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AI and Creativity: How Generative AI Helps Create Ideas but Yields Similar Outputs

August 22, 2025 / 08:28

This episode discusses the use of AI, particularly ChatGPT, in brainstorming and enhancing creativity. Guest Gideon Nave, an Associate Professor of Marketing at the Wharton School, shares insights from his research on AI's impact on creative tasks.

Nave explains that while AI can assist in generating novel ideas, it may also lead to a homogenization of creativity among users. He cites a study published in Nature Human Behavior that found GPT increased individual creativity but resulted in similar ideas across groups.

The conversation touches on the implications for companies relying on AI for creative processes, emphasizing the need for caution as AI becomes more widely used. Nave highlights the importance of individual creativity and the potential risks of over-reliance on AI-generated solutions.

Overall, the episode provides a critical look at the balance between leveraging AI for creativity and maintaining unique, diverse ideas in a competitive landscape.

TL;DR

Gideon Nave discusses AI's role in enhancing creativity and the risks of homogenization in ideas.

Episode

8:28
00:00:00
Dan Loney: We obviously have seen a rise in the use of things
00:00:03
like ChatGPT in the last couple of years, but one of the
00:00:08
questions now being asked is, can you use AI to help with the
00:00:12
brainstorming of ideas? Gideon Nave was part of a research
00:00:17
project done on the topic. He is an Associate Professor of
00:00:21
Marketing here at the Wharton School. Gideon, great to talk to
00:00:24
you again. How are you, sir?
00:00:25
I'm well, Dan. It's really hot outside, but we are in a nice
00:00:29
fresh air-con here at Wharton. So.
00:00:31
Absolutely, absolutely air conditioning is nice at this
00:00:35
time of the year. Hey, let's start, I guess, with the genesis
00:00:39
of the idea. And is part of this kind of the transformation
00:00:44
we're all going through in understanding just how much we
00:00:48
can use things like ChatGPT, and in what areas, and maybe
00:00:52
what areas we can't use them?
00:00:54
Well, you know, the work we've been doing recently was about
00:01:00
creative tasks. Our creative task, I would say the goal of
00:01:04
them is to come up with something that is novel, unlike
00:01:07
more routine tasks of, you know, just maybe translation,
00:01:12
right? Translation, you have a sentence, you will translate. It
00:01:15
doesn't have to be surprising in any way. It doesn't have to be novel.
00:01:20
You know, finding new ways to do translation is a
00:01:24
creative task. And when we talk about creativity, we talk about
00:01:27
things that are novel and useful. That's— you know, people
00:01:32
don't seem to agree on the definition, but when people see
00:01:34
something that is creative, they do seem to agree that it is
00:01:37
creative. I've been teaching creativity at Wharton for a
00:01:41
while. Even during the time when ChatGPT came out, I was in the
00:01:45
middle of class, and I even got to do like a live demo of it at
00:01:49
the time. And actually what I remember in this class, I
00:01:52
actually demonstrated to people, to my students, how you can use
00:01:57
GPT to just write an email to your professor. And I wrote an
00:02:01
email where you write an excuse to the professor, like, why did
00:02:04
you— why did you not submit your homework in time. And one of
00:02:08
the students said, "Hey, ask it to write a creative excuse." And
00:02:13
GPT did it well. It came out with the idea that, you know, my
00:02:17
project turned out into something that seemed like a
00:02:19
product, and I was working very hard to do it, to get it
00:02:25
into market, and I missed the deadline, right? That's very,
00:02:28
very creative. And that's the old GPT, the first one that
00:02:30
came out. So— and we know that these models have a tendency to
00:02:35
hallucinate. Meaning, to come up with new stuff when— and pretend
00:02:38
that they know it. So for this, for creative tasks, it's
00:02:41
actually pretty useful and cool. And these models are trained on
00:02:45
a lot of human thoughts, expressions, emotions and
00:02:50
whatnot. So we definitely see a great potential here. And some
00:02:55
companies have been doing it too. Coca Cola, for example, used
00:02:59
the AI to come up with, you know, a new flavor that is like
00:03:03
the year 3000 and so on. The thing is that as scientists, we—
00:03:06
what we want to do is go beyond these anecdotes and try to
00:03:09
systematically understand what's going to happen if all of us are
00:03:12
going to start using AI for our creative processes.
00:03:15
And realistically, when you're talking about the link between
00:03:17
creativity and what companies look for, in many cases, that's
00:03:22
a core element of their operation. They have to be
00:03:25
creative in order to be able to take that next step in their
00:03:28
success level. - When
00:03:30
you're in a competitive market, obviously, like, creativity
00:03:33
is key. You want to do something that your opponent
00:03:36
cannot do, and you want to— you want to beat your opponent,
00:03:40
whether it is as a company that tries to compete with others,
00:03:43
whether it is an employer that competes for promotion, and so
00:03:47
on. And in this sense, creativity is an ever-moving
00:03:50
goalpost, right? If I tell you a joke now that you've already
00:03:53
heard, that's not going to be funny. If I tell you a joke that
00:03:56
has the same principle that you may have already heard about,
00:03:59
maybe, maybe it has a chance. And in this sense, you know,
00:04:03
maybe getting the principles of a joke like, sometimes you kind
00:04:06
