unSILOed with Greg LaBlanc

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.

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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.

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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.

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How does the present reckon with the historical legacies of notable figures of the past? How do you contextualize the actions of people from other generations today? How do we deal with the information learned through methods that are unacceptable today?

Andrew Garrett is a professor of linguistics at the University of California, Berkeley, and the author of The Unnaming of Kroeber Hall: Language, Memory, and Indigenous California.

Greg and Andrew discuss the renaming of Berkeley buildings originally named after problematic historical figures, with a focus on Alfred Kroeber. The discussion explores Kroeber's contributions to linguistics and anthropology, his controversial involvement with Indigenous peoples and remains, and his work with the Yurok language. Andrew provides an insightful examination of the broader implications of these issues for contemporary relations between universities and Indigenous communities.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Alfred Kroeber
• Yurok Language
• Franz Boas
• Umwelt
• West Berkeley Shellmound
• Elgin Marbles
• Phoebe Hearst

Guest Profile:

• Faculty Profile at UC Berkeley
• Profile on Wikipedia
• Social Profile on X

His Work:

• Amazon Author Page
• The Unnaming of Kroeber Hall: Language, Memory, and Indigenous California

Is Alfred Kroeber's legacy in language and storytelling overlooked?

48:26: One of the reasons why I think Kroeber's real legacy have not been seen so clearly in anthropology because I think his most important legacy going forward is about language and about storytelling, narrative, and oral history. And those are things that are less part of the anthropology world today and more part of the linguistics world. But he's usually identified as an anthropologist. So linguists tend to be a bit unaware of what he did. And anthropologists look only at the culture side of what he did and find it less interesting. So, this kind of separation has, I think, been part of the difficulty.

Understanding inequality today requires tracing its roots to the past

41:21: I think the law has evolved in California. I'm not a lawyer, but my understanding of the way the law has evolved is that geographical and national ownership is sufficient. So, you no longer have to show that certain ancestral remains are somehow intangibly associated with you culturally, simply that they are found in the area that is your tribal area. That makes it more analogous to the Etruscan situation.

How Alfred Kroeber helped revive indigenous cultures

25:49: I think one of the important uses that have been made of [Alfred Kroeber]'s material is not for world culture but for those cultures where there's a massive archive of material from their grandparents or great-grandparents that they can use in cultural and language revival projects today. It's like the thing that [Alfred Kroeber] didn't see as possible—the survival of Indigenous cultures—that he, in fact, helped to make possible.

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When did the gaps in wealth distribution across the globe significantly widen? What is the role of human capital investment?Was the Industrial Revolution to blame? Or can the roots of economic inequality be traced back even further in human history? 

Oded Galor is a professor of economics at Brown University, the founder of the Unified Growth Theory, and author of the book, The Journey of Humanity: The Origins of Wealth and Inequality. His work covers the history of economic development throughout human history, as well as the consequences of that development – vast global inequality.

Oded and Greg discuss the significant historical factors that have shaped wealth distribution across the globe, Oded’s Unified Growth Theory, addressing the long-term impacts of population dynamics, and why diversity is a key but precise ingredient in economic development. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Malthusianism

Guest Profile:

• Faculty Profile at Brown University
• Professional Website

His Work:

• The Journey of Humanity: The Origins of Wealth and Inequality
• Unified Growth Theory
• Discrete Dynamical Systems
• Inequality and Economic Development: The Modern Perspective 

The interplay of institutions, culture, and geography in inequality

30:59: When I view institutions, I view them as a byproduct of the process of development. And this will be true for cultural elements as well. Naturally, at a certain point, there are certain externalities in societies that people cannot fully internalize, and the society is forming some cultural norms that allow individuals to coordinate and act based on cumulative knowledge and cumulative wisdom generated in the course of the history of this group over time. These cultural norms can feed into institutions. Institutions can cause some adaptations in cultural norms. But in terms of the hierarchy of factors, the way that I view the world is that, if we think about inequality today, it is affected by deep-rooted factors, institutions, and culture that are reinforcing one another. But, underlying institutions and culture are geographical elements and human diversity that affecting the nature of the institutions, the nature of cultural characteristics, and their interaction.

Understanding inequality today requires tracing its roots to the past

04:45: In order to understand the rules of inequality today, we have to develop theories that will enable us to link the present and the past. Namely, we have to focus on those initial conditions that created the precondition for economic development and ultimately created much of the inequality we see today.

There is no universal policy that would fit all nations

24:57: One of the main insights of “The Journey of Humanity” is that, in fact, there is no universal policy that would fit all nations. In fact, the design of policy will have to be reflective of the history of each nation, the geography of each nation, and the evolutionary processes that occur there and lead this society into its current position. Once we understand these processes, we can design policies that will foster economic development and basically target societies in a differential way.

