"If you have a brain, you have bias." That phrase is more than a tagline for the NeuroLeadership Institute's model for overcoming bias at scale. It's also a far-reaching truth with profound implications about who we are and how we navigate the world. In this episode of Your Brain at Work Live, Dr. David Rock (Co-Founder and CEO, NLI) joins Evynn McFalls (VP Marketing, NLI) to reveal the origins of the SEEDS bias mitigation model and how we put that science to work—transforming thousands of leaders and teams over the past decade. You've never heard the story quite like this. Catch the insights and get a sneak peek at what's next in conquering unconscious bias.
[INTRODUCTION]
[00:00:03] SW: Hello to all of our viewers across the world. Welcome back to another week of Your Brain at Work Live. I'm your host, Shelby Wilburn. In this week's episode, we are going to have a conversation to reveal the origins of the SEEDS bias mitigation model, and how we put that science to work over the last seven years.
For our regulars, great to have you back. For those of you that are new to Your Brain at Work Live, welcome to the party. For some context. It's a title of one of the bestselling books by our CEO and Co-Founder, Dr. David Rock, and it's also the name of our blog and podcast. Before we get started, I'm going to introduce our speakers for today. So, an Aussie turned New Yorker who coined the term neuroleadership when he co-founded NLI over two decades ago. With a professional doctorate and four successful books under his name, and a multitude of bylines ranging from Harvard Business Review, to the New York Times, and many more, a warm welcome to our Co-Founder and CEO of the NeuroLeadership Institute, Dr. David Rock.
[INTERVIEW]
[00:01:03] SW: Great to have you back, David.
[00:01:05] DR: Great to be here, Shelby. Thanks very much for the warm welcome.
[00:01:08] SW: And our moderator for today, who is also a first-time guest, is a passionate explorer of intersecting lines of narrative, communication and culture. He steers strategic communications and public and private research partnerships for some of the most impactful companies in the world. And this was the basis of his academic research. Today, he puts his brand-new work at the NeuroLeadership Institute where he leads our marketing and communications efforts to grow and strengthen the NLI community around the world. You might even recognize him from the LinkedIn comments section on our weekly show. Please join me in welcoming NLI’s Vice President of Marketing, Evynn McFalls. Evynn, great to have you here today.
[00:01:46] EM: Thanks so much, Shelby. It's a pleasure to be here. I'm like, super, super excited to be here. It's really a wonderful opportunity. Before I came to NLI, I was very interested in how cultures are formed at institutions and really thinking about this question of bias from a kind of social constructionist way. And when I thought about it in that way, I was like, “This doesn't feel quite so tangible to me.” And so being at the NeuroLeadership Institute really gave me the opportunity to see what's really happening in people's brains.
And so, super excited to learn a little bit more with you today, David, about what informs bias and how cultures are formed. And so I think I'm just going to jump right into today's questions and ask you, what kicked this all off for you? What was the spark for getting into the realm of unconscious bias?
[00:02:35] DR: Yeah, thanks, Evan. Great to be here with you. Excited to dig in. It was actually a while ago, now, we kicked off our bias practice in 2015. But it was actually about 2012, that we ran a series of events for heads of diversity. I remember, we ran a pretty big one in New York, another big one in – I think it was San Francisco. And we did some in other parts of the world. And I was really interested in trying to understand where the breakthroughs were in this space, because DEI, diversity, equity and inclusion, is an area people are really passionate about. And everywhere I went, people would say, “We're just not making progress. We're just not making progress.” We go to a conference now, it looks like the same conference 10 years ago.
And I was curious, like, where is the big breakthrough, potentially, in this space? And we literally just asked over 100 heads of diversity, “What's the one biggest challenge across DEI that has to be addressed, and you've been trying to address but you’re not being getting any momentum?” And there are all these different issues, ERGs, and gender issues, and all sorts of stuff. But actually, doing something about bias was an enormous outlier. Like everything else was sort of here. And then bias was like way up here. Pretty much everyone said this is a big problem.
