Discover how generative AI is reshaping creativity, collaboration, and decision-making in the workplace. From rethinking outdated brainstorming methods to overcoming human bias with data-driven tools, this conversation with Dr. Gleb Tsipursky, CEO of Disaster Avoidance Experts, explores how leaders can unlock more inclusive and innovative thinking without leaving human judgment behind. In this episode, you’ll learn: - Why traditional creative thinking falls short in modern organizations - The benefits of asynchronous brainstorming for idea generation - Ways to use AI as a strategic partner in innovation and collaboration
Discover how generative AI is reshaping creativity, collaboration, and decision-making in the workplace. From rethinking outdated brainstorming methods to overcoming human bias with data-driven tools, this conversation with Dr. Gleb Tsipursky, CEO of Disaster Avoidance Experts, explores how leaders can unlock more inclusive and innovative thinking without leaving human judgment behind.
In this episode, you’ll learn:
Resources from this week’s episode -
https://www.shrm.org/executive-network/insights/people-strategy/the-death-of-brainstorming-fall-2024
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Jerry: I am Jerry Won. Welcome to Tomorrowist, where we explore the trend shaping the future of work. This week we're re-imagining creativity, looking at why traditional brainstorming is losing its edge, how AI is transforming the creative process, and what forward thinking leaders are doing to unlock innovation in more inclusive.
Evidence-based ways here to help us unpack all this is Dr. Gleb Tsipursky, behavior scientist, author, and CEO of disaster avoidance experts. Gleb has spent his career helping organizations make better decisions and innovate with intention. [00:01:00] Dr. Gleb Tsipursky, welcome to Tomorrowist.
Gleb: Thank you so much for inviting me on, Jerry. It's a pleasure.
Jerry: You know, innovation and creativity are, are, you know, are core tenets of many organizations and some things that we focus on. And as we sit here in the middle of 2025, we're in the middle of, and in this, uh, evolving nature of AI and in how this disrupts everything that we do. And so really excited to chat with you for the next 30 minutes or so on sort of its impact and your thoughts on how.
Organizations can evolve, but also prepare for the future. Um, but you know, so let's set the table a little bit. You know, classic group ideation tends to reward the loudest voices in the room. He who she, who speaks so first always reiterates their point. And this sort of creativity ideation always, you know, rewards certain people.
And can overlook some better ideas. The unspoken ones, the soft spoken ones. Um, and as hybrid work has, you know, and generative eye has really impacted how we collaborate, how we work. Um, the old ways of both thinking about creativity [00:02:00] and I. You know, rewarding or prioritizing creativity has shifted. And so that's been your thesis, right?
Over the course of your work, you've argued that traditional creativity and brainstorming techniques are outdated and need to evolve. Um, what are the key flaws in how most organizations still approach creati creative thinking? Um, and then what needs to change?
Gleb: Well, you pointed out some of them is that when you're doing the traditional group brainstorming, what you're finding is that people who speak loudly are the ones who are paid attention to, and that's a real problem because people who are introverted. They don't get the opportunity to have their ideas heard.
So when you're a traditional brainstorming session. The people who are introverted tend to not function very well in that loud group environment where people are just shooting ideas. That's great for people who are extroverted and also, so that's one dynamic, introvert, people versus extroverted people. The other challenge is for people who are. Lower on the totem pole. [00:03:00] So people who are less powerful, who tend to be people who are newer, and if you think about people who are newer to the company, newer to the field, they tend to have the freshest, most different ideas,
Jerry: Hmm.
Gleb: ideas. The people who are in the experienced power positions, they tend to have a lot of authority and they tend to also be stuck in their old ways because they have a lot of authority. Those ways are the ones that have brought them to where they are right now. So that's a one big, big challenge, kind of that issue. Another issue is. People who are worried about judgment from others. So that first one, we have the issue of people being loud in the room. The other one is people who are worried about how they're evaluated by others.
It's called evaluation apprehension in the research, if you wanna look that up, it's gonna be my article in People and Strategy for the audience to check out term Purdue publication People and Strategy. And so. That dynamic has to do with people who are optimistic versus [00:04:00] pessimistic. So
Jerry: Hmm.
