Future of Business: Reid Hoffman on Managing Technological Change and Innovation

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I want to just start with the situation we're in. I mean, I think most of us feel this is a tumultuous time in terms of technological change, politics, civility, you name it. I'd love— your sense on how business leaders can best respond to this moment of uncertainty?

So obviously, it's complicated and it's different circumstances. But I do think that one of the things that's really important for business leaders to do is to think broadly about what their responsibilities are as leaders of this business. Because businesses are not just these little abstract kind of profit generation machines. They're things that live within networks. They live within networks of customers, networks of employees, networks of investors, society, et cetera. So when you're a leader of a business, you're responsive to all these networks. And that's, of course, part of the reason why the classic kind of dictum in business is to be nonpartisan, to be broadly inclusive in lots of different kind of human vectors because You want to be inclusive across all these networks. Now, that being said, I think there's a number of things that are kind of good business articulations. Like when you're a leader, you say, look, this is the kind of society that's better for my operating my business, the operating the health of my employees, et cetera. So like we should have stability, we should have stability, we should have unity, we should be adherent to genuine truth, not the claims of truth, but actual real truth. That kind of thing is really important to stay to those virtues where you're saying, I'm not being, I'm not trying to be kind of partisan in this. Now, there are some areas where people will claim that you're being partisan when what you're being is, you know, kind of rule of law, stability in society. And, you know, it's like, for example, someone could claim you're being partisan by being anti-eugenics or being partisan by being anti-Nazi. You're like, well, that's not partisan. That's just, you know, kind of truth and the right thing for society. And I think that's the kind of thing to kind of do as a leader, and it's what I've been trying to do. So, like, for example, it's interesting on LinkedIn, I'm very careful to post only the things that I think are the kind of the pro, the business perspective about what it is. A bunch of other things about my political views I post in other places. And that's kind of how I sort even my own identity between these.

Yeah, so it's interesting. So you're advocating in a sense, I think, that there are issues, fundamental issues that every business has, and they won't be the same from business to business. And on those issues, maybe you shouldn't be silent, that you need to speak up. And I asked it just because I think there's a fatigue, I guess, about— and people have gotten their fingers burned trying to wade in with what they feel is a fundamental value, and then it just sort of blew up in their faces. So it's a minefield. And it's interesting that there are some people like you who dive into it, and there's some people who really feel the safest place is to have their head in the sand. And I suppose you're talking about a middle road, which is you need to be engaged when it's really fundamental to your business, to your businesses, your institution's values.

I would change the metaphor slightly. I mean, I always like driving down the middle of the road, you get hit by cars going both directions, although it might be actually an appropriate metaphor in this circumstance. But it's kind of more foundational. It's kind of the question of, look, if you're being a leader, you're being— and this is one of the things I think is really healthy and great about American society is that business leaders are leaders. Our leaders are not just political leaders. Our leaders are not just military leaders. Our leaders are not just university leaders. But they're also business leaders. And actually, I think part of the health of society is fundamentally in the health of business. So articulating what kinds of things are good for the health of business. And I tend to find that business leaders who say that the only really relevant variable is corporate tax level or tax level are clearly very narrow-minded in kind of what their— the only variable. It is a variable, but it's not the only variable in the health of society. And so it's important to have the discussion, but to have the discussion with thought and civility. I'm making the argument for what is a better case for business. You can make an argument back, right? But it's a civil discussion.

So let me switch gears a little bit. You have had an incredible career in Silicon Valley and driven in part by being really good at discerning weak signals before they become obvious to the rest of us. Is there a method to this? Is there anything you can impart to this audience on how to do that better?

