Jamie Metzl’s Superconvergence: The Intersection of AI, Biotech, and Innovation

Jeff Kavanaugh: I am Jeff Kavanaugh with the Infosys Knowledge Institute. We are in the midst of tremendous innovation in AI, genetics, and biotech. While these revolutions are each significant, together they offer incredible opportunity, yet also existential risk. I'm here with Jamie Metzl, technology futurist and geopolitical expert, to discuss this superconvergence of the three major evolutions and the exponential impact it will have on business and society.

Welcome, Jamie.

Jamie Metzl: Hi there, Jeff, nice to see you again.

Jeff Kavanaugh: Absolutely. We live an age of constant innovation, and in November, 2022 ChatGPT certainly caught everyone's attention. Yet, after reading your book, its significance pales in comparison to the advances in genetics and biotech. What are the most important innovations business leaders may have missed?

Jamie Metzl: Thanks so much, Jeff. Really happy to be here with you again. People are really excited about ChatGPT, and they were very excited because when it showed up, people got this sense, wow, this is what AI is, and this is really exciting. I talk to a lot of people, I say, "Are you experimenting with AI?" And they say, "Yeah, I went to ChatGPT and I did AI." And that's not wrong. But if I were to ask you, "Did you do electricity today? How did electricity influence your life today?" You couldn't even answer that question because electricity is woven into really everything that we do. Not just our computers and our lights, but our phones, our homes, our clothes, our haircuts. It's really everything.

And so when we think about AI, it's not just what open AI is doing, and it's not just AI itself. And that's the title of my book, Superconvergence. The real story of this moment is this superconvergence of different technologies that are all inspired by each other and inspire each other. And so, the machine learning revolution that Infosys has played such an important role in, the AI revolution, genetics, biotech, they're all being accelerated by this same set of factors.

And so, the first point, if people think this is just about AI, they're missing this broader technological story. And the second point is that, because of this, we're seeing an acceleration of technological innovation really across the board, and it's not coincidental that advances, maybe it goes back historically. So we had our agricultural revolution 10 to 12,000 years ago, and then we had agricultural surpluses, which allowed us to have bigger communities, so we needed writing to keep track of things.

And now, if we were just on the computers that both on, just to press a few buttons and we'd see the code that is underlying our communication, we see the ones and zeros of the binary computer code, and that dates back for thousands of years to what we call Arabic, but are really Hindu numbers, and we'd see what we call the Latin letters, which are really Phoenician letters for the new computer codes.

Which, these are all these ancient symbols and systems, and they've empowered our computers, which creates machine learning, which create AI. And now we're using the tools of AI and advanced machine learning to understand evolved natural systems, like how a plant diffuses nutrients through a leaf, and using those models to build better, stronger, faster computer chips that speed up everything else. So it's really, the story is technology.

Then the third thing, which I think is more important than ever, I mean you and I are speaking today, Jeff, while Davos is coming on, and you see, all of these tech leaders who are in Davos, I've seen a bunch of things even this morning of saying by 2027, our AI systems, what they call AGIs, are going to be able to do everything that humans do, just better than humans.

I think this is insanity. One, I don't believe what we're creating, AI, is artificial intelligence. We're not making artificial humans. We're creating machine intelligence. Maybe machine superintelligence. It's going to be able to do really incredible machine things, but we are humans with our great embodied intelligence, all of our senses, our communities. And so, I just think it would be a big mistake for companies to be asking the question, how do we use these technologies, as the first question. The first question is, who are we? What do we stand for? What are we trying to achieve? And how can we use these very powerful technologies in order to better achieve our goals?

Jeff Kavanaugh: That context is important, because I think that the rapidity of change right now, people get lost and overwhelmed in it, and it's important to have a sense of context, looking back, taking stock before looking forward. And in that spirit, our research suggests that humanity matters perhaps even more in the age of AI. Your book shows how the concept of humanity itself is advancing genetics and biotech. What are examples, and how do we ensure that these emerging technologies benefit humanity, rather than harm it?

