How Generative AI Changes Creativity

From prehistoric cave paintings to an inventor’s Eureka moment, creativity has always been described as a particularly human trait. But something strange can happen with generative artificial intelligence. Your ideas can take shape far faster. You also get ideas that you might never have imagined on your own. So, who is the creator here? What is creative work in the era of generative AI? What is innovation in this emerging world?

In this episode, How Generative AI Changes Creativity, HBR editor in chief Adi Ignatius speaks with video artist and consultant Don Allen Stevenson III about how generative AI is disrupting creative work and the creative industry. Then Ignatius speaks to two innovation researchers, Jacqueline Ng Lane and David De Cremer, about changes to the creative process within organizations. Lane is a professor at Harvard Business School. De Cremer is a professor at the National University of Singapore Business School and a coauthor of the HBR article “How Generative AI Could Disrupt Creative Work.”

How Generative AI Changes Everything is a special series from HBR IdeaCast. Each week, HBR editor in chief Adi Ignatius and HBR editor Amy Bernstein host conversations with experts and business leaders about the impact of generative AI on productivity, creativity and innovation, organizational culture, and strategy. The episodes publish in the IdeaCast feed each Thursday in May, after the regular Tuesday episode.

How Generative AI Changes Strategy

And for more on ethics in the age of AI, check out HBR’s Big Idea on implementing the new technology responsibly.

May 11, 2023 Transcript :

HBR EDITOR IN CHIEF ADI IGNATIUS: Don, you are an artist based in Los Angeles. I’d love to hear you talk about that moment that you realized that, okay wow, this generative AI is doing incredible things. And to what extent did you feel, at least initially, that existential dread?

DON ALLEN STEVENSON III: Yeah, I mean, it really kicked in pretty fast. I would say within the first couple of hours of playing with these tools, it started to sink in that this was going to fundamentally change what it meant for the value of my own work. In the past, I made a lot of money off of kind of how much time something used to take me, whether that’s an augmented reality filter for a client, a commissioned art piece, a 3D model, a 3D sculpture, a video edit, an animation, all these things used to take a lot of time. So if it took a week, I might be able to charge more, and if it took a day, I would probably charge less. So when I started playing with the earliest text-to-image editor generative AI tools, I was realizing that the iterations of ideas that I can get through and show to a client shrink the time to almost zero.

What would’ve taken me a week to iterate and think of before having a sketch that I could show a client, well, now that just takes a few seconds. And so that suddenly hit me hard because I had to really rethink what it meant for me to exist as an artist. It’s going to really change what it means to do artwork professionally. It’s going to change what the expectations are for artists as well as clients. And so the dread really came from this idea that, well, I’m going to have to change a lot of what I thought my future was going to be.

ADI IGNATIUS: Welcome to How Generative AI Changes Everything, a special series of the HBR IdeaCast. From prehistoric paintings in caves, to an inventor’s Eureka moment, to the collaborative imagination behind breakthrough products, creativity has always been described as a particularly human trait. But something strange can happen with generative artificial intelligence. Sure, your ideas can take shape faster when you use these new tools. But you also get ideas that you might never have imagined on your own. So, who is the creator here? What is creative work in the era of AI? What is innovation in this emerging world? This week: How Generative AI Changes Creativity. I’m Adi Ignatius, editor in chief of Harvard Business Review and your host for this episode.

In this special series, we’re talking to experts to find out how this new technology changes workforce productivity and innovation. And we’re asking how leaders should adopt generative AI in their organizations and what it means for their strategy.

Later on in this episode, you’re going to hear from Jackie Lane and David De Cremer, management professors who research innovation. And I’ll ask them how generative AI can change the creative process within organizations.

But right now, I’m talking to Don Allen Stevenson III. He’s a video artist and consultant based in Los Angeles. And he has worked at the animated film studio DreamWorks. He also collaborates with freelancers and independent artists. And he’s been using generative AI in his work for clients. Don, thank you for coming on the show.

DON ALLEN STEVENSON III: Thank you so much for having me. I’m very excited to be here.

ADI IGNATIUS: So we talked about that first moment when you realized generative AI’s potential in your world, that kind of moment of existential dread. So since then, obviously you’re learning it, you’re playing with it, you’re creating with it. What have you learned about the technology and how it affects the creative process?