And what was interesting is I realized, at the time, in 2012, I realized it was a problem that was probably going to get worse because the kind of the busier you are, the more likely you are to be biased. And I could see everyone getting busier and busier. And just reading the zeitgeist, I could see this was a problem that needed to get addressed and probably wasn't going to go away. But the interesting thing was it's a problem that everyone had, and a lot of people were actually investing a lot and getting no returns at all. And that was the big kind of aha for us. Like, “Oh, interesting.” And when we find those conditions, like something that matters and something people are really trying to do something about, investing time, money and resources, but getting no movement. Our hypothesis is that we might be doing it all wrong in simple terms. And that kind of kicked off the journey, and we said, “We're going to really study this.” And in our incredible naivety, we said, “We're going to tackle this for the next six to 12 months and see if we can come up with the big insight.” And three and a half years later, we found something. Back to you.
[00:04:53] EM: Yeah, thank you for providing that context. Something that I want to circle back on a little bit there is you touched on how organizations really were not seeing progress as they were investing in unconscious bias and their DEI initiatives. When I hear that, I have to ask, what was in place before that was leading to that lack of progress would you say?
[00:05:15] DR: Well, there is a lot of work out there that companies are doing on like raising awareness of bias. And today, there’s probably a million people in a classroom today somewhere around the world learning about bias with the hope that if they're more aware of it, there'll be less bias. So that's what we saw a lot of, is a lot of good work, a lot of great work by Mahzarin Banaji and many others who are educating people that bias is real, and bias is an issue.
The trouble was, as soon as we started the research journey, like as soon as we started the literature review, we found this really scary thing, which was that being aware of bias doesn't do much at all about it. And the reason is that it's called unconscious bias and is conscious bias. But a big part of the problem is, is that it's unconscious bias. And it's not something you can be very conscious about.
And we can dig more into that. But essentially, the sort of the whole theory that was out there was incorrect, which is if you've you raise awareness of it, people will change. And what we found in our research was there are three or four reasons why that doesn't actually work.
[00:06:21] EM: Yeah, great. Thank you. I know that there are some people who have joined us that are a little bit new. Could you tell us a little bit more about those reasons why things didn't work?
[00:06:30] DR: Let me tell you about the research journey, because I think that will bring it alive. Like the first thing that we did when we start any research journey is we do a sort of general literature review. Like what do people say about what models are out there? Who are the big thinkers in this space? We put together a research digest. And we didn't get very far into it before we saw something startling, which was, basically, everyone from Wikipedia, the low-end, to the Nobel Prize winner at the top-end, and pretty much everyone in between said, “You actually can't do anything about bias.”
And it turns out like raising awareness of it does very little. And motivation doesn't do much at all. And ironically, intelligence probably makes it worse. So the smarter you are, probably the more bias you have. I’m not saying people with lower intelligence have less. But it's not like, “Oh, if we hire really smart people, they won't be biased.” It doesn't fix it.
And so that was kind of scary. And we sort of spun around for a long time trying to think about, like, “Okay, so what do we do? If people can't like be less biased, what do we do?” And there was actually a quote from Kahneman’s book, his earlier book, Thinking Fast and Slow, which is kind of a lot about bias, but not directly about it, but it kind of is. And there's a quote, and he talks about how if someone kind of dug into how the brain processes bias, we might find some solutions. And that was like one of about five different research directions that we took.
And so we went down this one research path with a team. We had some external scientists and a big internal team. And we started to meet every few weeks to essentially say, “How does bias work in the brain?” And what we did was we noticed that there was something kind of wrong with bias. Because I don't know if you know this, Evynn. But the literature, when we looked at the literature and said, “Hey, how many biases are there?” There was no answer, right? The answer is 100, plus or minus 50, depending who's asking and what day it is and what – Like there was no framework for even how many there were. And the number was ridiculous.
