Instant Genius - Why gradual change is the true driving force of innovation

Episode Date: February 6, 2026

Over the past several decades, many technologists and policy makers have sought out huge, disruptive shifts in thinking in almost every area of science, business and commerce in the hope that they’d help to drive innovation forward in giant leaps, one brilliant new idea at a time. But how successful has this been, and should we instead be focusing on a more gradual, incremental approach to innovation that’s based on the steady upgrading of the systems we already have in place? In this episode, we’re joined by Albert Fox-Cahn, a visiting professor at The Centre of Governance and Human Rights at Pembroke College, Cambridge, to talk about his latest book Move Slow and Upgrade – The Power of Incremental Innovation. He tells us why we tend to overemphasise the potential impact of the Next Big Thing, how this often leads to a rush to adopt unproven, and at times, unsafe new technologies, and how applying evidence-based thinking and an upgrader’s mindset can help us to be more like the tortoise than the hare, and ultimately win the race. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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Over the past several decades, many technologists and policymakers have sought out huge disruptive shifts in thinking in almost every area of science, business and commerce, in the hope that they'd help to drive innovation forward in giant leaps, one brilliant idea at a time. But how successful has this been? And should we instead be focusing more on a gradual, incremental approach to innovation? That's based on the steady upgrading of the systems we already have in place.

In this episode, we're joined by Albert Fox Khan, a visiting professor at the Centre of Governance and Human Rights at Pembroke College Cambridge to talk about its latest book Move Slow and Upgrade, The Power of Incremental Innovation. He tells us why we tend to overemphasise the potential impact of the next big thing, how this often leads to a rush to adopt unproven and at times unsafe new technologies, and how applying evidence-based thinking and an upgraders mindset

can help us to be more like the talk to. than the hair, and ultimately win the race. So welcome to the podcast. Thanks so much for joining us. Thank you for having me. So today we're talking about your latest book, Move, Slow and Upgrade, The Power of Incremental Innovation. So the kind of idea of the book is that we have sort of two opposing forces,

one being innovation mentality, which in your thesis has caused all manner of problems over the past, I don't know, quite a few years now. And we need to shift to a more, what you call upgrade mentality. So let's start by exploring these terms then. So first off, what do you mean by an innovation mentality? Yeah, we've gotten use over the years to hearing people talk about innovation as the fix to everything. It's the path to the future. It's the way we're going to solve everything from economic inequality to, you know, climate change. And people often use it to mean these big, wild swings at the future. But what we point out in the book is that innovation makes for a great sales pitch, but it doesn't usually make for a great plan. We document all these places where all

these corporate titans are trying to invest in this grand transformation of the way our society works, only to end up realizing that innovation isn't really up to the job. And that includes things like cryptocurrencies abject failure to solve unbanking. It includes Mark Zucker, Borg's multi-billion dollar failure to create a metaverse that we all work in every day. It includes all of these failed innovations from the pandemic era, where we saw just some of the most preposterous claims about what tech could solve. And what we show is that we don't have to accept this as the price of progress. We don't have to accept this lottery ticket mentality every time we want to get ahead.

In fact, there are like sober, evidence-based alternatives that we oftentimes can choose instead, but are just constantly seeing overshadowed by the emphasis on big-ticket innovation. So on the flip side, then, what's the upgraded mentality? The upgrader mentality is do the hard work. Look for the boring answer that's got a proven return. You know, instead of, it's the tortoise and the hair, you know. We all know this as a kid. The flashy race to the finish line oftentimes is going to end up, you know, losing out on the whole competition because, you know, it's the methodical workhorse who we tell kids they're going to actually take the prize in the end.