Gleb: people are the ones who are risk seeking, who like to look at the world that's full of opportunities, and they like to share a lot of ideas. People who are more pessimistic, they tend to be risk avoidant and they tend to think through ideas. They are not verbal processors, so they tend to think through ideas before sharing them. And so again. If they're in that room, they want to think through an idea. They're not, so they, it's not like the introversion versus extroversion, but they want to think through it. And so they often end up sharing many fewer ideas. So that's a big problem in that dynamic. We're not even talking about generative ai. We're talking about how humans interact, and that has been known for a while already. So research already in the eighties and nineties has shown the traditional brainstorming. Is leaving out really important people. So newer people, people who are introverted and people who are pessimistic and there are a number of techniques to include those people, but, and that they were used before generative ai. They were already used in [00:05:00] Harvard in the, did research on them in the 1990s, and people who knew about them. In the companies we're already using them extensively throughout the 30 years-ish before generative AI became a big buzzword. And we can talk about that so that those are the people who are left out and that's where companies are losing creativity from people who they can really get creativity from.
Jerry: I, I, you know, it, it's fascinating, right? 'cause I think we're. You know, as, as we mentioned, um, and maybe our audience is, is, you know, tuning in because AI is a hot topic, but we need to talk about these things and sort of the existing, as you mentioned, biases and sort of the, uh, the, the ways that we used to work, right?
Because the technologies will change, but organizations and, and our characteristics and quirks may not. Um, you, you mentioned some demographics of people who sometimes are not. Heard enough, you know, if you, uh, you know, our, our demographic change in the United States and even globally, so the working population is also becoming more diverse, changing, right?
And so [00:06:00] whether we're looking at it from a gender perspective or cultural perspective, you know, some cultures prioritize harmony and not speaking up others, reward speaking up and having your individual voices heard. Um. What is your perspective and, and work in terms of how that's changing as well. Um, the, the business world, let's call it, um, looks different today in 2025 than it did 20, 40 years ago.
Um, has that changed how creativity and voices are rewarded in meeting rooms?
Gleb: And that's a big point that, uh, you brought up in terms of identity. So when we think about people who tend to be. risk avoidant and pessimistic. We think of people who are belonging to the mainstream dominant groups. White, straight males. White. Straight males are the ones who tend to speak up the most in meetings, and they tend to be the most risk seeking, the most opportunity oriented and especially people who are weird, western educated, rich industrial democracies.
That's kind of the, the acronym for weird. [00:07:00] So if you're becoming not from a weird country. Then you might have more innovative, creative ideas to bring. But you're not as likely to voice them because your culture has taught you to be more risk avoidant in social situations, so you'll behave in a more pessimistic fashion, so risk avoidant fashion. Then of course, these people tend to be newer because all rich white males or straight white males. Tend to be in positions of power, so again, they'd be lower on the totem pole. You also have evidence that men are particularly likely to be risk seeking, so women's
Jerry: Hmm.
Gleb: aren't heard, so you're not hearing ideas from people who belong to minority categories that you really want to hear ideas from because they'll bring the most innovative, diverse ideas.
Jerry: So before we talk about how generative AI can help or mitigate some of these things, what are non-technological things that leaders can do in terms of, and, and [00:08:00] let's also look at this more from sort of a hybrid sense, right? So five years ago during the pandemic, we all went virtual. Did that help?
Perhaps, you know, the, the physical presence of people or raising your hand or, or physically speaking up, you know, how, what have we learned as, as a community, as a business community through our transition from, you know, uh, going generally in person to all virtual to a hybrid world, um, what are some organizational tips and, uh, guidances that we can provide leaders to make sure that all voices are heard?
Gleb: So this is another article that I wrote about in People and Strategy for SHRM on asynchronous brainstorming. So going back to what I mentioned in Harvard, they started researching how people can brainstorm in more effective ways that are more inclusive of those demographics. Identity categories, neurological categories in terms of risk avoidance, introversion, extroversion, even the power dynamics.