Jamie Metzl: Humans have co-evolved with our technology for hundreds of thousands, and certainly tens of thousands of years, ever since we domesticated fire, which changed the way that we processed nutrients, because we could cook animals and then we could actually reallocate energy to our brains. The agricultural revolution, we co-evolved, even on a genetic level with our innovations. And that will continue to happen. And so, that's just part of our experience as humans.

And so, we really need to do both things, as we've both now mentioned. We need to recognize the incredible power and capability of these technologies, which are creating levels of agency that go well beyond anything that we've had in the past, or maybe even could have imagined in the past. And we need to recognize the essential core value of our humanity. We are going to learn over the coming years, decades and centuries, that there are certain categories of things that machines can do much better than we can. And we've already learned that with lots of activities in agriculture, where we all used to be agriculturalists, but now we don't have humans doing sowing and plowing, because our machines just do it better than we are.

So there's going to be a lot of things that machines do better than we do, and there are going to be a lot of things that we do better than machines. And so, one, as you mentioned, that's going to speed up innovations in a whole lot of different areas. We're already seeing it in healthcare, and I've written about this and I lecture about this a lot. We're seeing the transition from generalized healthcare based on population averages, to precision personalized healthcare based on a deep understanding of each person's individual biology. And as we build these massive data sets that include all kinds of, not just genetic information, but human biological information, that's going to shift us to the next phase of our healthcare, which is predictive and preventive.

And that same formula, which Infosys has been at the center of growing, which is the more and higher quality, larger data sets we have, the more computing power we have, and the stronger our algorithms, the more we're going to be able to identify patterns in very large and very complex data sets. And by identifying those patterns, we're going to see opportunities, both to do things differently, and to interact differently with those systems, whether it's manipulations or other activities that we can take.

So that's really, really exciting, but again, everything comes back to goals. What are we trying to achieve? Because this isn't a story of technology, it's a story of humans plus the technologies that we have created. So thinking about what we're trying to achieve, and then using these tools in order to achieve that, is critically important.

Jeff Kavanaugh: Why do you think so many, including yourself, are concerned by AI in its potential applications, and further, how is AI fundamentally different from previous emerging tech?

Jamie Metzl: So the fear question, I think, is really important. There is a reason why humans feel anxiety. It's not just some kind of wasted feeling. Evolution has preserved this feeling over millions of years in humans and all other animals, because anxiety is a way of saying, hey, there's something happening around us that actually could really be dangerous. And like with every other technology we've developed in the past, including agriculture, stirrups, spears, everything, every technology has an upside and a downside. I couldn't be more excited or enthusiastic about the potential upsides of all of these tools for healthcare, agriculture, industrial materials, energy, data storage, and a whole lot more as I write about in my new book. But it is not just right, but it's necessary for people to recognize now that there are some real dangers that are the flip side of everything that we can imagine.

Our ability to manipulate human biology for our own benefit also opens the door to manipulating our biology in ways that could harm us, our ability to develop new varieties of seeds that could increase agricultural productivity, which is something that we desperately need in a world of limited resources and still growing population. And it could also, if we get it wrong, lead us to some pretty bad outcomes. And that's why in the book and in life I talked about, well, here's what the positive vision looks like, and here's what the negative vision looks like, and neither of them is preordained or inevitable. And the work that all of us need to do now is asking, how do we optimize the benefits and the potential benefits, and minimize the harms and the potential harms?

And that's really the responsibility of everybody, and that's why I write a lot and think a lot about issues of governance. And governance isn't just what governments do. It's not just government regulation. It's really thinking at every level, from the individual, to the communal, corporate, regional, national, international and global about, what are our responsibilities in making sure that these technologies develop in a beneficial way?

And in your next question about how things are different, these are very powerful technologies. These technologies have the ability to speed up everything, and to in many ways improve themselves at accelerating rates. We're already seeing that with new programs that are speeding up coding. Google already announced in October, 2024 that about a quarter of the code it's using in all of its products is first generated by AI bots, which are then overseen by human engineers. The speed of coding has increased by about 50% over the last couple of years, and now we're going to have natural language coding, where people like me who don't even know how to code are going to say to our AI systems, hey, write me a computer code so that my lights will flicker on and off every 15 minutes, or whatever that thing is, and we're going to be able to get passable codes.

