influenced by historical and sociological contexts. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Brexit
• Friedrich Hayek
• Daniel Kahneman
• Amos Tversky
• Frankfurt School
• Michel Foucault
• Scientific Management
• Elton Mayo
• Mary Poovey
• Dominic Cummings
• Boris Johnson
• Jeremy Bentham
• Thomas Hobbes

Guest Profile:

• Faculty Profile at Goldsmiths University of London
• WilliamDavies.blog
• Wikipedia Profile

His Work:

• Amazon Author Page
• Nervous States: Democracy and the Decline of Reason
• The Happiness Industry: How the Government and Big Business Sold Us Well-Being
• The Limits of Neoliberalism: Authority, Sovereignty and the Logic of Competition (Theory, Culture & Society) 
• Economic Science Fictions

True happiness lies in quality time, not more work or consumption

53:18: This science of happiness proves, not that surprisingly, that actually spending time doing things that we consider to be intrinsically worthwhile, like hanging out with our families or pursuing activities in the outdoors that we enjoy doing, is more likely to make us happy than simply working more and consuming more. This is not a mystery. Most people intuitively understand this, but that would then point towards a set of policy goals regarding work-life balance and the rights to log off and to not always be at the beck and call of your manager, and that thing. So, those are more about empowering people than just fixing them the whole time.

How social media weaponizes our comparisons to others

30:35: I think one of the things that a lot of political psychology and economic psychology demonstrate quite convincingly, and I think that this is something that social media platforms weaponize, is that, when we compare ourselves to others, it makes us far more unhappy than economics.

Why culture mass surveillance aligns with conspiracy theory

46:35: [The] culture of mass surveillance goes hand in hand with a mentality of conspiracy theory because a conspiracy theorist believes, in some ways, quite correctly, that there's all this other stuff going on; you don't yet know about it, but someone else knows about it, and they're right! And that, in a way, has always been a feature of conspiracy theory, of social life. There's always been more to political institutions than meets the eye, but what there wasn't in the past was this capacity for vast quantities of data to suddenly come spewing out and often discrediting quite famous and quite powerful people.

How is artificial intelligence reshaping social dynamics, knowledge sharing, and the workplace in the digital age?

Alex “Sandy” Pentland is a fellow at Stanford University’s Human Centered AI Institute and helped create the MIT Media Lab. He’s the author of numerous books including, Honest Signals: How They Shape Our World, Social Physics: How Social Networks Can Make Us Smarter, and most recently, The Digitalist Papers: Artificial Intelligence and Democracy in America. 

Sandy and Greg discuss the evolution of social physics and computational social science, the importance of knowledge sharing in the age of AI, and AI’s implications on connectivity and curiosity. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Brownian motion 
• Republic of Letters 
• Raj Chetty 
• Charles A. O’Reilly III

Guest Profile:

• Faculty Profile at MIT
• Professional Profile on LinkedIn
• Human Centered AI Institute at Stanford University

His Work:

• Honest Signals: How They Shape Our World
• Social Physics: How Social Networks Can Make Us Smarter
• Building the New Economy: Data as Capital
• Global Fintech: Financial Innovation in the Connected World
• The Digitalist Papers: Artificial Intelligence and Democracy in America 

What impedes the transmission of good ideas from one part of the organization to the other? 

13:34: Organizations are always, today, siloed, and they're siloed for a variety of reasons. One is that we're not so smart. We can only understand a certain amount really well, and when it gets more complex than that, we go create another silo. We break it apart and create another silo, and people don't like to share things out of their silo because that means they're not valuable anymore. You like to control the staff and believe that your expertise is valuable. And if someone comes and says, "Well, give me all your data," that's like, "Hey, we're going to fire you in a month," right? People don't like to do that. And the data that they have is not contextualized, right? It means something to them, but somebody else looking at it will say, "Well, I don't know, it's a bunch of ones and zeros. What does that mean?" Right? You need to know what it's measuring and why. The intention is usually not in the data; it's in the context around it.

Does the rise of new AI tools stimulate curiosity or potentially dampen it?

59:34: The phenomenon of people not meeting other humans because they're all on social media is real and disturbing, and AI can make it worse. That's not quite the same thing as being curious. They are curious, just about things that are not actually in their physical environment or likely to affect them in that sort of immediate way.

Why smaller teams move faster and learn better

44:52: The smaller teams are necessary to move fast. If you have a big team, it's really hard to get everybody educated and on the same page. But with software and the sort of things that they do, you can do it with small teams. And so, you can have small teams, which means you can get consensus about what to do pretty fast. And, of course, the connections to everybody else mean you can look for opportunities and learn from other people much better than other people. So, it's a win-win thing. You get people that are able to put things out there quicker; they're able to learn from all the other people that have done it better. And it works pretty well.