And so what they found and what I talked about is that what the key is to [00:09:00] have people do separate brain writing instead of brainstorming separately, individually, come up with their ideas. And then in a more collective way, collaborative ways evaluate the quality of ideas. So if you have people first coming up with ideas separately, then people individually come up with a lot of ideas rather than just be introverted people being not willing to interrupt when other loud people are speaking and
Jerry: Hmm.
Gleb: pessimistic, not being willing to interrupt with an idea that might be half formed, they can actually form their ideas and write them out. So. When we went to a fully remote setting, people spent a lot more time in asynchronous communication, that was a very natural fit for asynchronous brainstorming. So it's kind of a really good methodology to do asynchronous brainstorming. I'll describe the steps for people who want to do that. So what you do is that you give it, and this is again, before even getting to generative ai, you [00:10:00] have in each individual with. A prompt and I generate some ideas on this topic. Let's say you have 16 members who previously would've been six people brainstorming in the room, and then now you have them fill out, let's say a Microsoft. Form, or Google form or whatever it is that you put their ideas on. A whiteboard, a digital whiteboard, there are a number of digital whiteboards that you can use. So each individual puts their idea on the whiteboard or in the form, and then you get a combined whiteboard. Then you combine their ideas on the whiteboard. So whoever is managing the meeting. haven't the look at all their ideas, combine them, take out duplicates. Or in Google form, Microsoft Form, you create a spreadsheet with removing the duplicates.
Then you have people, again, anonymously evaluate the quality of HIG, so that you, people who are powerful are not going to get extra credit just because they're powerful. individually. So that's the second step. First, everyone generates their [00:11:00] ideas. Then you have them be in the Excel spreadsheet or, or a whiteboard. Individually and anonymously, each person evaluates the quality of each idea You can give. Have a rating for innovation, how innovative it is, how doable it is, of ideas. Let's say 50 ideas. And you have them if value in a category from one to 10 each. So let's say three categories. So each idea has, you have six people. Each of them idea has anywhere from three to 30 points. And so you have a hundred up to 180 ideas up to 180 points per idea. And so now the third step is you take all the ideas that are 150 points and above, and then you discuss those ideas.
And so you have a much smaller group of ideas left. And then you choose those ideas, and you'll find that often they come from people who previously would not have had their idea heard. And now if they're anonymous idea that's evaluated by everyone. In a fair way, then that's going to [00:12:00] be much more likely to bring ideas of people who previously weren't heard to the top of the table, and you have a much better outcome.
And we have extensive research showing that this methodology results in both more ideas and more novel ideas, rather than the traditional brainstorming approach.
Jerry: Well, that's fantastic. You know, I, I think, you know, at, at the core of it, we're, we're trying to remove or, or lessen the subjectivity of input and, and bring a little bit of objectivity. Right. And then, so,
Gleb: Mm-hmm.
Jerry: know, one, one tool that I use a lot and I know other, uh, folks use is particularly in town halls or when you're giving a presentation and when it comes to.
The q and a portion, you know, uh, particularly in the virtual setting, using anonymous question, asking tools rather than opening up all the microphones and saying, Hey, who's got a question? Because as, as you alluded, there's a lot of things in play, including fear of judgment. What are my coworkers gonna think?
What is my boss gonna think if I ask what I perceive to be a not so smart question? Um, but it also allows the moderator to look at the questions [00:13:00] beforehand and, and pick and choose. And I also think it has some other. Secondary order effects of maintaining the flow or staying on task, um, in terms of, and all these things.
And so, um, let's get to the elephant that everybody is, is curious about when it comes to creativity. Um, generative ai, right? A lot of folks are using tools like, uh, chat, pt or Claude to ideate. Uh, this notion of having a writer's block, uh, perhaps will be a thing of the past. You ask it some questions, at least you get something on paper.
Um. What is, so before we, uh, look at the practical applications of it, um, how has that challenged our assumptions and this notion of what it means to be creative or innovative?