And yet we reverse that entire narrative as soon as they get to grad school and say, hey, the way you succeed in computer science and bioscience and all of these different areas is you need some flash in the pan, world changing. innovation. Doesn't matter if it works, but it just needs to work well enough to actually get some capital. But what we see is this unsung army of upgraders working in the shadows to actually tinker on the incremental improvements that keep things from falling apart. It's stuff like the cybersecurity professionals who are constantly patching and upgrading systems, looking for the mild tweaks that they can use to slightly improve the safeguards against a constellation of threats coming from everyone from, you know, fake princes trying to sell us, you know, elaborate scams to foreign governments trying to, you know, take away, you know, vital secrets. It's, you know,

all of the, you know, civil servants and real technocratic experts who, sadly, in my country, in the United States, are becoming an endangered species in the federal government as we see the innovation mindset pushing more and more experts out of government. government with this relentless focus on the dojification of how we administer, you know, federal programs. So, you know, why does this idea of sort of innovation, almost at all costs, seem to be such a widespread concept, you know, when did it really start picking up pace? I mean, can we even answer that?

I mean, I think it's always been there, but, you know, what we saw is there's been this rapid acceleration of innovation thinking since the dot-com era. We saw this one moment in human history when there actually were quite a few technical breakthroughs that allowed us to rapidly reorient whole industries and make a lot of people a lot of money. And that got baked into our theory of capitalism in the U.S., but also into our theory of government. And we saw it spread from America to so many other countries around the world. But we can't just pick this one clean start date because we've always seen technical boondoggles

where people invested in these adventures that they wouldn't actually pan out. I mean, here in the UK, an example that often comes up with my colleagues at Cambridge is the post office scandal. The fact that you had a massive investment in this software that was supposed to wipe out fraud and improve the economic functioning of the post office on a scale that really would dwarf all of these prior efforts.

What did we see? We saw just the heartbreaking consequences with people being falsely accused of fraud they never committed, driven to bankruptcy in some cases even worse. And so I think that what we're saying in our book is that when you look at the history of scientific development, when you look at the history of how, you know, countries come to tackle really hard problems, they can do it. We can do amazing things. We don't have to accept the status quo. But the real historical narrative is often this long, boring slog through incremental change, not the one eureka moment where some, you know, garage tinkerer solves, you know, the world's most vexing problems. That's the thing that we see in the movie.

and that far too often is also the theory of innovation that gets public funding. Yeah, so you've mentioned a few already, but the books kind of split up into a series, I guess you'd call them case studies. Seeing as we've only got about 30 minutes, is there one sort of exemplar of these you'd like to pick out, which we can go into a little bit more deeply to illustrate this process? Well, one thing that I like to point to these days,

And given how there's always a lag between when you write a book and when it comes out, it's not quite as flushed out as it would want to be, is just the role of artificial intelligence, right? So when we look at all the hype cycle around AI innovation today, you would think that artificial intelligence is this thing that came just out of nowhere, that it came together from the myths just two years ago, fully formed, when Sam Lutman plucked ChatGPT from the ether. But in fact, we've seen the linear algebra at the core of ChatGPT being used to develop incrementally more sophisticated machine learning systems for decades.

We've seen this increasing complexity in the algorithms at the heart of LLMs. We've seen this increasingly powerful computational network that is able to draw on ever more GPUs, graphical processing. units, the sort of nerve center of modern AI, we've been able to see them ratching up the power, ratching up the scale. But we had this inflection moment where you suddenly were seeing mass adoption of the technology, not because there is some massive change in how chat GPT was able to technically deliver in that LLM methodology. But they were really good at marketing. and they deployed something at a time when a lot of existing large companies thought, quite frankly, it was irresponsible to go to the public with this sort of product because of the risks of hallucination, because of the risk of bias, because of all of the risks that we've seen played out in the implementation of large language models on a large scale.

And so when we look at it through this lens, this, you know, flash in the pan innovation story, this step change narrative about how, you know, AI fundamentally changes our society, it looks very different. And so the question about how to think about AI, how to invest in AI, how to regulate AI, it starts to look very different as we look at, well, if this has been a long incremental story to get here, even with all the countless billions being poured into AI now, you see a lot of skeptical analysts who are saying, well, actually, we may not continue to see AI, you know, rapidly shift the way that it did. We may actually see this slow incremental change.