So we're seeing that acceleration from our AI, just like our LLM, our large language models, have started to figure out natural communicative language. Our AI algorithms that are developing code aren't just now able to suggest, hey, here's a next line of code based on what you've written so far, we're increasingly able to understand coding logic, and that's going to open up a lot of new opportunities and a lot of new dangers. So we are going to see that kind of acceleration across the board. And the summary of it is, innovation begets innovation, and so the more innovation we have, the more innovation we can and will have.

Jeff Kavanaugh: Well, it's a lot to digest, as well. In our research at the Knowledge Institute, we consistently see technology advancing faster than human ability to process. We see it over and over. You make the point eloquently in your book, while our abilities to change the world are accelerating exponentially, our ability to understand and manage these powers are only inching forward glacially, and mismatch is perhaps the greatest challenge of our time. What advice do you have for leaders to close this gap?

Jamie Metzl: Yeah, it's a great point and I couldn't agree more with it myself. And it's really important, because again, if this is just about technology and we're having this conversation in the United States now as we speak, the incoming Trump administration is pulling back a lot of executive orders that the Biden administration had created with regard to technology governance. And yes, I think it's important that we spur technological innovation, because if done well, we are all beneficiaries.

But this could also really go wrong. And it's the same point that I made before, that if we want to manage these superpowers wisely, we need to do it at every level. And so that means specifically for corporate leaders, every conversation about technology should start with the question, who are we and what are we trying to achieve? And then go to, well, how can our technologies help us achieve those goals? And then the third question is, what are the steps that we can make to make sure we take these steps wisely, and that every person at every level of this organization recognizes that we have a responsibility to make sure that happens? And so that's within companies.

But companies, corporations have a really important role to play in national and even international conversations about governance and regulation. And I think that if we should... I mean, it's still the early days. If we should get into an environment where the message coming from Washington is, well, it's a no-holes-barred technology arms race, I think corporate leaders have an important role to play in saying as we said with every other technology, we're not beneficiaries of a no-holes-barred technological arms race, across the board, really in any field. I mean, we've seen that in agriculture where the United States is a world leader in GMO crops, but in my view, significantly under-informed debate, public debate about GMO crops has made that terrain much more difficult.

The whole AI story, you don't need that many catastrophic bad experiences to change people's perceptions. That's what happened with gene therapy. We're now in the second spring of human gene therapy. The first one came to a crashing halt in the late '90s when tragically, a young patient, young man died at the University of Pennsylvania in a clinical trial of a human gene therapy. So it's not just that the people who are saying we need good governance at every level are just naysayers. The way that we can advance as rapidly as possible is by making sure we do it wisely, and everybody has a role in that process.

Jeff Kavanaugh: While these genetics, biotech, and AI revolutions will impact many industries, they really hit home for life sciences and healthcare. How can business leaders in these sectors use the superconvergence to their advantage and avoid obsolescence?

Jamie Metzl: Yeah, it's really important. The "don't be a Kodak" aphorism has become just a cliché, but it's a balance, because a lot of things that we have done traditionally, in health and life sciences and biotech traditionally, is measured in decades, more, maybe healthcare a little longer, than in centuries. There are just new ways to do different things that we want to do. So if you're in healthcare, you're in the business of preventing, treating and curing diseases. And so the question is, how can we think about doing that in a better way?

As I mentioned before, we're going to have a lot more actionable data. And so if we do this well on a corporate level, but also on a national level, and maybe on an international level, we can move back the intervention point, so that if you know that you are at risk of developing some kind of genetic disease or disorder, or other disease or disorder a decade from now, two decades from now, maybe there are just really simple low-cost interventions that you can make today in order to do that. So that's a whole new industry on prediction and prevention, and we're starting to see a little bit of it with the Oura Ring and different uses of Apple watches, but there's going to be a whole new field of biological sensing.