There absolutely is. And what you do is you think about— I mean, you kind of start with kind of the Wayne Gretzky line, which is things are changing and go skate to where the puck is going, not to where the puck is right now. And so you should start with asking yourself that question, which is, OK, so what are the ways in which things could change or seem to be changing? And then what are the consequences of that? And if you say yourself, You may generate some of the ideas, but then go ask people in your network. So, it's kind of the classic thing that I ask when I'm talking to technologists is, what do you see is going to happen in the next 1 to 5 years in this technology? What do you think might happen with it? What do you think people think might happen is actually not going to happen? It's going to happen differently. And then you begin to think about, okay, which of those things track to what actions you should take differently? And part of it is always probabilistic. Being overly certain is wrong. Whereas, whereas kind of thinking, okay, there's a good chance of this. So it's a good chance. What does that mean I should do now? Because very rarely it's like I should presume 100% unless I can just correct from it. But it's like, oh, I should do X. Now, some of that's investing, some of that's deploying technologies, some of that's, you know, kind of guiding an organization on towards what you're doing. And so, for example, you know, it didn't it didn't surprise me that the general press discourse around AI was, oh my God, it's going to change everything. It's going to be like a total shakeup. And people are generally more pessimistic initially, disaster. There's like, oh, is all this AI thing is doing is kind of like how you help you cheat at homework? And it's like, no, today with these AI things, literally anybody who is a white collar professional or is doing anything with language, It is a tool that is useful today. And if you haven't discovered how it's useful to you, that's because you haven't tried enough, right? It isn't because I wanted to say, write me an investment memo. Oh, look, it wasn't very good. Okay, try other ways. Like, what should be the due diligence? I upload my investment memo and I say, what should be the due diligence questions that I'm asking on this? You might find something interesting. So anyway, so that's the kind of the looking at the future is what are the different trends. And one obviously massive set of trends that I look at is technology. But by the way, it's also markets, it's investment and capital, it's competition and different kind of workforces, it's kind of changes in regulatory law or social considerations. And you look at all of those things and you go, okay, what might happen? And if that might happen, how should that change what I'm doing now?

So I want to talk a little bit about the sort of man versus machine and as you just said, There are pessimists who are, who are concerned. Uh, you're actually— you've actually argued that tech technology, instead of this sort of man versus machine, that technology makes us all more human. Can you explain how that works?

So it goes all the way back to like, why do we have like the, the, the centers of all of human progress have been the creation of villages and cities, and that's result of technology, agriculture. We go, okay, this is technology, this is technology, we're speaking through technology. All of these things change the pattern of how we live, how we do business, how we create products and services, how we market them, deliver them, how we do financial analysis, how we media communicate, all of it. And so opposed to thinking of ourselves as Homo sapiens, because we go, oh, what's really important is how we think. Of course it's very important. But by the way, the pattern of sapiens and how we think is technology. So for example, once we get to the written word, once we get to the printing press, once we get to the internet, once we get to podcasting, all of these things are we evolve through technology. And that's true at the macro level, the history of human societies. And that's true at the micro level of, for example, you say, well, okay, I'm a writer, but I don't use word processors. Well, it's possible. It's very hard. A graphics designer, I don't use, you know, kind of Adobe or Figma. No, very hard. And so it's kind of the question of these tools are how we progress and we learn. And The AI tools are going to take every single tool that you use in a professional context, because even like email or meetings or other things, and is going to bring mass, like bring them to the next level, massive new transformational features. And that will be happening over a small n number of years for that. And so what does that mean for you? What does it mean for your organization, et cetera? And that's the person plus machine. Now, What happens is people say, well, shoot, if I, if I make my marketing people 10x more productive, am I going to, am I going to, like, for example, um, you know, lay off 90% of my marketing people? Well, you know, look, sales, marketing, those are competitive functions between businesses. The whole point is to be a lot stronger, or, you know, relative to your competitors as you're doing things. I don't think you're going to lay off any marketing people. I actually don't even think you're going to lay off any salespeople. What you're going to do is you're going to say, I'm going to refactor the throwaway to my department for that. Some of that may be trading some people who cannot use the new tools. Yes, that's part of the job transition. But some of it is upskilling them and some of it's hiring some new people to do it. And it's using these new tools in that competitive game that is sales and marketing. And when you look at the whole swath of an organization, you say, well, like I could use a lot more engineering. You say, well, what about like legal and finance? It's like, well, actually, in fact, we kind of do the amount of legal and finance that we can afford in our organizations. Like previously, when the Excel— like when spreadsheets, VisiCalc was created, people said, oh, accountants, all these people who are doing double entry accounting and calculators and books, they're all going to go away. And yes, that function went away. Accounting didn't go away. Accountants now do much more detailed analyses about risk factors and scenario planning and, you know, kind of revenue attribution and financial modeling and all the rest. And that same kind of thing is going to happen when you get to legal, when you get to finance and so forth as part of how AI works. So it's that exact human plus machine. And that's why I call us Homo Techne. And that's the natural pattern of it. It doesn't mean that there aren't lots of transition issues and those transition issues are real. One of the nifty things about AI is that AI can also help with the transition issues. So you say, like, unlike, for example, I go to the accountant and say, here's this new thing, VisiCalc. And it's like, oh shit, I gotta learn this. And some people are like, well, here's this new thing, AI. And by the way, the AI is gonna help you learn it too.