Gleb: It's a fascinating issue where. Previously before the rise of generative ai, people thought that, well, creativity would be something that's limited to humans, and then generative AI
would take over lower level tasks. But what we found is that generative AI is actually great at creativity because it's a pattern matching tool, [00:14:00] and that's what creativity is. You're trying to match certain patterns and connect them to other patterns. Generative AI is great at that and very nicely, uh, a big benefit of generative AI used for creativity is that it doesn't. with the problem of hallucinations because hallucinations are what you're supposed to come up with when you're brainstorming ideas.
People hallucinate all the time, so it's not a problem if generative AI hallucinates, that's just part of the game. Sometimes the idea will not be functional and people hallucinate non-functional ideas all the time. The nice thing about generative AI is that it's not bound by. Human biases. So human biases unfortunately, often bind us and prevent us from coming up with good ideas.
One of the biggest challenges is called the status quo bias, where we tend to stick to ideas and concepts that we already know and are comfortable with. We're not comfortable challenging
ourselves and challenging our ways and methods of [00:15:00] being and doing. That's kind of one problem with human creativity and innovation. Another is functional fixedness. So it's, uh, where we tend to think in terms of, Hey, this is a thing and it has a certain function. So let's say we're trying to come up with new ideas for a feature for. A product or, or a service. We tend to think in functional terms like, okay, look, this is the function of this tool and therefore it should do this. Whereas that's not something that this, we can be much more creative and get a 10 X outcome instead of a one X outcome or two x outcome. If we're creative and more innovative and we. Forget the previous function of whatever it was, and we try to come up with it from first principles. are not good at functioning from first principles.
GER of AI is good at functioning from first principles, so it gets rid of that functional fixedness problem. And so we have a lot of research showing that it's really quite creative and innovative and [00:16:00] gets rid of a number of problems that people fall into when they do innovation.
Jerry: We think of creativity, we think of innovation and you know, if you are familiar with this TV series, mad Men, it, it sort of
Gleb: Mm-hmm.
Jerry: this notion of a really smart, creative, singular person who comes up with the ad, the copy or the slogan and, and that is rewarded and that's what the rest of the world sees.
We're, we're moving towards a more evidence and data-backed decision making, uh, as it relates to creativity. And, you know, uh, that is probably a better, a, a more sound business decision rather than banking it on one person saying, this is great. Um, how, how has that changed? And then how do we actually use it?
It, it seems to be the more practical and pragmatic approach to, to, uh, decrease also risk, um, and to make sure that, you know, businesses will have a greater chance for success at it. How, how does that actually look like in practice to put it into function?
Gleb: Well, that's a good point about data because another problem that people have when they're being creative is called attentional [00:17:00] bias, where we pay attention to what's most emotionally salient
Jerry: Hm.
Gleb: whereas. AI doesn't have that cognitive bias. It can pay attention to all the data. So in terms of practical approach. What you want to do is have an AI that's trained on your data. So let's say if you have a product, you want to innovate and could create a new idea about a product feature. Or if you are an HR professional, let's say you want to innovate about improving your employee experience.
Jerry: Hmm.
Gleb: how can you improve your employee experience?
So let's say you're doing that. What you want to do is you want to have data about your current employee experience. the surveys and everything that you've done on your employee experience, some guidelines, what you're currently thinking about, and you want to feed that into an AI tool. You can use Chad, GPT, cognize, Microsoft Copilot, you can use Claude, Google, Gemini, it doesn't matter, and drop Cloud for those [00:18:00] are the big four of whatever you want to use. Then again, going back to the example of let's say you have six team members in the HR. Who are working on employee experience, you give each of them individually the task of working with this chat bot that's been trained on your data, on employee experience individually come up with some ideas for innovating and improving your employee experience.
And so each of them, one big benefit about joint of AI is that. can come up with lots of ideas,
Jerry: Hmm.
Gleb: Many more than an individual can come up with very quickly. So each of them can come up with a whole bunch of ideas. Let's say a hundred ideas they'll come up with, and then individually, separately, without bothering everybody else, they should by themselves filter it down to the top 10 ideas for each individual. So that's the first step. The next step is you want to evaluate these [00:19:00] ideas from the perspective of the company. So the HR per person, like each of the six people on the team, the HR professional, would think about, okay, how would this new employee experience for each of the 10 ideas, how would it be accepted and what would be the impact on. Marketing on it, on operations and all of these sorts of internal groups. And they can have a, the AI that's trained in your company data, take on the persona
Jerry: Hmm.