For companies that are in the life sciences, I mean, they're in some ways well-positioned because the life sciences are just, it's such a revolutionary set of fields, which are based on technology. But again, it's this balance, because technology is advancing so rapidly. And the question is not just technology itself, but what are the wisest and most economical, with in terms of return on investment, ways of integrating these technologies into workstreams that you're already doing.

And so, I do a lot of lecturing to biotech companies. I have an exchange-traded fund, and we have a basket of 90 different biotech companies, healthcare and beyond. So I see a lot of these companies, and it's really a balance. I mean, we had, certainly in biotech, from the beginning of the pandemic in early 2020 until the middle of 2021, there was a real biotech boom, and there was tons of money that was flowing into this sector, and tons of investment and people could really be dreamers. Then in the middle of 2021, there was a massive pullback that has lasted until today and continues.

So all of these companies need to really think about cash on hand. They need to think about things like burn rate. But what we're seeing is you can be a lot smaller. I mean, people are dreaming about a single person, unicorn company, like one person who uses AI and distributed networks to do all of the things of a company, and to have a billion-dollar valuation. Will we see that? I don't know.

But certainly when people think about AI, certainly in healthcare and biotech, a lot of people are imagining a magic AI button where you press one button and then it cures cancer. But it could be that the most significant AI and tech interventions for lots of companies are just doing really boring stuff. And so looking at, well, what's taking the time of your employees? And it may be things like accounting. It may be certain aspects of human resource management.

And so, I've written about this at some length. The specific, I have actually three recommendations that I make for companies. The first is, the future doesn't belong to humans alone. It doesn't belong to AI and our technology alone. It's humans plus AI. But how do we operationalize that? And the way I would say is, for every employee in your company, and maybe for the company itself, you can break down what they're doing into a series of about 10 subtasks.

And for every one of those subtasks, you can map it out and say, 10 years from now, will this, do I believe this subtask will be better carried out by machines or by humans? If it's machines, then you should be investing. Well, how do we get the machines to do that subtask well? If it's humans, that's a real area where you should be investing time and energy in helping humans be the best humans they can possibly be. And if it's someplace in between, thinking about those interfaces.

The second, it's continuous learning. Everybody gets, you need to learn what's in your line of sight, but it's learning things from adjacent spaces. And that's the Kodak example and the disruption example that you mentioned in your question. Everybody has to be aggressively learning from adjacent spaces, letting curiosity be your guide, because we'll see things that we've seen in one way for a long time, and then suddenly things will look a little different, and we have to keep asking ourselves why.

And the third point that I hit over and over, and I've said it now a few times in our conversation, is it's all about values. If values and goals aren't your north star, if the starting question is, how do we use these technologies? Every company is going to get lost.

Jeff Kavanaugh: Wel l said. The business model and operating model implications are just mind-blowing here. And the fact that it evolved so much. So, it's exciting. At the same time, it does require a strategy, no matter how fast you move, and maybe that means even more. So speaking more broadly, you state that every company and government must have a strategy for this massive bio-economy transformation. Let's shift gears now. We talked about life sciences and healthcare-specific. Now, what about all the other companies that this bio-economic transformation will affect?

Jamie Metzl: Yeah, it really depends on where you are. But companies that are making stuff, that are using industrial raw materials at very least need to be keeping an eye on this space, because for certainly many decades and a small number centuries, or even larger number of centuries, our model for industrial production and getting the industrial materials that we need is cutting them down and digging them up. And that comes with all kinds of costs, including environmental costs.

And now we have new models of growing industrial materials, whether it's energy resources or plastics or woods, or actually, I was at the Textile Expo here in New York, and there was a great company, Modern Meadow, that's making leathers out of mushrooms. But the leather, it's really high quality and it feels great.

So there's issues of cost and scale, because we've been at this other way of doing things, certainly for decades, if not centuries. But we can see how quickly nature can scale, how quickly rainforests can grow, how the size of the Great Barrier Reef in Australia, we have a 50-mile island of Sargassum seaweed floating off of the Gulf of Mexico, which has been sparked by outflows down the Mississippi River of fertilizer. So nature can grow really quickly.