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All right, so let's spin forward then. So as you think about the future and 10, 15 years out, do man and machine merge? I mean, how do you imagine that the delivery of all this and the merging of man and machine What does it look like, do you think, in 10, 15 years?

Well, 10, 15 years is a guaranteed way to look a little foolish, because the future is almost always sooner and stranger than you think. And so obviously some science fiction technologists will go, well, we'll have, you know, kind of the equivalent of neural implants and other kinds of things. And some will say, hey, it's now kind of like an earbud or something as a way of doing this. I tend to think that when we see this, we tend to be and. So we'll still have a phone, we'll still have a computer or a display interface computer and so forth. But it certainly would, I think part of what generative AI is gonna do is the interface to all of this stuff becomes much more natural language. Like we've had to learn when we interacted with these, devices to be, because they're very brittle in terms of they need an exact semantics. And part of what we built is like a windowing environment and so forth to make the semantics much more naturally translatable. Like I'm pointing at this and, you know, I want to turn on the mic here and I want to, you know, readjust the sound there and other kinds of things as ways of doing it. And now with AI, language is not so brittle. We're going to use language a lot more. And so I tend to think like when we're doing precision, we'll be typing. And when we're like, oh, I want to write a memo about AI's impact within the manufacturing industry and how actually in fact the information ecosystems will actually in fact have the following kinds of efficiency and da da da. And you're like, you're just kind of like throwing it all out there and it then starts acting on it. And so I think a whole set of the devices, the complete interface all the way down is going to change on that. And so if you ask me to kind of guess what the most the kind of the newest thing might be is kind of a generalization out of kind of the equivalent of earbuds, where you are using language fast and a lot more efficient, like kind of quick on what you're doing. Because, you know, like, for example, we can all almost, almost all of us can speak a lot more fast Faster than we can type. And part of the reason why we type is because it gives us a precision, different metaphor. But when the thing is interpreting you and getting your interpretation right, then it doesn't really matter if your sentences are not fully grammatically correct while you're speaking. You literally will just start going, oh, like for example, like I was doing that memo on manufacturing, go, memo, manufacturing, AI, information supply chains, increased efficiencies, you know, da da da da da. And it goes, oh, you're looking for something like this, da da da da da. And then it starts. And And our thinking and patterning becomes much more like video game playing in terms of the way we operate than the current discourse of I sit in a room and I think for a couple hours, you know, as we do it. Now, I'm not saying we won't be doing that, but all of a sudden we have this new way of using the tools and that kind of new front-end tool I think will be primarily kind of language-based. Now, obviously some people are working glasses because you see the whole world. And when I look at the screen and look at Audi, it'll go, "Oh, ask Audi this question," or something. And obviously, we've seen Minority Report as a movie and other kinds of things as ways where these come out, but audio first, I think.

So let's jump back to 2024 for a second. So you've had fun, I guess I would say, with the sort of fake Reid Hoffman, using AI to create an animated likeness. So I'm interested, what have you learned from this experience about ability to do more with your brand and likeness, and what have you learned about the ability of others to use the technology to hijack your brand and likeness?