The role of diversity in economic development

43:49: Diversity is an incredible force in the context of economic development. Based on our estimates, it accounts for about one-sixth of the variations in inequality across the globe today. And much of the variation in diversity, as we see it across the globe today, was determined very much in the distant past. They were determined due to the exodus of humans from Africa during a time when humans started to populate the planetary assessor.

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Ever considered how something as simple as a notebook could shape history?

Roland Allen from Thames & Hudson chronicles the substantial history of a humble tool in The Notebook: A History of Thinking on Paper which traces the roots of jotting things down all the way back to medieval Florence and beyond. 

Roland and Greg chat about the earliest forms of notetaking on things like papyrus and wax tablets, the great thinkers in history who were prolific notetakers, and the enduring importance of writing things by hand in a digital world. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Giotto
• Petrarch
• Zibaldone
• Erasmus
• John Collett
• Samuel Pepys
• Bob Graham

Guest Profile:

• Professional Website
• Profile on LinkedIn

His Work:

• The Notebook: A History of Thinking on Paper

Why writing by hand engages your brain

29:18: The brain, as you know, it's all about connections. It's not about really what one part of the brain does; it's about how different modules in the brain relate to each other. And when you write in a physical notebook, you activate more parts of the brain than when you type. So, for instance, you tend to activate the hippocampus, which is your mental map, and you activate that when you're writing in a notebook. And they reckon this is because a notebook isn't just a thing; it's also a kind of place. And so, when you put an idea on the page, you're locating it on this kind of mapped reality, which is the pages of your notebook. And if you think about this, when you're flicking through a notebook, you quite often think to yourself, "Oh, I know this is on the left side at the bottom," or, "I know this was in blue, not black," or, "I know that it was a doodle in a corner of the page." And you don't get that when you're typing. And they think it might be to do with the fact that, as you scroll up, or as your document scrolls up the screen away from whatever it is—the leading edge of what you're typing—it just vanishes into the machine.

Why slowing down improves your writing

26:57: It is much easier to tap into a laptop. It's much easier to edit on a laptop. And it's much easier to word process, produce a thousand words of text on a laptop. But to make it good takes work, and if the process of writing is a little bit difficult if you're forced by the labor of handwriting, which is slow and hard work, to actually think through every word carefully as you order it, as you make your sentence, this I think is a really good discipline, and it will give you better quality results.

The power of handwritten note taking

28:12: When you're note-taking, there's a real advantage to the physical labor of picking a phrase, a sentence, a reference; you excerpt it, you choose it. And because it takes that two minutes to write down a long quote or something like that, or longer, you have to focus on every word as you do it. You can't just control C, control V. Yeah, or Apple C, Apple V, all of the quotes you need, and just dump them into your document. If you do it by hand, you digest them. You get to know them. And that's the best way, I think, to understand something that's been written by someone else—to copy it out because you have to really engage with it.

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If meaning is made with our minds, what role does the body play in shaping meaning? How do the studies of philosophy and cognitive science intersect?  

Mark Johnson is an emeritus professor of philosophy at the University of Oregon and one of the key thought leaders on the co-evolution of philosophy and science in the 20th century. His books like, Metaphors We Live By and Philosophy in the Flesh: the Embodied Mind & its Challenge to Western Thought explore the relationship between philosophy and cognitive science. 

Mark and Greg discuss the evolution of philosophical thought from metaphysical realism to embodied cognition, the impact of metaphors on human thought and understanding, and philosophy’s potential future in the world of artificial intelligence. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• George Lakoff 
• Patricia Churchland
• Gottlob Frege
• Maurice merleau ponty
• John Dewey
• Brain in a vat
• James J. Gibson
• Time and Narrative by Paul Ricoeur
• William James

Guest Profile:

• Faculty Profile at University of Oregon
• Professional Website

His Work:

• Metaphors We Live By
• Philosophy in the Flesh: the Embodied Mind & its Challenge to Western Thought
• Moral Imagination: Implications of Cognitive Science for Ethics
• The Meaning of the Body: Aesthetics of Human Understanding
• Embodied Mind, Meaning, and Reason: How Our Bodies Give Rise to Understanding
• Philosophical Perspectives on Metaphor
• Out of the Cave: A Natural Philosophy of Mind and Knowing

Embodiment and the human experience 

15:25: The fundamental unit of experience, or of anything you do or think, is a human brain, at least partially functioning, operating a human body, at least partially functioning as it engages in an ongoing way. It's an environment which is, at once, material, interpersonal, and cultural. That's a nugget of what everything we're doing is about and trying to articulate. So, embodiment all the way through. And now that we have all these information processing models, sometimes questions get raised about, well, you know, are we going to do what to do away with the body and all of that, but you have to build up to that.