But what's really interesting is that when you sort of put them on a wall, which we did many times, when you literally put them on a wall and started to kind of group them, you saw some natural patterns. Like there were biases that were clearly about how you feel about a person, which were really different to biases about how you might feel about a loss of some sort. We just got loss aversion, which was different also. So we started to see that there were some groupings. So there wasn't probably really 100 biases. There was a smaller set.
And the interesting thing was, at one point, we realized we had this big aha, which was that all this sort of work we could do to organize bias and synthesize bias is, in a way, none of it would really work. And everyone, from Wikipedia to Kahneman, was right. We actually couldn't do anything about bias.
But the big insight that we had was that while you can't notice bias in yourself, you can notice bias in other people. And the reason that you don't notice bias in yourself is basically just a cognitive constraint. So if you're trying to decide between two people to hire, holding the information about both people in your brain uses up all available resources. It's like trying to do two different math tasks at the same moment. You just can't, right?
So what we realized is people can't detect bias in real-time while they're making decisions because we just don't have the cognitive – We’re just not built for it. We can't see infrared either. Lots of things we can't do. But you can see it in other people. And so what we’ve realized was if we were – We sort of put these two things together and said, “Hey, if we were able to simplify all the biases enough into something memorable that people could use, maybe people would be able to see biases and have common language for biases that were happening in a conversation or in a process as a team, as opposed to yourself, right?
So, Evynn, you and I are in teams all the time, and in conversations all the time, and probably just about everyone, someone will say, “Hey, let's be careful. That's not a safety bias here.” As opposed to, “You have a bias personally. You're broken, and bad, and wrong.” So those are a couple of the insights that there was a pattern, and that if we could simplify it enough that people could remember it, we would be able to have teams identify bias, as opposed to individuals trying to just be less biased. So we can sort of catch it and put in place processes.
[00:11:02] EM: That's fascinating. And so I understand that, ultimately, over that three and a half years of research that culminated in the SEEDS model. And something that I'm hearing you say is that this social learning component was critical to the success of doing something about bias. So I kind of want to move the conversation forward and talking about how you translated the research of SEEDS into the programming or the programs that you do for organization.
[00:11:32] DR: Before we get there, let me just take a step back, because I think there's an interesting story that hasn't been told very often. And there's some interesting questions coming in as well. But there’s an interesting story. So in the three-and-a-half year journey, the reason it took so long, is about two-and-a-half years in, we finally organized a framework. We've kind of done this. We'd simplified a framework. And at the time it was called the COST model, C-O-S-T. And we republished it. It was a lot of work. We were really proud of it. At the time, it was our biggest research project ever. It was two-and-a-half years. And the interesting thing was we started giving talks on the COST model. We started getting research briefings to senior team, to executive teams. We started speaking about it in conferences, all this stuff. And then just got to listening as we always do, like, “Oh, how many times did you use that this week? Did you find yourself applying the COST model with your team? How many times?” We're really interested in habits. So if we teach something, it should show up in the practices that people have week to week.
And what we found was the practically no one was using COST. And we got quite concerned. And we actually put together a team, ironically, a more diverse team, to kind of look at the model. Kind of take it apart and look at it from different angles. And we brought a couple of other experts in. And what we found was that the COST just wasn't right. And it was terrifying, because we already had a client that was like thinking seriously about rolling this out. It was BlackRock at the time. And they've been public about the work with us, if I'm allowed to mention it.
But what was interesting was we actually retracted it. And we said, “We don't want this out in the world. People don't use it. And we don't want to put a model out there in the world that people actually don't use. So we're going back to the drawing board. It took us about six to 12 months, and we came up with the SEEDS model.