Well, we always have some serious issues with deepfakes and so forth. We're in political season. There's obviously the set of things that are happening there. The, you know, I think that one has to be careful about that kind of stuff. Now, part of the reason I did it is I wanted to show even in this kind of what is obviously very worrisome technology, because deepfakes are worrisome across everything from political elections to, you know, what's going on with the harassment of teens and other kinds of things, is you kind of go, okay, what's the, you know, kind of set of things that can also be very positive? And, you know, like, for example, you know, one of the things in terms of communication, you know, why are people here? They want to get a sense not just of what I'm saying, but who I am and all that kind of thing. And people, you know, I only unfortunately only have the ability to speak one language with any real coherence. And yet when I gave the kind of honorary doctorate speech in Perugia, I had it, I had Read AI give it in Italian, in Hindi, in Chinese. And so you have that kind of human connection and that capability of not just translating in those languages AI, but delivering it that way. You get a broader brush of, you know, I can only select very few events like this one that I can actually speak at. You know, I'd say I probably turn down 99 for every one that I accept, maybe even more. And yet now that I have the other thing, I say, oh, that's a really valuable, that's a great, you know, like young student group at, you know, the University College London. I'll have the, I can allow the Read AI or like, for example, that Eric Brynjolfsson teaching that business school class at Stanford. I'm out of town, I got a career commitment, but Read AI can come and do that and help and participate. And so those are all the ranges of kind of the positive things. You know, I'm not yet the recipient of a negative use of a deepfake, versus a digital twin or something else with Read AI. But obviously, those things will happen, and we need to navigate them as a society.

Yeah. Um, so I want to go to a couple audience questions. This is from Jaime, co-founder at Latin Leap. So the question is, given your deep involvement in both AI and the startup ecosystem, how do you envision generative AI transforming the entrepreneurial landscape?

Oh, um, it's massive. So on one hand, you get to the kind of professional thing of like every individual should be trying to use. GPT-4 and, you know, all the others, you know, a number of the others as a feature. So their attributes— entrepreneurs tend to be adoption of, of new technology. So it's kind of like, well, you know, writing my, uh, doing my research, doing my PowerPoint, doing my marketing materials and my sales materials, figuring out how to recruit, figuring out which, which venture capitalists I should talk to. So on a micro level, they'd just be massive across all these fronts. Then on like, okay, well, what kinds of, of products and services. Because part of what happens in entrepreneurship— and this is to your earlier question, Adi, of, of kind of like anticipating the changes in future— part of what opens up entrepreneurship is, is new markets, new products, new services. And you say, well, what's going to happen because of this that the, uh, other incumbents or maybe other startups haven't seen yet that I can see and I can go operate on? And classically, new platforms open up room for new massive technology companies. Like, you know, the internet gets to Google and Amazon, and then Web 2.0 gets to Meta, right? And, you know, and these are kind of— and obviously Meta gets a lot bigger with its successfully transitioning to mobile. And then, of course, you have like Apple reinventing itself with the iPhone. Each of these kind of things, these technological platforms, it creates entirely new ecosystem areas. And the startup you know, Google, Amazon, Meta, you know, kind of do that quite well. AI is going to be doing the same thing. Now, it doesn't mean that creating your own frontier model of these super side scale is the right thing. That actually, I think, will very quickly not be a zone of startups, but only a zone of the hyperscalers, or most likely, you know, 99 plus percent. But on the other hand, like a whole bunch of startups that I'm investing in that are transforming productivity, transforming medicine, transforming applications within the enterprise. And all of those things that, you know, my partners and I at Greylock are looking at doing, those create massive new kind of startup entrepreneurial openings and activities. And then there's this question around, like, for example, the surfaces of existing products massively change. Maybe companies will adopt it the right way, or maybe they won't. And when they don't, that's frequently when a challenger can challenge an incumbent and, and make a new product area, you know, whether it's, you know, a CRM product or something else. And so I think that's, that's all in the, uh, in the entrepreneurship arena.

So here's another question from the audience. This is from Sanchit, who identifies as a student, who asks, since AI is made by humans, do you think that AI ultimately will be limited to kind of the human capacity? In other words, human folly becomes AI folly, or do you think it could transcend these limitations?

Well, we definitely already have pretty good examples about how technology made by humans adds in superpowers that are beyond what are human superpowers. And it isn't just in the physical arena, try driving in a car versus running, but also You know, kind of mental, like computers and their ilk add a huge amount of mathematical capabilities to what otherwise would be mistakes. Now you say, well, look, the deeper version of the question is, are there, you know, tendencies for human beings, like, for example, to have confirmation bias in decision? And so does that lead you to, you know, the kind of thing that gets replicated within the devices? And the answer is some and some. So obviously there will be blind spots that we won't see our way around that we'll have to work on in order to do, just like we do with collective human beings. And that's part of the reason why we do a lot of work joint, because it helps us, not just the number of hands, but the collective cognitive capabilities and the diversity of those cognitive viewpoints bring in to solve problems. But also there will be a bunch of areas where that will that will help. So for example, if you say, well, I have a confirmation bias, but now I have an agent that's looking at the information with me and goes, well, you do know there's some really good things that contradict this confirmation bias. And you go, oh, well, tell me about them. So I think it's, generally speaking, a lot better, not just it's only replicating our biases, but doesn't mean that we can't just rely upon it and it will be an ongoing work.