Gleb: from each of these groups and think about what would be the employee experience impact on that. And so then you can filter down those initial ideas.
The like let, let's say the 10 ideas. Into the top five ideas and then from the next step would be you want to think about, okay, so you talked about the employee experience from individual perspective. How would the management feel about it in various areas of finance, whatever [00:20:00] leadership at, at various levels, and then you can filter those ideas down.
So have the AI take on the perspective of each of those. So not simply the individual staff and file, but the management and have it filtered down from five ideas to your top one idea. Then you have the AI build out a business plan for this employee experience improvement, the cost, the ROI, all of that, and you can have it create a pitch deck. And so then you'll have a business plan, a business case. And a pitch deck for your solution. once you have that, you have six people with a business plan, with a business case and a pitch deck. Then you have everyone email that to each other, and you can use your AI tool to evaluate the other people's pitch decks and business plans. And then you have a final meeting where you discuss. six ideas and you choose one. the AI was a key [00:21:00] co-pilot in this experience, co-partner in the experience of creating these. So you earn much better SPL pace than if you just got together in a room and started brainstorming ideas.
Jerry: And what you shared just now, Glenn, is, is also a, a, you know, a, a warning or at least an encouragement to not actually let go of the entire creative process, right? You need to have the, the organizational knowledge, the institutional. Lens through which, especially if you're making decisions on behalf of an entity or organization, to make sure that it, you know, is, is in line with the priorities, the goals, and the culture of the organization.
So I, I know that, you know, there's a lot of, um, talk about AI replacing all of us one day and it's just gonna think by itself and talk to other robots and create all these things, but. You know, what you're advocating for is definite human involvement, not only to make sure that there's checks and balances there, um, but it is in partnership with, and that you still need folks, uh, who are deeply [00:22:00] knowledgeable about not only the culture, but how to navigate, um, AI in that path and so on.
On the same note, um, you know, on the human involvement, what, what role does cognitive bias still play in the creative decision making process? Um, and, and what? Practical steps can leaders take to mitigate it as we go sort of into this new frontier of creativity and decision making.
Gleb: So I talked about a number of those cognitive biases already. The status quo bias, the attentional bias, functional fixedness. Those I think are the ones that you want to really watch out for Now, another. Problem that I think you want to watch out for in relation specifically to ai, there's two problems that you want to watch out for. One is automation bias. That's a tendency to automate things that you should not be automating that are where humans are still quite valuable and where you don't want to leave it up to the machine. So, for example, what I was just talking about, the innovation. [00:23:00] is definitely better than humans at generating a lot of ideas, a lot of ideas, a lot of good ideas. It's created creativity. So the creativity, that's something that you should lead to the AI and that will become definitely less important in the future. And that's something I was just talking about to one of my clients who I was working with and adopting generative ai. this was a professional services firm and we were just like figuring this out and I was talking to them about it. So the creativity, the gen idea generation, that's great for AI to do, but AI is not great at editing,
Jerry: Hmm.
Gleb: So figuring out which of these is actually the best thing to go forward and how to interact with other human beings in order to implement the thing. the human touch, the human. Talent that will become more important in the future. is idea curation, idea editing, idea implementation. AI will be [00:24:00] responsible for the initial generation of ideas, and humans will be more responsible for the idea curation and editing and implementation. So that's one of the other cognitive biases that you want to one. The other biases, you want to be aware of the automation bias. Another problem is called automation anxiety, where people are too afraid of using this new technology. So I was working with another client. Uh, this is a insurance company, and what they are about is replacing their intake form. Currently of insurance documentation with a chatbot. They currently have a form.
They're worried about what will happen if you replace it with a chatbot that people won't accept it. They'll be about using it, and I am telling them that people are using chatbots a lot. They're very comfortable with it, and this is the future. It's going to save you so much time and effort and hassle. You really wanna do this, and so [00:25:00] the automation anxiety is another sort of issue that you'll want to address if you want to integrate generative AI effectively.