We may see this plateau, and there may be a way to upgrade AI further. But the idea that you can then just innovate with AI instead, use it to display entire workforces, use it to displace entire parts of government. You know, that to me seems like, you know, we have learned from these past case studies why this is really a folly and why, you know, if we do entrust AI to be that sort of innovation, we'll replicate, you know, failures like the post office scandal, like, you know, the metaverse, like, you know, the follies with cryptocurrency. yet again.

Yeah, so one phrase that I thought was really interesting in the book, as you say, that this kind of activity focuses on disruption rather than improvement. So can we unpick that a little bit, please? Yes, exactly. So when you look at, you know, cryptocurrencies that were being, you know, initially deployed through Bitcoin back in 2008 at, you know, the height of the financial crisis and then subsequently Ethereum, and then all these hundreds and hundreds of spinoffs,

if you look at what they're doing, they are trying to disrupt the way that we bank, the way that we hold money, the way we think about currency, but nothing that they're actually conceptualizing is actually an improvement in the function of those systems for everyday users. You know, I'm sure we have all met people in our life

who invested early in cryptocurrency and made a huge amount of money and we're like, oh, wow, oh my gosh, they must have known something. But one of the things we try to pick apart in the book is that, yes, cryptocurrency ended up being this phenomenal asset bubble. It ended up being the modern-day equivalent of the Dutch tulip craze, where you saw tulip prices going sky high before crashing to Earth. And just because something is an asset bubble doesn't mean it's actually able to innovate,

able to improve on its stated end goal. And with cryptocurrency, the promoter said, this is a way to help bank the unbanked. But when we look at the way cryptocurrency is used in the world, not only is it not helping provide financial access to people who are unbanked, no one's actually banking with it because it's not the sort of asset class that people consider to be a currency. They consider it to be an investment. They consider it to be something that they would use, just to build wealth. And when you look at all the people who said, oh, cryptocurrency will be this innovation to help move us away from traditional currency, those people, those really strong proponents of using cryptocurrency as an alternative to dollars and pounds, they're the

last to actually use it that way, because they're all the ones who are saying, well, but I would never sell my cryptocurrency. I want to hold onto it because I believe in it for the future. That is the paradox here. If you believe that this is incredibly valuable and you want to hold on to your crypto at all costs as an investment for the future, then by definition, you're not going to go out and buy a latte with it at the corner store. And that's before you get to the fact that none of the coffee shops around me would ever accept payment in crypto. Because if they were, and I'm talking about crypto on the blockchain, the original version of crypto, we have this distributed ledger where people are using mathematical proofs in order to sort of

create this trust model. If you look at that original form of crypto, no one uses it for purchases, no one uses it for banking, no one uses it as an alternative to the currencies around us. And instead you see people saying, okay, now the solution is because we can't actually use crypto that way, let's build on crypto and let's do it in a way. that allows us to avoid the fact that crypto is very slow and very expensive to transact on. But that's how you get FTX. That's how you get people like Sam Bankman-Fried who went to prison for allegedly stealing, you know, billions of dollars in crypto assets from the people who were innovating in the financial

system by investing within it. I do find that crypto is particularly lively as an innovation fail case because it's still failing on its own terms, on the terms of the people who, you know, pushed it as an initial financial innovation. And yet people are still, you know, investing huge sums in it, not because it becomes a way to solve those problems, but because it's a asset that they think will make them even richer. I think that what upgraders do instead is they say, well, let's just make bank accounts easier to get. You don't need to set up a massive alternative financial ecosystem built on exotic mathematical proofs as the way to, you know, fix banking and equity. Just try to actually

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Visit focal powered by name.com for more information. So another sort of thing that you point out, another issue with this kind of innovation mentality, is that someone will come to, oh, you know, I've stumbled on this new tech. What can I do with it? Rather than being the other way around, or perhaps more often, you know, how can I sell it? So, you know, what can we say about that? Yeah, one of the hallmarks of innovation thinking is when you build first and justify later. And we've seen this across industries.

You know, we see this a lot of the time with policing tech. with these people who will build new surveillance devices and then come up with a justification for it. There is one company we profile that created this device to monitor the location of people wearing badges at a school. And they initially were saying, oh, we have this technology to monitor the location of students.