And there's a bunch of reasons COST didn't work. It was a little too cerebral. It didn't quite organize it just right. It wasn't memorable enough. It was too complicated. There are a number of factors. And it turns out to be really, really hard to simplify bias. And we eventually got there about three to three-and-a half years later. So those a really interesting journey. And then that's maybe a backdrop to kind of your question. The first time we then started working with this was with BlackRock. And they kind of seen the COST model. And I sort of came to them with my tail between my legs and said, “Hey, guys, I'm sorry. But, actually, we don't think that works. You know we're a research company at heart. Well, we take that seriously. And we've studied it, and it doesn't really work.” And we just thought they would cancel everything and to give them money back. And it was going to be very embarrassing. But we just didn't want to put something out that didn't work, right?
And actually, sort of in the moment, like the team there, it Matt Breitfelder at the time, who's now the CHRO at Apollo, said, “Well, show us what the new solution is. We’re curious to see it.” And I literally on the back was actually – This is a bit of a cliché. But it was actually on the back of an envelope that I spelled out the SEEDS model, with similarity, expedience, experience, distance and safety. And he looked at it and he went, “That's so much better. We need to roll that out. Let's get everyone together and like completely refocus.” And we ended up teaching, I don't remember the number, thousands of people managers at BlackRock in 2015, 2016. The SEEDS model, they’re the first people that kicked it off. There're some lovely videos of them talking about that journey from early on in some of our summits. So anyway, that was sort of some of the backdrop.
[00:14:49] EM: Well, thank you. Thank you so much. Do you think that bias was more focused on the past as discrimination and that discrimination was associated with reprimands or even legal concerns? What is your perspective?
[00:15:03] DR: I mean, there's a lot of different ways that we've approached bias, aside from just framing it into SEEDS. There's a lot of different kinds of philosophies that we've brought to this. And we've always come from, “How do we get people to use this every week?” Our mission is to get people to build habits. We're in the habit activation business. So for us, mitigating bias means to be doing it many times a week.
And so one of the things that we saw is that bias was seen as this negative thing. It was weaponized in a way. It's very accusatory, “You've got bias.” And it was linked, obviously, to race but also to gender, to different all sorts of things. And to this day, we still get asked sometimes by folks like, “Hey, why aren't you doing specifically work on, say, gender. Why aren't you calling out this community? Or why aren't you calling out this community?”
What we found is we wanted to de-stigmatize bias. And we had a bit of a tagline we've had for years now, which is, “If you have a brand, you have bias.” And we wanted to de-stigmatize it and have everyone realize that it was just a part of who we are, which it is. Bias is another way of saying approximation, generalization assumptions, doing things unconsciously, doing things automatically. We actually need those mechanisms. We could not make it to breakfast without those mechanisms.
So what we wanted to do was de-stigmatize the concept of bias and say, “Hey, look, you can't address bias constantly. Your brain would explode.” But probably, as a CEO or C-suite of a company, you probably going to run into issues that you should bring up a bias two or three times a day, and maybe a mid-level manager, probably two to three times a week. You're going to see things. And it's natural and normal. But it's just built into how the brain is. And so we tried to de-stigmatize it and say, “Look, it's just a natural part of who we are.” And you can't even address it all the time. You're going to have to just address it in these situations.
And the other thing that we did was a little unusual, is we said, “Let's stop talking about bias in relation to just diversity, equity and inclusion.” Now this was kind of sacrilegious in some ways at the time, and a lot of people were going mad. But we said, “Look, let's link it to decisions, of which there are people decisions. And then there are also business decisions.” And why wouldn't we want people to be catching biases, whatever kind of decision they're making, right? And then they're much more likely to catch it in a people decision, right? You're much more likely to notice a bias when you're hiring, if you're also noticing it when you're investing, or deciding on a vendor, or something else. So if you're in the habit of addressing bias across the board, you're more likely to use it with those things that matter.
So we took the focus away a little bit from just DEI and said, “This is about decisions. And that's why we call the solution – The solutions we turned SEEDS into what's called Decide, because it was about decisions specifically.