DON ALLEN STEVENSON III: Well, for me, it’s actually helped me to experiment a lot more with riskier, more out-there ideas in creativity, because in the past, it would’ve taken too much time to experiment with the vast creative ideas I would like to do. And so now, because a lot of that iterative cycle is replaced with just kind of instant feedback, I’m actually allowed to explore and do a lot larger scale projects, which has actually been really productive, really positive for me.

ADI IGNATIUS: Can you talk about some of those projects?

DON ALLEN STEVENSON III: Sure. So in the past, oftentimes I would like to tell more animated stories, but it takes a lot of time to create 3D characters, to give them bones, give them the ability to move, to place them into worlds, to render them into the scenes, to relight them. All of these steps are normally pretty time-consuming for someone who just wants to tell a short story. So all these things in my past I might have resisted, but now there’s tools like Wonder Dynamics that came out that basically streamline this entire process of creating characters that are embedded in live-action video.

Now, instead of me having to go and animate characters manually one by one, I can just film with my phone camera, somebody acting and performing in front of the camera. And when I process that footage, it comes back with a character replaced in the person’s place. So if there was once an actor raising the right hand and waving, I would get that footage back and it would be my 3D character waving, and the actor would be physically removed from the frame and all of the pixels cleaned up. And that would’ve taken me weeks, and now it could be done in like an hour.

ADI IGNATIUS: So that is amazing. That’s an amazing example. I mean, here you’re talking about like we can all create Pixar.

DON ALLEN STEVENSON III: Yes.

ADI IGNATIUS:

It’s sort of almost that level of quality.

DON ALLEN STEVENSON III: It is that level of quality.

ADI IGNATIUS: So does that mean you don’t collaborate, whereas in the past, not only would this have taken weeks, you might have been working with a team of people? Does this eliminate collaboration for you?

DON ALLEN STEVENSON III: So some of the tools eliminate collaboration and other ones actually encourage it. I’ve actually been collaborating more on short films since using Wonder Dynamics because I need actors. I need someone who can operate the camera really well. That being said, I don’t need the same massive size of a team to produce a short film, so the number of people has reduced. Now that I can kind of spearhead and streamline the effects process, I kind of have more time and energy to bring on more people if I want to.

ADI IGNATIUS: Yeah, that’s really interesting. It’s sort of counterintuitive, but I think I get that that it enables you to think bigger. And what’s also interesting to me is, we’re talking about a technology and we’re marveling at its possibilities. We’re just a few months into this thing. So it’s going to get better. It’s going to do more I assume. Can you talk a little bit about how the technology has improved even in the months maybe it is since you’ve been playing around with it?

DON ALLEN STEVENSON III: Sure. So I’ve been playing with the AI tools for about a year and a half now, which makes me really old school. Which is so weird, a year ago where the state of the art of artificial intelligence and generative AI was, people don’t even care about it anymore in the same way. But one of the biggest changes I’ve noticed from the creative industry is moving away from just being impressed with 2D images and moving into a world where we’re now expecting and being impressed by video that’s generated, and 3D animation and 3D performances and 3D characters that are generated.

ADI IGNATIUS: So, Don, I understand you have a relationship with OpenAI, which is the firm that developed DALL-E and ChatGPT. You mentioned that you sometimes feel like a dinosaur just because the technology is moving so quickly. But given the conversations you’ve had and what you’ve seen, what does the future hold? I mean, will generative AI kind of hit its limit, or are we going to see dramatic improvements to come?

DON ALLEN STEVENSON III: So I’ll start off and say that I’m going to speak from my own personal experience of what I’m allowed to say and what I think is public and availably open knowledge and assumptions that I can make. So on that, I would say that we’ve just scratched the surface of what generative AI can do. I’m already very impressed with what it’s publicly able to do, but to be honest, this is not even close to what it’s going to be like in even a year from now. Because imagine you’re trying to learn a concept and maybe you go today to ask ChatGPT, I want to learn about the moon. How far away is the moon? And ChatGPT would do a great job at explaining that number and writing it to you in text and giving you a nice little paragraph about some science about the moon.