What do we say this is actually good for? And at first they were saying, oh, this is a great way to respond to a mass shooter, which in my mind is an absurd response to the appalling threat of gun violence in the U.S. that somehow you'll make all the students who are being targeted by a gunman wear a Bluetooth badge to help track their movement. But then during the height of the pandemic, this same company then rebranded this exact same product with the exact same technology as a solution to COVID. by saying, oh, these Bluetooth beacons are a way to now do contact tracing and a way to actually prevent the spread of the disease, not because it was actually shown to be effective or sound

at any of that, but because that was the fear that was motivating their purchasers. Schools weren't as focused on mass shootings. They were focused on COVID. So anytime you see a technology being rebranded as a solution. for different problems. It's a warning sign that you're dealing with a innovation that's going nowhere, not an evidence-based upgrade. And I think, you know, we see this a bit in the AI age as well, where I hear from product managers at very, very prominent AI companies who say, well, we built this really big cutting-edge model and now we can't figure out what the heck to do with it,

because it's so expensive to run it that any time we try to sell it to a company, They say, well, that's great. You save me thousands of hours of manual labor, but it would have been cheaper just to, you know, pay people minimum wage to do that data entry or to do that task. And so upgradeers are the people who we see thoughtfully looking for problems to solve and designing solutions to those problems. who, you know, people like the, you know, cybersecurity researcher who is really interrogating the vulnerabilities in their system and applying that targeted patch. It's, you know, not this sort of idea that you need to build an impressive solution and then come up with a justification for how to monetize it later. Yeah, so do you think there's a sort of, there's some sort of appeal in a kind of false belief that such and such a product is going to be the future of such.

in such a field. And really, you only have to have a bit of a cursory look back over the years. And you'll see a graveyard of hundreds of products and services that were supposed to be the next big thing. And now are just useless. And often, products that were hugely expensive. Yeah. I mean, I was at a game developer convention

when Microsoft announced its multi-billion dollar acquisition of a new metaverse platform to compete. with all of the energy behind Mark Zuckerberg's acquisition of his own Metaverse companies. And now you talk to people about the Metaverse and you'll get a chuckle or a blank stare. It still remains the thing of science fiction. But to think back a few years to realize that corporate leaders, investors, Wall Street, everyone was showing this just unrivaled optimism around the ability to invest in effectively a video game company to spend tens of billions of dollars, you know, reorienting

something like Facebook to pretend that we were all going to be living in a simulated reality with each other in the next couple years to see Apple, you know, which has in the past had some real breakthroughs in consumer technology. The company that brought us, you know, the iPod and the first, you know, truly successful smartphone, Apple, which revolutionized personal computing, gave us a $3,500 headset that it said would be our portal to the Metaverse. And when I actually got it for a couple months to write about the experience, it was just jaw-dropping how poor devices was, because every single task I tried to complete on the headset, it was pretty clear that they had built the headset technology

and then tried to come up with the use case afterwards. That, oh, here's this way you can see your real apartment because it would have cameras on the front and then show you the simulated vision of how your home looked. And it would invite you to move around the space and to be interactive. And that clearly was the main appeal to the device once they realized how to integrate the cameras

on the front and the virtual sensors. But they hadn't figured out how to stop it from shaking on your head and blurring every time you walked around. So each time you took a step with this, you know, $3,500 contraption, you ended up taking a step closer to nausea. It was just this really disastrous role. And, you know, Apple has reversed course on the product since then. But I really do think that there is something broken.

in the United States about the way we invest in solutions, the way we build new technologies, the way we think about the future. Because the way we're approaching it, there's so much fear of missing out on the next big thing. There's so much outsized returns for being the first to come to market with some new version of what the future will look like. And so we just see what Corey Doctro has lovingly called in shittification, not just of single products, but the entire infrastructure of technological creation, evaluation, adoption, and obsolescence. So some people listening might think, oh, the metaverse. Well, I wasn't interested in that anyway.