All philosophy emerge in experience

44:53: I think that all philosophy, all thought, all action, and all values emerge in experience, which is not reducible; its enriched experience, and that we have to, through inquiry, remake that experience to move forward in the world. 

On bringing rigor from science to the humanities

50:05: Doing good science is so difficult, labor-intensive, time-consuming, and expensive that it kind of fills up your world, I want to say. And they [scientists] don't see the same rigor in what they regard as the humanities. So, the best I can do with that is try to bring research out of the humanities and help it interface.

On the theory of meaning

26:27: My theory of meaning is built around the fact that the meaning of something is the affordances that it enacts. There's a complicated story to tell about that, but intuitively, it makes you grow into a world where you learn the meaning of things by what it affords you by way of experience.

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For many job seekers today, the first eyes on their application are most likely not human. Companies and recruiters are turning to AI more and more to streamline the hiring process. But is AI actually fairer than its human counterparts? Or is it bringing in new biases and discriminatory practices when looking at a job applicant’s qualifications?  

Hilke Schellmann is a professor of journalism at New York University and the author of The Algorithm: How AI Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now. Her work examines AI’s increasing role in the world of work and how companies should be cautious of its pitfalls. 

Hilke and Greg discuss the scale of AI’s impact on hiring, the bias and inefficiencies in these tools, and why more human oversight and testing is needed in this field. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• AIHawk
• HireVue 
• Joseph B. Fuller
• Cambridge Analytica

Guest Profile:

• Faculty Profile at New York University
• Professional Website
• Professional Profile on LinkedIn

Her Work:

• The Algorithm: How AI Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now 

Is AI more biased or human hiring?

04:16: I think the one concern that I have with AI tools is like, one human hiring manager can be biased against a certain amount of people; it's usually very limited. How many can they possibly hire in a year, right? And I'm sorry to all the people who have been the victim of somebody who's biased in HR or in hiring manager. The problem is with AI tool we sometimes see it used in a new scope. If you have a resume parser that's discriminating against women. If you use it in all incoming resumes in your company, some companies receive millions, literally millions, of applications. So the harm can be just so much larger than one biased human can apply, and I also feel like if we build these sophisticated AI tools, let's make sure they work. They're not compounding their already bias that people, especially people of color, especially women, especially people with disabilities, have already encountered.

The misconception of AI as thinking machines

16:29: I think the problem is that we assume that AI tools are thinking machines and that they find something meaningful. But they have no conscience. They don't understand. They just pick.

AI tools don't erase biases

14:09: If you work with an AI vendor that cannot tell you how a score comes to be and says, "We know it's a deep neural network. We don't know it's on in training data," I would be really worried because we have only seen time and again that we find bias in these tools and not the opposite. The tool doesn't erase the bias, unfortunately.

Do we need more educated HR consumers or consumer reports for AI tools?

51:54: I would love to have a consumer report, but in the absence of that for AI tools, we need to get a whole lot more skeptical and do pilot studies. Also, like, hire maybe an outside I/O psychologist to take apart the technical report. And if an AI vendor doesn't have a technical report that explains how the tool was validated and built, and how they did at least the four-fifth rule analysis to understand that there's no disparate impact—if they don't have a technical report that explains any of that or whatever they call it—I would assume they didn't do this. I would run away if they can't even tell you how the tool was validated and checked for disparate impact. And then I would scrutinize these technical reports. I had people help me with that, and they found flaws in a couple of technical reports that I was able to get my hands on. So I would do that.

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In the last five years, artificial intelligence has exploded but there are a lot of holes in how it works, what it is and is not capable of, and what a realistic future of AI looks like. 

Gary Marcus is an emeritus professor of psychology and neural science at NYU and an expert in AI. His books like Taming Silicon Valley: How We Can Ensure That AI Works for Us and Rebooting AI: Building Artificial Intelligence We Can Trust explore the limitations and challenges of contemporary AI.

Gary and Greg discuss the misconceptions about AI’s current capabilities and the “gullibility gap” where people overestimate AI's abilities, the societal impacts of AI including misinformation and discrimination, and why AI might need regulatory oversight akin to the FDA. 

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Thinking, Fast and Slow by Daniel Kahnemann
• Joseph Weizenbaum
• “Overregularization in Language Acquisition” by Gary Marcus and Marcus Pinker 
• Lina Khan
• Reid Hoffman
• Tesla collides with private jet (YouTube)
• Cruise (autonomous vehicle)
• AlphaFold
• “The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence” by Gary Marcus 

Guest Profile:

• Professional Website
• Social Media Profile on LinkedIn
• Substack

His Work:

• Taming Silicon Valley: How We Can Ensure That AI Works for Us
• Rebooting AI: Building Artificial Intelligence We Can Trust
• Kluge: The Haphazard Evolution of the Human Mind
• The Algebraic Mind: Integrating Connectionism and Cognitive Science (Learning, Development, and Conceptual Change)

Is Gary pessimistic about AI's future?