What I think is going to happen probably pretty soon is, you’ll ask the same question and imagine, you say, well, can you help explain it to me? I’m more of a visual learner. And so then ChatGPT or a model like it that might come out might actually share an animation with you. An animation that would help explain the concept of the distance of the moon visually, because we’ll be moving away from having it be just text output to having it be image output, video output, 3D model output, 3D environment output. First, it might be a 2D image, just shows a moon, some solar space, earth, and maybe a line between the two. Then it’ll probably eventually become a video, so you actually see stuff moving around. It shows maybe the distance being drawn between the two, and then after it’s drawn, it then puts in the distance. And then eventually it’s going to be 3D. It’ll actually just pop up like a 3D model of a moon that it generates and 3D zoomed-in picture of earth, and then showing that distance, generate visuals that would help accommodate the learning.

ADI IGNATIUS: Amazing. So from everything you say, I mean, it sounds like somebody like you who is creative, who is not afraid of technology in the sense of you’re willing to roll up your sleeves and try to master it, but there may be people who are several rungs below you in the experience chain who because of these tools can actually create what you create almost, right? A sort of good enough version.

DON ALLEN STEVENSON III: A hundred percent.

ADI IGNATIUS: Yeah. So do you worry about your ability to get compensated and recognized as an artist when all of us suddenly have these tools at our disposal as well?

DON ALLEN STEVENSON III: So I’ve actually in this last year have been transitioning away from being identified as an artist because of all these AI technologies. Instead, I’ve been moving more into basically doing consultations, doing inspirational videos, public speaking gigs. Those are actually what are going to pay the bills now as an artist, not the art itself, unless you’re a very specific niche brand that people already love and care about. It’s going to be really rough right now for people that are only identifying as artists, especially if their output is solely digital.

ADI IGNATIUS: So that’s interesting. So you’re not self-identifying as an artist now, but what does it mean to be an artist now in this era of generative AI where suddenly we have amazing tools at our disposal?

DON ALLEN STEVENSON III: Yeah. So the good news is, if you’re creative, what it means right now is you’re able to bridge domains that normally don’t talk to each other and have them interact in new and innovative ways. But someone who’s a specialist in one category or domain, they’re the ones that I would say are in the most danger zone for generative AI. Because if you’re a specialist and it’s a very narrow field of tasks, these are exactly the kinds of things that AI systems would like to get training from. It’s a very specific narrow data set. They don’t have to work as hard to generalize if you’re a specialist, but they have to work very hard if you’re a generalist at trying to clone and copy what you do. So if you’re a creative that’s being a generalist, you’re safe. If you’re a creative that’s being a specialist, you’re not safe at all.

ADI IGNATIUS: The revenge of the generalist, I like this world already. So Don, as this technology is starting to take shape and potentially reshaping your world, my world, everybody’s world, so let’s say as a creative, how do you make sure you’re part of what it does in the future rather than getting steamrolled by it? I mean, what’s the best wisdom so far?

DON ALLEN STEVENSON III: Yeah. So if you’re a creative and you’re trying to figure out how not to get left behind right now with all of this innovation in AI, the main thing that you can do is actively experiment with the tools. The ones that are too scared to even touch this stuff, there’s no space for them, unfortunately.

ADI IGNATIUS: So Don, given all of this, is the product that you are giving to your clients going to be different in this world?

DON ALLEN STEVENSON III: Significantly different. The main way that it’s going to be different is that now I have to show my work on how I got to the output for my clients so that they can actually see the human effort, the human fingerprints, the human touch that was put into whatever that output is. So if you’re a video editor, your fingerprints are showing screenshots of what your sequencer window looks like. If you’re an illustrator, then your work is showing a time-lapse of how you actually made that piece. If you’re a writer, it’s showing all of your rough drafts and all the versions that you went through before you got to your final thing that you wrote. These are just a few examples of showing your work in a world where the output is not going to be enough to understand the value.

ADI IGNATIUS: That’s fascinating. Yeah, none of us has had to show their work since school.

DON ALLEN STEVENSON III: Right? It’s like, oh, because the output was the most important thing. And then now, it’s like, well, how did you get there? How do I know that you didn’t just generate this whole entire podcast with AI using voice synthesis? How do I know-

ADI IGNATIUS: Interesting. So there’ll be a whole parallel industry that’s about trust.