But in the book, you give a really good example about cars, which I thought was really telling. So these days, if you buy the most high-end car and go in the interior, it looks like a spaceship. There's things everywhere. You know, it doesn't even look like a car anymore, a car interior. This is being done in the name of progress. But in fact, in terms of things like safety, it's having the opposite effect. Yeah, and this was something that came from my own experience buying a car.

I'm a very grudging car owner. I have this lovely house that is nowhere near any. form of mass transportation. And so when I made the realization I would need to buy a car, I started looking around. And I was just appalled that so many of the vehicles that, you know, I was being told I would love were these just overbloded, you know, arrays of sensors and screens and interactive systems, all of which were, you know, a threat to my ability to do the one thing I wanted to do, which was actually pay attention to the road. And we think about what it's like when, you know, you're driving and it's dark out and, you know, your lights are on and

suddenly you realize the windshield is fogging up. And, you know, on a dark, curvy road without any place to pull over, that can be a really, really fraught situation. It's every day for most of us. It's very pedestrian because you just flick on the defroster and you're going to be a really, to go, but what happens when you can't take your eyes off the road and you can't navigate the controls of your car? These sorts of innovations in user experience and control, the bloatware we see, the unnecessary LLMs, all the stuff that gets in the way, the consequences aren't usually this fraud, but when you're talking about, you know, the controls for our automobile, it can be a literal car crash. And it's not just a thought experiment. We've seen analysis by different, you know,

automotive researchers who found that, you know, a 20-year-old car is going to be much more effective at performing these simple tasks, changing the heat, changing the defroster, changing the things that you actually need to do to drive safely versus all the, you know, fancier, higher-end models on the market. And as we see the push to adopt self-driving cars, the danger is only going to be magnified by this rush to innovate self-driving technology. Look, I am not, you know, going to say that self-driving technology is bad. I think when it's actually done well, when it's fully developed, when it's, you know, inspected by regulators, when it's vetted, it will be a transformative thing. But instead, we see this rush to slap on, you know, half-tested forms of self-driving algorithms that have people speeding away

and at times are literally running them off the road. And I think that, you know, it's really an epic failure that we are so deferential to technology firms that we let them take risks in this way that we would never allow in other industries, simply because, we somehow believe that that sort of innovation is innate to technological development, not just a choice. Yeah, so sort of widening the idea out a bit then. So some people might say, well, surely there's going to reach a point where we've upgraded a certain system as far as we can take it.

And we generally do need innovation. What would you say to somebody that asked you that? Well, upgrading is far more robust. far more powerful than most people think. You know, upgrading means evidence-based changes. It means focusing on the proven return. It's putting a dollar in the savings account instead of buying the lottery ticket. Sometimes an upgrade is going to mean a shift in the type of system you're using. It's going to mean, you know, switching programming languages. It's going to mean shifting technical standards. It's going to mean introducing a whole new type of

medication. It can mean those things. But the question is, how are you evaluating that change? How are you investing in that change? And how are you, you know, figuring out when the time is right? You know, I think that our critique is that there's so much focus on the benefits of getting these long-shot bets right and so much focus on the economic and social gains that come from it, that we don't look at the costs as well as the reward. And when you actually do the accounting and you actually look at the amount of just blotware and garbage and just completely discarded and discredited projects

that have fallen by the wayside by this point in history, it becomes quite clear that, you know, yes, we have these small number of successful cases of moonshot innovation, but they're standing on a mountain of monuments to the risks that we collectively take and the harms that we collectively bear from having these sorts of experimentation.

Thank you for listening to this episode of Instant Genius, brought to you from the team behind BBC Science Focus. That was Albert Foxconn. To discover more about the topics we've just discussed, check out his book, move slow and upgrade. The power of incremental innovation. If you liked what you just heard,

then please do consider subscribing to Instant Genius on your preferred podcast platform. If you'd like to see our guests and hosts in person, then why not check out our YouTube channel at Science Focus. The current issue of BBC Science Focus magazine is out now. Pick up a copy wherever you buy your favourite magazines or download us on your app store of choice.

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