30:28: [With AI] I think the last five years have been a kind of digression, a detour from the work that we actually need to do. But I think we will get there. People are already realizing that the economics are not there, the reliability is not there. At some point, there will be an appetite to do something different. It's very difficult right now to do anything different because so many resources go into this one approach that makes it hard to start a startup to do anything else. Expectations are too high because people want magical AI that can answer any question, and we don't actually know how to do that with reliability right now. There are all kinds of sociological problems, but they will be solved. Not only that, but I'm somebody who wants AI to succeed.

Why AI hallucinations can't be fixed until we stop running the system

21:02: Any given hallucination is created by the same mechanism as any given truth that comes out of these systems. So, it's all built by the same thing. With your less-than, greater-than bug, you can work on it selectively in a modular system; you fix it. But the only way you can kill hallucinations is to not run the system. As long as you run the system, you're going to get it sometimes because that's how it works.

Should we help people cultivate their uniquely human common sense?

43:01: In general, critical thinking skills are always useful. It's not just common sense; a lot of its scientific method and reasoning. I think the most important thing that people learn in psychology grad school is whenever you've done an experiment and you think your hypothesis works, someone clever can come up with another hypothesis and point out a control group that you haven't done. That's a really valuable lesson. That breaks some of the confirmation bias and really raises one's level of sophistication. That's beyond common sense. It's part of scientific reasoning; those things are incredibly useful. I think they'll still be useful in 20 years.

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Technology changes have always meant business changes, but with technology changing this fast, how long can businesses keep up? How can businesses work with technology to increase their own yields exponentially?

Azeem Azhar is the founder of Exponential View, a platform that features podcasts, newsletters, and video content. Azeem is also the author of the book The Exponential Age: How Accelerating Technology is Transforming Business, Politics and Society.

Greg and Azeem discuss the rapid technological transformations reshaping business, politics, and society, transitioning from a linear era to an exponential age. Azeem explains the historical turning points of technological revolutions, the economic implications of these changes, and the role of general-purpose technologies like certain AI models and solar photovoltaics. They also go over the challenges and opportunities faced by corporations and government bodies in adapting to these rapid changes, and how to mitigate many problems with the practice of continuous learning within organizations.

*unSILOed Podcast is produced by University FM.*

Recommended Resources:

• Ray Kurzweil
• UnSILOed: Episode 360: Robert J. Gordon
• Carnot's Theorem
• Experience Curve Effects
• Philosophy, Politics and Economics
• Nvidia
• Steve Ballmer
• Kenneth C. Griffin
• Perplexity AI
• Claude (language model)
• ChatGPT
• Michael Porter
• Daron Acemoglu
• James Boyle

Guest Profile:

• Azeem Azhar's Exponential View Podcast
• AzeemAzhar.com
• LinkedIn Profile
• Wikipedia Profile
• Youtube Channel
• Social Profile on Instagram
• Social Profile on X

His Work:

• The Exponential Age: How Accelerating Technology is Transforming Business, Politics and Society
• Exponential View Podcast
• Exponential View Newsletter

Integrating technologies into organizations

42:58: My observation with these technologies is that they're very, very powerful. There are  clearly some good directions to head in, but they're a bit complicated to bring into an organization. And then the question about learning is this: Are you willing to do the work to bring onboard a powerful technology that's a bit complicated? That may mean you got to read a document on a weekend rather than golf, or do you not want to do that work? And I love learning, as you do. This podcast is about learning. Of course, I'm going to tell people, "Just do the work, get learning." Because it's never going to stabilize, right? This technology is not going to stabilize. It'll get better in many different ways and, therefore, harder to use. I can drive a Tesla Model 3; I can't drive a V12 Ferrari. I'm not a good enough driver to drive a great car. And so we have to get better at them. And that ultimately is your choice.

Are we all students in this exponential age?

49:58: In this new world, into the exponential age, we all become students because the world is going to change so rapidly. On the other hand, the cost of being a student is much lower than it ever has been because I've got a professor in my pocket. I will continue to learn, and I can continue to actively learn about the world.

AI's public good—who benefits and how?

54:07: I think that, with AI, the potential public good and social good of being able to put humanity's knowledge into systems that can become freely and widely available should force a process—an open process of discussion about how those rewards should get split and who should get what.

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