And so, we're at the beginning of a process. People call it synthetic biology, but it's really, I think a better word is nature co-design, where we're tweaking living systems to do things that we want. And we know that model because that's the whole history of domesticated plants and animals, and we've seen the scope and scale that those have gone to. So it's not that hard to imagine that we could have the equivalent of what we do for food crops, but instead, growing raw materials that could cheaply and affordably become part of everything, whether it's woods, plastics, but do it in a much more productive and sustained way.

So at very, very least, every company should be looking at this space, and they should be looking at their own, their materials that go into their products, their supply chains, and saying, maybe are there better ways of doing this now? But what are the ways in which there might be better ways and cheaper ways of doing these same things one, two, three years from now?

And you don't have to bet everything on day one, but this is really an across-the-board point. If you're not making a bunch of small bets... It's the Clay Christensen model. If you're not planting a bunch of seeds which are going to grow as conditions around you grow, it will not be possible to just do a massive, all at once pivot at some point in the future when conditions change, as eventually they will.

And the second point, I've talked about the superconverging technologies, but certainly in AI and machine learning, we are going to see, and we are seeing a rapid acceleration. And so every company is going to need to really take a step back and try to predict, what are the areas of their business that are going to be disrupted? What are the areas of their operations they can do better now? And again, it doesn't need to be sexy. It could be some really small, narrow, focused things.

And every company needs to recognize, coming back to my humans plus AI point, you have a lot of wisdom already in your company. You have a lot of people already in your company who are really smart people who want to learn. Everybody in every interest, in every industry is being overwhelmed by messages from consultants who want to come in and sell you some magical way to do things.

And there are magical ways of doing things, and certainly I'm not against people doing consulting and offering those services, but companies really need to be careful about not overvaluing outside consultants and undervaluing the people and knowledge that you already have. Your people are your goldmine, and just like you have to tap new technologies, you also have to tap the wisdom of the people you already have.

Jeff Kavanaugh: To put, I guess a cap or exclamation point on your point, two thoughts come from reading the book that were genuine a-has for me. One is, beyond food and beyond that area where genetics might play a role, CRISPR and editing and all that, the materials area and material science. That was a big a-ha. The other was your-

Jamie Metzl: And just on that, let me just add, right now I'm working on the, I'm revising the book for the paperback edition, which is coming out in October of 2025. And just since the book, Superconvergence, came out in June of 2024, the progress in the application of certainly AI, but it's more bigger than AI, to materials, is just incredible.

Just this year in January, 2025, Microsoft publicly released its MatterGen, which is an AI algorithm. And it's really, it's got so much information from physics, chemistry, biology, engineering, it can do 3D modeling. And you can say, hey, here's specifically what we are looking for, here's what we're trying to achieve, and then it can start generating informed hypotheses. I mean, it's really incredible. So we're going to see a lot of this stuff in material science speeding up. And right now, people are imagining asking the question I've just asked, there's a thing that we need. How can we get that better and cheaper?

But we're also going to see new products, and graphene, and there are other examples of this, new products are going to emerge that maybe we hadn't imagined, or maybe we had imagined, but they were too far away and they just seemed impossible. So we're going to really see a lot of new kinds of materials arriving that will allow us to solve problems in different ways.

And again, coming back to the same humans point, machines have creativity. I'm actually now, I'm writing a novella about next generation AI and robots making real human music, and I think that is real. So machines have creativity. But we humans, we have our creativity, which is different from machine creativity, and that's a really essential resource to be tapped for just imagining, what are the problems that we want to solve? What are the interactions that we want to have with our AI systems so that we can get a great outcome?

And I say it over and over because it's just so important, but I hear people saying, humans are the new Neanderthals. Nothing could be further from the truth. These are really exciting technologies that will inspire us, I believe, to be the best humans that we can be. So we need to invest our energies into becoming exactly that.

Jeff Kavanaugh: I like the phrase that these new technologies are our Iron Man suit. It makes us more. That's all.

You paint two futures, one where genetic and biotech benefits solve our most pressing problems, and another dystopian scenario of pandemics and weaponized biotech. You see that the unsexy word governance will be the key to guiding to the better future. How can business leaders use governance to accelerate more of these beneficial outcomes, and prevent the undesirable ones?