DON ALLEN STEVENSON III: Yes.

ADI IGNATIUS: It’s about trust and verification. That is a really interesting observation.

DON ALLEN STEVENSON III: And the reason why I feel like I need to show that is so that people know that it’s me who made it. They’re not going to believe me when I say I made this anymore because it could have very easily just been generative. But if I can show me making that thing that someone bought, oh wow, there’s a real human behind there, oh wow, it’s a real human artist, they put a lot of effort, the value is clear.

ADI IGNATIUS: Don, thank you for speaking with us. Thank you for sharing your experience.

DON ALLEN STEVENSON III: Of course, so happy to be here.

ADI IGNATIUS: Coming up after the break, I ask two experts on innovation: How does generative AI change the creative industry and the creative process at firms? Stay with us.

ADI IGNATIUS: Welcome back to How Generative AI Changes Creativity. I’m Adi Ignatius. Joining me now to discuss how generative AI will change the creative process within organizations and how they innovate is Jackie Lane, a professor at Harvard Business School, and David De Cremer, a professor at the National University of Singapore Business School. He co-wrote the HBR article, How Generative AI Could Disrupt Creative Work. So Jackie and David, thank you for joining me.

PROFESSOR JACQUELINE NG LANE: Super excited to be here.

PROFESSOR DAVID DE CREMER: Thank you, Adi. I’m really happy to be here.

ADI IGNATIUS: Good. Well, Jackie, I want to start with you. You have studied innovation at NASA, at hospitals, at big digital firms. I know you’re now looking closely at generative AI, at ChatGPT. Help us figure out what is unfolding now. What can generative AI do already today, let’s say, for companies that want to innovate with it?

JACKIE LANE: Yeah. So I study how we generate ideas and how we evaluate them. And so a lot of my research focuses on crowdsourcing. And so when I first heard of generative AI and the capabilities ChatGPT, I thought, “Wow, there’s just a lot more capabilities and possibilities that are available both from the idea generation side to diversify the kinds of ideas, more innovative, more breakthrough ideas, and then also there’s implications for how do we pick and select that.” And so I think that it’s a super rich and exciting time for companies.

ADI IGNATIUS: With crowdsourcing, if you want to, you can find the human fingerprints that are on ideas as they develop. With generative AI, it’s hard to tell where these ideas come from. I mean, it’s a sort of mashup of old knowledge, and I’m never sure if it’s something lifted almost plagiaristicly or it’s a trope that the bot has come up with. How do you deal with the quality and the reliability of what a ChatGPT is generating?

JACKIE LANE: Oh, that’s a great, great question. I mean, we need human agency in this too. And so for example, if you’re trying to think of how do you do the business model for a real estate startup, you could get ChatGPT to give you some ideas. You’re right, there is the question of quality. And I believe that there’s also powers of using ChatGPT to help us with filtering these out. In the beginning, it could be filtering out the low-quality ones, but going forward, we can get better at training our models to come up with those better-quality ideas as well.

ADI IGNATIUS: And when I think of how companies innovate, how they experiment, you think of design thinking approach with rapid experimentation, you think of brainstorming, rapid prototyping, all of that. What’s the role of a generative AI in some of these processes, do you think?

JACKIE LANE: Yeah, for sure. I mean, there’s a famous study that was done by Hargadon and Sutton on the design consulting firm IDEO. And the competitive advantage for those designers was to be able to take and understand knowledge from one domain in one technology or industry and apply it into another one where it wasn’t known. And that’s, I think, one of those beautiful things that ChatGPT can help us with. It’s to give us those kinds of recombinations from different industries and domains in ways that we might not necessarily think of them ourselves. It’s not like everyone has this kind of experience or this exposure that the IDEO designers had, but ChatGPT can enable people who don’t sit in those cross-boundary positions to be able to come up with those types of recombination.

ADI IGNATIUS: So David, I want to ask you, I mean, one of the interesting things about this new technology, it’s not like a supercomputer that churns out information faster than we’ve ever seen. It’s capable of doing things far more interesting than that. And there are examples of architecture firms using generative AI to churn out new designs to share with their clients, drug companies who use it to conjure up candidates for therapies to study, companies creating imaginary customers to interrogate as part of product development. It has really amazing uses. Reflecting on all this, can this help make firms better at creating new markets?