Yep. So we probably only have time for one more question. This goes fast, but this is from Lena, an IT business analyst, and she's picking up on the— or Lena is picking up on, you know, what is— on the techno-humanist ideas of yours. So the question is, what does a successful techno-humanist society look like? Again, it's out in the future, in the next 10 or 20 years. What are key milestones that, you know, one should look at along the journey?

What I would say is, how do we have technology amplify what do we think are the key characteristics of kind of human existence? And the one way to look at it in terms of the virtues is, you know, when we look at the inverse of what we think of as inhuman. So we go not just intelligent or not just smart or not just quick, but also wise, compassionate, etc. And how can all of the various technological elements and how we navigate individually but also navigating groups and navigating society combined to making us better. And, you know, obviously when we look at a bunch of mostly video media, you know, anything from Black Mirror to those are things they all come down to man versus machine, machine, you know, ruining things. But actually, in fact, when you look at it, you know, what we've done over time, there's a transition period. And so, you know, we had to get through the Industrial Revolution. We had to get— we had to integrate the printing press and all the rest. But we get through it. We suddenly get to a much more elevated human circumstance where we're better educated, we have better perspective, we have room and chance for dialogue on different points. And I think that's the continuation of the thread. And I think that's what we'll want to see with, you know, we're going to have, you know, kind of millions of AI agents. And how do those millions of AI agents help us with that?

So I'm actually going to ask one more question. This is from Kristen, who is CEO at pad climbing. And it sort of comes at all of this from a different angle. Kristen says, AI could easily allow us to ask for best practices like a mentor, but it will come up with basic solutions. So, you know, and I, you know, some of us have experienced that, that, you know, generative AI is incredible, it's fast, but often the text is generic. So the question is, how do we kind of make sure we're infusing the creativity that's needed to build the network so it isn't predictable and generic, but is actually something creative and remarkable?

Well, one of the skills— there's a whole long set of answers to this, but even the current AI tools— is pay attention to the skill of prompting it the right way. It's kind of like if you come and ask, you know, someone like me and say, well, what's the— what are the things that create an enduring business? You go, well, it's a really good set of products and services that have good operating margins and good competitive modes. And you're like, yeah, yeah, blah, blah, blah, blah, basic. Um, but if you say, well, you know, what are the places where adding intelligence and artificial intelligence transforms all elements of kind of how a normal business operates, then you get a better answer. The same thing as in prompting these AIs. And so for example, I very rarely just go like, write me an investment memo on AI. I will go, write me an investment memo on this. Highlight the following possibilities of concerns. Make sure you address the questions around capital efficiency in model deployment and where models are going, et cetera. And then you get something much better. And so for more pizzazz, frequently if you prompt them to say, give me 3 very different answers. To this question. And then all of a sudden, you're less in the vanilla mainstream. And that's just the beginning of looking at how we use these tools, what the prompts are, and all the rest.

[MUSIC] That was Reid Hoffman, the co-founder of LinkedIn and Inflection AI, in conversation with HBR editor-in-chief Adi Ignatius at our Future of Business virtual conference. I hope you listen to all of our Future of Business series and all of the episodes we have on the HBR IdeaCast about leadership, strategy, and the future of work. Find us at hbr.org/podcasts or search HBR on Apple Podcasts, Spotify, or wherever you listen. And if you don't already subscribe to HBR, please do. It's the best way to support our show. Go to hbr.org/subscribe to learn more. Thanks to our team. Senior producers Anne Sanny and Mary Doo, associate producer Hannah Bates, audio product manager Ian Fox, and senior production specialist Rob Eckhardt. And thanks to you for listening to the HBR IdeaCast. I'm Alison Beard.