Jerry: there's two, uh, sort of. Concerns or anxiety points maybe that leaders might be thinking about, which is one, um, the, the reliance on ai, how much do we use it? Um, and, and also are there, and as new tools are developed almost daily, um, sort of keeping up with. You know, what tools do we use and adopt? Um, and, and I guess what I'm really getting at is, you know, how do you balance sort of the, the exhaust of creativity or the efficiency of creativity as it relates to good enough?
And let's move on. Because if you ask any AI chatbot, gimme another idea. It's never gonna stop, you know, because it's trained to do that. But as businesses in, in timely fashion, sometimes you have to be. Uh, not even content, but happy with what you're doing and, and move on. So how do [00:26:00] we balance that?
Because it, it seems to be, uh, something that can be never ending.
Gleb: Yeah. So the best way to approach balancing that is not to let other people build your AI tools. That's the key thing. That's a way that I see companies often going wrong. They hire a. technology firm that builds them a tool, and then they're like, well, this tool is. Stuck where it currently is, a problem. A much more effective approach to this, and this is something I do with my clients all the time, is teaching them how to use these tools and then having them develop and improve these tools. As the tools improve. Now some things are going
Jerry: Mm-hmm.
Gleb: for them to build. But some of the things that companies are offering are really quite simple to build. So let's say with this insurance company, to use it as an example, they were offered a claims writing tool. You know, I worked with them and with AI capability, I worked with them with [00:27:00] simple Microsoft tooling approaches, and they were able to get a result that was. High quality and that they were able to change themselves and then
Jerry: Hmm.
Gleb: over time and not rely on me to do it. And so once you know internally how to use the AI tool, going back to the nature of the question, you know when to stop. You know when to stop optimizing. You don't need to rely on anyone else. You can figure out, okay. We got 95% of the way there. Is that good enough? Or maybe sometimes 90% of the way there is good enough.
Maybe 80% of the way there is good enough. then you can make your own decision.
Jerry: Right.
Gleb: how the AI tool functions and how much benefit you'll get from optimizing it, and then you'll have much more control over your own fate and future. And this is something that I think HR professionals in the audience really need to think about how to have control over your own fate and future. As you adopt generative AI tools by learning how to use them yourself, getting that knowledge and then relying on that [00:28:00] knowledge to deal with any external vendors who you might engage with to build something much more complex. I.
Jerry: That is a perfect segue as, as we wrap this, uh, really insightful conversation, Gleb, and then, um, you know, give something of, of value and maybe a homework assignment to our audience here. Um, what is the one thing that leaders can do today? And I know you just touched on one, um, but what is the most important thing that, uh, leaders can think about doing or putting under calendar today to really understand that how they can modernize this approach to innovation and reimagine creativity?
Um, you know, what, what is the one thing that they can do today to start getting better at it for tomorrow?
Gleb: Oh, I'd recommend going and reading my article and People and Strategy on the death of brainstorming. That's going to be
Jerry: I.
Gleb: you good guidance. But besides that, besides the article, what I think you really want to do is play around with generative AI and see how it can brainstorm ideas for you in any area that you're concerned about, whether it's employee experience or onboarding or with [00:29:00] the offboarding or any area recruiting.
Anything that you want. To work on. That is an area that you want to experiment with yourself and that you want to support the training of your people in this area. So encourage them to get training. Whatever tools you use. If you're using Microsoft Tools, you can work with copilot. If you're using Google Tools, you can work with Gemini. Anything that you use, I mean chat, GPT, Claude, all of these other tools are great. So you want to work with them and experiment with them and be confident that the future of creativity is not in generating ideas, but in editing and curating ideas. And that's the skill that you really want to focus on building.
Jerry: Wonderful. Uh, I learned a lot. I know our audience has both the, the, the theories behind why we do what we do, how we will evolve, and indefinitely practical tips for us to be really great at this tomorrow. Uh, Dr. Gleb Tsipursky, uh, thank you so much for joining us on Tomorrowist, and we will see you tomorrow.
Gleb: Thank you so much for inviting me, Jerry.
[00:30:00]