DAVID DE CREMER: Creating markets, at the moment, I’m not too sure about it because not only for generative AI but AI in general, if you look at how do they create value for companies, usually it’s promoting efficiency, making sure that people work better. But I hardly see that AI is really capable or even being used to create new markets. I think that’s something that’s not really happening yet. So that kind of value, I don’t see being created that easily.

I still believe it’s an augmenting tool, but humans are in charge. And the reason why I’m saying this is because I look at creativity in the following way. Creativity or a creative solution for me is something that is new, it’s a novel idea, but it needs to be useful. It needs to be useful to solve something that humans care about. And this is where AI in general is lacking. It doesn’t have that sensitivity. So AI can do the first part. It’s new, I generate as many ideas as possible, but then we need to verify, we need to edit, and we need to see is this something that’s useful. Is this useful to solve a problem that we care about?

ADI IGNATIUS: Yeah. Well, those are good questions. And then there’s the whole kind of ethical line of concern. And I guess I’m interested, David, to what extent are you thinking about ethical considerations when you’re using generative AI in the creative process?

DAVID DE CREMER: Well, I mean, first of all, let me say, with any new technology, if you look in the past, of course, if we didn’t take the risks, many of the things that we know today, we wouldn’t have if we would shut it down right away. Having said that, I’m not someone who likes to see, hey, let’s see what happens. And then when it goes wrong, okay, then react. So we can anticipate already. And some of the things we can anticipate, I think you’ve referred to already is, it has such access to the World Wide Web. It scrapes everything. It knows everything. It has all these data sets available. Obviously, one of the things that comes to mind is then IP rights, the intellectual property rights. So that’s one ethical issue.

The second is what I see ChatGPT is being used in terms of its applications a lot. And one of the more recent ones where you can see in the US is like, can it replace doctors? For example, let’s say you’re sick, you’re developing a flu, you don’t know exactly what it is. So the first point of contact will be ChatGPT, to see, okay, what will be the diagnosis that AI brings forward. And then if it’s severe enough, you may be transferred to a human doctor. I don’t want to end up in a world like that where insurance companies are going to decide these are the decisions about your health. So we really have to think about, again, how will we use it.

ADI IGNATIUS: So Jackie, are there now early good practices that are emerging in implementing this technology into workflows, into corporate creative processes?

JACKIE LANE: Yeah, no, I think that’s a great question. I mean right now, everything is in its infancies, but a lot of the way that work gets done in companies is at the group level. People work in teams, multiple teams in different groups. And I think the question is, how does ChatGPT or generative AI fit into that workflow? And so if we go back to the basics of idea or group brainstorming, I think there’s a lot of evidence from studies that have shown that groups tend to come up with better ideas when you do it alone first, and then you share your ideas with one another. So you can imagine a world where that process still exists, but you could insert generative AI into that individual aspect.

And so instead of you coming up or an individual worker coming up with some ideas and then sharing them with the group, you use ChatGPT as your co-pilot or as your assistant to help you think of some other ideas. Maybe more wacky ones, maybe some that wouldn’t have necessarily come to you and encourage the serendipity, and then you come into your group and discuss the ones that may make the most sense. I think, maybe thinking about it more in terms of how it fits into our workflow can help us disentangle what it means to have these tools at our fingertips.

DAVID DE CREMER: Yeah, I agree.

ADI IGNATIUS:

With “Bot” as my co-pilot.

JACKIE LANE: Yeah, exactly. So I think there’s that. And then the second thing is, it’s clear that uptake of ChatGPT is not universal. And even in our small pilot study that we were running, we can see that there’s differences by where you live, your age. That’s an important aspect because if everybody that’s using ChatGPT is of a certain demographic group, then in order for this to really democratize the workplace and help us come up with ideas, there needs to be training, training on how to use ChatGPT and how to use it with prompt engineering to help people understand the capabilities and the potential, and also maybe the challenges and the drawbacks as well.