Jamie Metzl: Yeah, and we've talked about this somewhat, but certainly, we are already seeing just incredible rewards from these superconverging technologies. And it's easy. You don't even have to imagine. We could just have linear growth from where we are now, and we could solve huge kinds of problems, cure tons of diseases, sustainably feed the world, store our data for millions of years. So many great things. And we could extrapolate from now negative stories and say, hey, this is really scary. We could crash whole ecosystems and undermine our humanity and all of this. So both of those stories are real.

And the difference between them is governance, which as I've said before, is what everybody does. And I have a whole framework in the last chapter of the book for how to think about governance. But your question is specifically about leaders of corporations, because I think companies have a really important role to play, and they have an important role to play for what they do inside of their companies. And we've talked about that, about making clear what are the goals, what are the standards, what are the values, what are the safeguards? Because we live in a world where even individuals are super empowered. So just like individuals can get things really right, I talked about the billion-dollar unicorn, individuals can also do a whole lot of harm. And so, that kind of really thinking systemically about what's the right balance and empowering people to create, to innovate, to learn, but making sure that there are a set of guiding values and principles and norms and safeguards, that's more important than ever before.

Corporations also have the stakeholders in the communities around them, the communities where they work, their suppliers, the consumers of their products. And that creates an even broader ecosystem where the same thing needs to happen. And we live in a world where corporations now have a greater voice than certainly most other times in human history, and certainly in the United States, we've seen that, where one corporate leader, Elon Musk, has already developed some kind of quasi-executive power over the whole country.

And so, whether we like it or not, corporations really have an important role in setting an agenda. I'll just call out one company. Right now, there's a lot of pressure on the DEI programs, and I know there's a lot of controversy in that world, and for me personally, what I will say is certainly with the lowercase D, lowercase E, lowercase I, I think that's absolutely essential for the world and for every company. The capital DEI has become kind of a juggernaut, which I think has its own issues and problems.

But a company like Costco, even, we're having this conversation in the first week of the Trump administration, where there's a massive rollback of DEI, certainly in the federal government, but across the board. But a company like Costco, I've been really impressed. Separate from this issue of DEI, they have put out a very strong statement saying, "This is who we are. This is what we stand for." And that's really important. I think it's important for us as individuals, it's important for companies. It's important for everybody, because there are so many pressures.

You and I, Jeff, are both on social media, and I just try to speak honestly and with an open heart all the time. But every time you say something, and maybe somebody who agreed with you on something last week says, how could it be that you said this and now you're saying that, so you must be in the pocket of whatever, big yogurt or whatever.

And I just think that it's really important for individuals, for companies, for faith leaders, like we saw this week in Washington DC with the Episcopal Bishop, just to be honest with ourselves and to speak about values, because again, I say it over and over, if we make this about technologies, if we don't say, what we are doing is about the realization of our goals and values in a complex and constantly changing and technology-driven world, if we don't do that, we're going to get lost.

Jeff Kavanaugh: Well, we could talk for a lot longer, but I think it's a good point to close on. And before we go any further, we've been hinting or mentioning your book. I'll be formal. It's Superconvergence: How the Genetics, Biotech, and AI Revolutions Will Transform Our Lives, Work and World. And I mentioned because it is, although it's not an academic book, it's so well annotated, so many references and links, it's a lot of detail we didn't get into that is, I think, extremely relevant for business leaders, for anyone interested in this very important area, and folks that make policy as well.

You can find details on our show notes and transcripts at Infosys.com/IKI in our podcast section. Also, anyone who's interested in what Jamie is doing, I think JamieMetzel.com, and we'll have that in our show notes as well. There's a lot there. Much more that we can go into at this point. Thank you, Jamie, for being part of this. And everyone, be sure to follow us wherever you get your podcasts.

Yulia De Bari and Christine Calhoun produced this podcast. Dode Bigley is our audio engineer. I'm Jeff Kavanaugh. From the Infosys Knowledge Institute, until next time, keep learning and keep sharing.