of build something, and then you break a pattern, that will be—
00:04:08
maybe a joke like this could work.
00:04:12
So you mentioned Coca Cola, Gideon, about how they use it.
00:04:16
How much expectation should we have that companies are already
00:04:19
using AI to enhance the creativity that they have?
00:04:23
You know, many companies are using it already. And what
00:04:26
we as scientists try to do is to try to go beyond these anecdotes
00:04:30
and get into real science and see, what is going to happen if
00:04:34
everybody is going to use the same model, such as ChatGPT? It's
00:04:37
very possible that the new AI is going to give you an edge. But a
00:04:41
non-specific AI is kind of the very start. And that's where we
00:04:45
come to the study that we recently published. So a study
00:04:49
published in <i>Nature Human Behavior</i> about four or five
00:04:52
months ago did an experiment where they gave people various
00:04:57
creative tasks, such as coming up with a novel use for a
00:05:01
garden hose and a rocket, or coming up with— with ideas to
00:05:07
buy for an 80-year-old birthday. And they did— they randomized
00:05:12
people into groups that either could use Google searches or
00:05:15
ChatGPT, and they just compare the creativity of the people who used
00:05:20
the former versus the latter. And they found that the GPT
00:05:24
increased the creativity, overall, of every person. What we did,
00:05:29
though, is, once we reanalyzed their data, we found that GPT
00:05:33
indeed increased the creativity of every individual, but it made
00:05:36
also everyone more similar to one another. And if this is the
00:05:40
case, we actually end up with less new ideas as a group. Okay?
00:05:45
So it's kind of like a prisoner's dilemma, where it's
00:05:47
the benefit of everyone to use the GPT. They, on average, become
00:05:51
more creative. But then, as a global company, as a society,
00:05:57
we're going to become more similar to one another, and then
00:05:59
we're going to actually smother creativity.
00:06:02
And do you potentially end up losing, you know, the individual
00:06:08
creativity? Because how one person is creative compared to
00:06:11
another is most likely different. And you're coming now
00:06:15
with a more kind of steady path, straightforward path, of the
00:06:19
same types of creativity if you're relying on ChatGPT.
00:06:22
Exactly. On the long run, I think that once all of the ideas
00:06:25
are available to everyone, I'm pretty sure that, like— we call
00:06:30
it the sprinkler effect. Like, the one use that GPT came up as—
00:06:35
for garden hose and rocket ball, is to make sprinklers from it.
00:06:39
It's an idea that is great. It's useful, it's novel, and it's
00:06:42
rated highly. But if I'm a manager, I'm going to get 50
00:06:46
different proposals of what to do with that. And 20 of them are
00:06:50
sprinklers. I'm probably not going to judge the people that
00:06:53
came up with the sprinkler as more creative, even though, you know,
00:06:56
if I get one sprinkler it seems like a great creative
00:07:00
idea. So I think we need to be careful here.
00:07:02
So this is very much like a lot of things around AI right now.
00:07:06
We're kind of testing where it's taking us, but we still have to
00:07:09
be wary as to where it's going to take us down the road.
00:07:11
I think that one—
00:07:13
you know, initial promise of studying AI was to look at the
00:07:16
individual and how it makes the individual more X, Y or Z.
00:07:20
When it comes to— when it comes to productivity in maybe routine
00:07:24
tasks, it makes sense. When it comes to creativity— but
00:07:27
creativity is always measured against the prior art, against
00:07:30
what everyone else is doing. Using GPT in a conventional way
00:07:35
is going to make you look conventional, because everybody
00:07:37
is going to use it the same. Even though, you know, if you're
00:07:41
the only one using it, it will make you look like a superstar
00:07:44
creative person. But we're talking here about technologies
00:07:47
that is available to everyone. So there are risks here. And one
00:07:51
of the emphasis in my class— my creativity class, I fully
00:07:54
endorse AI. So I wouldn't say that, you know, don't use AI.
00:07:58
But there are ways to use it, and there are smarter ways to
00:08:01
use it than just asking it, "Hey, come up with a creative solution
00:08:05
to me, for my problem."
00:08:06
Gideon, great to talk to you again. Thanks very much.
00:08:08
Always, Dan. Thank you.
00:08:10
Thank you. Gideon Nave, Associate Professor
00:08:12
of Marketing here at the Wharton School.

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This episode stands out for the following:

  • 60
    Best concept / idea

Episode Highlights

  • The Role of AI in Creativity
    Gideon Nave discusses how AI tools like ChatGPT can enhance creativity but may also homogenize ideas.
    “AI can help with creative tasks, but it may make us more similar.”
    @ 05m 36s
    August 22, 2025
  • The Sprinkler Effect
    Nave explains the 'sprinkler effect' where AI-generated ideas may lead to repetitive creativity.
    “If I get one sprinkler it seems like a great creative idea.”
    @ 06m 30s
    August 22, 2025

Episode Quotes

  • Creativity is an ever-moving goalpost.
    AI and Creativity: How Generative AI Helps Create Ideas but Yields Similar Outputs
  • AI can help with creative tasks, but it may make us more similar.
    AI and Creativity: How Generative AI Helps Create Ideas but Yields Similar Outputs
  • We need to be careful here.
    AI and Creativity: How Generative AI Helps Create Ideas but Yields Similar Outputs

Key Moments

  • The Sprinkler Effect06:30
  • Caution with AI07:00

Words per Minute Over Time

Vibes Breakdown

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