ADI IGNATIUS: I mean, look, I think most of us were introduced to this technology in November when suddenly it was available on a mass scale. And what you’re getting at Jackie, it seems, is that there will be new job descriptions that we don’t quite know what they are yet. I mean, it’s about the prompting and then it’s about the analyzing what comes out, but those aren’t small things. And if you were advising people who are entering the workforce and want to succeed in a world where generative AI is dominant and not get swept away by it, what should they study being ready for this new era?

JACKIE LANE: Yeah, I think a couple of things. The first one is, I mean, don’t be afraid of it. I’ve talked to people who’ve said, “Oh, I’m nervous about what it is,” but a little bit of encouragement, and then people start using it. And the best way is really to practice. And then the second thing is because the output is so dependent on what us as humans put in, and I go back to the prompts here, take a prompt engineering course. I mean, there’s free ones online. Andrew Ng has an amazing one on Coursera. And then also think about, say, templates that can help you. And I think just those kind of two things, and the iterative process of using GenAI can really help train and help people who are just entering the workforce.

ADI IGNATIUS: David, I want to come back to you. You talked about the tension between technology and the human in the creative process. Traditionally, certainly, we’ve thought of creativity almost without fail as something that is uniquely human. It is what we do that a machine can’t do, and now we’re in a somewhat different world. Do you think that generative AI will essentially make us all innovators? Obviously, with caveats, we have to figure out what we’ve got, but doesn’t it… There are those of us who say, “Ah, I’m pretty good at putting stuff into practice, I’m not a great innovator.” Aren’t we all great innovators now with this tool at our fingertips?

DAVID DE CREMER: Well, yes and no. But that depends on the economic model in my view. If we look at the output of AI as basically the output of a job, then yes, we’re all innovators because we’re all prompters now, and we let AI work for us. Yes, we’re all innovators. Basically, it’s cheaper, it’s more efficient, makes you efficient, so your job will be a prompter. If we live in that economy, yeah, everyone will be an innovator, but a restricted one. And I would call it, okay, then we lock up humanity in the data of the past because everything that’s new now is generated by AI, we just need to prompt it. We’re not innovators if we have an economic model where I do believe people will value authenticity still, so is it a human that created the end game, the end product, the end idea, the solution.

Right now, studies and our own studies show this as well. People still see authenticity in their mind as something human but not related to AI. So they don’t see AI as authentic in terms of moral ways, in terms of creative ways. It can generate, but the real authenticity still lies with the human being. So it will still be important from an economic point of view that customers, stakeholders see that the final product is one that is handpicked to say so almost by the individual, by the human being. So in that sense, of course, the collaborative model, machine, human, and how they work together, that’s the one to develop. And again, like I said earlier, we need to find those exact place that AI plays in it and the place that humans stake in it. It’s still up to us to make that choice.

And just one quick example to illustrate this is, yes, we can see AI as promoting efficiency across the board, there’s no discussion about that. They are a superior tool and they make us more efficient. But if we only adopt that point of view, you can also think in terms of work, are we then looking at human beings as an employee only as a task completer. Because then, yeah, great, generative AI is the way to go and the only way to go because it will allow us to complete our tasks more easily. But from the other point of view, you could also say, what does it mean to being a worker, an employee in an organization today with GenAI around? It may be that some of these tasks we truly enjoy as a human being. So do we really want to outsource this to machine? Do we really want to delegate it to machine? Because it may have impact on work satisfaction and in turn on the creativity of people in general.

So these are questions that are still unexplored. And I find this from a humanistic point of view, a very important one because it’s still about creating the right work culture, which is motivating, inspiring for humans. So again, that collaboration between machines and humans is really going to dictate how we’re going to build our jobs in the future and how we’re going to do our business, and what we can promise to society and our stakeholders in terms of innovation.

ADI IGNATIUS: One of the things that we write about in Harvard Business Review sometimes is how difficult it is for large established companies to innovate or that they need to rethink how they go about their business in order to be as innovative as say, startups. I’m curious. Jackie, let me ask you, I mean does generative AI change this equation where big dinosaurs that haven’t felt very innovative and maybe really aren’t very innovative suddenly can be because everyone can be?

JACKIE LANE: Potentially, but I think this is where leadership really matters. So there’s many reasons why I guess you call these old dinosaurs or the established firms fail to innovate. One of those is just organizational routines, the way you’re set up, the technologies that you’re built on. Legacy technologies, it’s really hard to change those kind of things. And so figuring out how you can incorporate generative AI into those workflows, into your routines, change the mindset of how people go about their tasks, that requires organizational change and cultural change, and also feeling like that the company is empowered to do that. And so I think we’ll see. We’ll see. I think this is where leadership really matters.

ADI IGNATIUS: Well, so let’s end on this. I’d like to ask both of you. Jackie, let’s start with you. I mean, what is it that senior leaders need to know about this technology and innovation, its capacity to assist in the process of innovation?

JACKIE LANE: It’s here! And it’s in its infancy. But my personal belief is it’s here to stay and it’s going to change the way that we come up with ideas within the workplace. And I would think of it as an opportunity and the potential. Just like how organizations started to use crowdsourcing in the last couple of decades, generative AI has similar feels to it. I think it’s something that leaders should embrace.

And then there’s a question that we need to figure out, which is: How the heck do we evaluate these ideas? There’s so many of them. The fact that even when we had crowdsourcing with just humans, there were so many ideas that we ended up not picking the ones that were the most novel. And this is a study that was done by Henning Piezunka and Linus Dahlander back in 2015. It’s beyond our human capacities. So, the question is: What do we do with that now? And what are the things that we can do within firms for leaders to start thinking about how we select those ideas that are not only novel but also useful and feasible that we can actually action on?

ADI IGNATIUS: So David, same question to you. What do senior leaders need to know about this technology and about its capacity to assist in the process of innovation?

DAVID DE CREMER: Well, first of all, I like what Jackie said earlier, “Don’t be afraid.” Just use it. Get to know it. Actually, we need our business experts much more involved today in any digital transformation because there’s so many ideas than, well, don’t create chaos either. We still need to know which ideas are worthwhile pursuing, and this is where business experts are extremely valuable. Why are you in business? What is the purpose of your business? What is it that you want to achieve? You need to keep asking these questions because that’s going to help the implementation and adoption of GenAI in creating better solutions for the questions that you want to address.

So purpose-driven leaders are more needed than ever to know what their business is about because it’s going to help the tech guys to make sure, okay, this is what we want to use GenAI for, these are the questions that we want to see addressed, and in the big range of ideas that we’re going to generate, that we know at least how to select what matters to us. There is great potential there, and I think it’s Winston Churchill who said, we’re not even at the beginning of the revolution, it hasn’t even started. we’re in the phase before the revolution starts. Well, I think when it comes down to generative AI for a business leader, just be clear on why are you in business, what are you trying to achieve, which questions do you want to ask? Keep asking questions. That’s going to be your big contribution.

ADI IGNATIUS: All right, David and Jackie, I want to thank you both for sharing your thoughts and being part of this show. Yeah, the revolution is happening, and it’ll be fascinating to see where it goes. But thank you very much for being here today.

DAVID DE CREMER: Thank you.

JACKIE LANE: Thank you so much for having us.

ADI IGNATIUS: That’s Jackie Lane, a professor at Harvard Business School, and David De Cremer, a professor at the National University of Singapore Business School and cofounder there of the Centre on AI Technology for Humankind. Before that, I talked to Don Allen Stevenson III, a video artist and consultant in Los Angeles. You can find his work on Instagram @donalleniii.

Next time, How Generative AI Changes Organizational Culture. HBR editor Amy Bernstein will host a conversation about adopting generative AI in your organization, with the emerging best practices for how to do that effectively and ethically. That’s next Thursday, right here in the HBR IdeaCast feed, after the regular Tuesday episode.

We talked about ethical considerations today. For more on ethics in the age of AI, check out HBR’s Big Idea on implementing the new technology responsibly. That’s at hbr.org/techethics.

This episode was produced by Curt Nickisch. We get technical help from Rob Eckhardt. Our audio product manager is Ian Fox, and Hannah Bates is our audio production assistant. Special thanks to Maureen Hoch.

Thank you for listening to How Generative AI Changes Everything, a special series of the HBR IdeaCast. I’m Adi Ignatius.