[00:17:57] EM: Thank you. I'm really glad that you touched on Decide, because that was kind of where I wanted to go next, is that over the course of three and a half years, you arrive at the SEEDS model. You begin thinking, “Okay, this is a meaningfully different approach to bias mitigation.” What’s next? How do you take that out into the world?
[00:18:18] DR: These were some of the most complicated, and feisty, and just rich conversations we'd ever had as a research team. And it's really, really difficult to work out the exact right way to address this. But we knew, as a guiding principle, we were about mitigation, not awareness. We were about people taking steps to mitigate this, right? And so we wanted to build a solution. And we just, at this time, when we launched SEEDS in 2015, we’ve just seen these incredible results from our Connect solution in a very digital form. Connect was with the first time we've done a digital solution, or what we call now a distributed learning solution. Essentially taking something apart, teaching in over a month in small bites.
And so we said, “Well, could we do that with SEEDS? Could we teach this in like three, five-minute videos in a one-hour webinar at massive scale?” And honestly, at the time, there was a bunch of people, including me, who were like weren't sure. Like, it's complicated. We probably came up with 10 different versions, right? Do you do people biases first, and then business? Or do you break SEEDS up over a month? Then there was a really interesting discovery, which is that there are three kinds of mitigations that you need to do, because we wanted to study mitigation, not study awareness, right?
So what we found is there's three really different types of mitigation you can do. There's something in the moment. So if you're in a meeting and someone says, “Hey, I really liked this person. We should give them a shot.” You might say, “Hey, let's make sure that's not just a similarity bias. What data do we have that they have the skills?” right? So it's something you do in the moment.
And people kind of think of those things. But those things are not the most powerful at all. What we found is two things are actually more important in a way that in the moment. One of them is called if-then plan. An if-then plan, if you follow our work, we talk about it a lot. But if-then plans, if I'm recruiting a senior role, then I will have a diverse panel helping me make the decision, for example, right? An if-then plan. So it becomes a protocol, in a way. It becomes a habit.
But then the even more important thing is what we call a preventative measure. And a preventative measure, the famous one everyone's heard of, is taking people's gender, age, race, everything out of the application process so that you're taking bias out right at the source, right? So you've got an if-then plan. If, the word, it's almost like a computer. If-then, right? So if-then plan is like a habit that works more at a team level. And a preventative measure works more like a functional or whole organizational level, a little bit more.
Coming back to question, there was this whole internal debate. How do we teach this? Do we teach the mitigation things first? Do we teach the models first? Do we do – And we're up to about, I think, version three of complete overhaul in like the third time. But we have been able to teach this over a month in literally three videos and in one-hour experience in a way that gets 78% of 10,000 people using it every week. Have data on it. So we know that around 78% of folks, when they learn it in this digital solution, use it every week in some form or another. So we know it works. But it was a really complex. And we still argue about it to this day. Like have we got it right? And we're up to version three.
[00:21:32] EM: Right. And that's pretty remarkable impact. But scientific organization, you have to test things and iterate over time. Something that I want to go back on, you mentioned that we've rolled out three versions of Decide by this point. But let's hear about the early days. What was the first rollout of Decide like for you?
[00:21:52] DR: Yeah. I mean, go back to the story with BlackRock. It was fascinating. We co-built a half-day experience with them that I think we facilitated a few, they facilitated a few. We co-facilitate. But we co-built a program, because we know about learning design. We have a thing called designing for insight. We're really interested in designing to maximize the strength of insight. They knew their organization and the people and the process and all that stuff. So we co-built that half-day workshop.
One of the most interesting things that happened out of it, and it's a story that still kind of influences us, is we talked a lot with Matt and the team then about how do we make sure this really, really sticks. And it wasn't just a half-day workshop. It was really an experience. And the really fun idea that came up that they executed across the world, was at the end of the workshop, people – And this is their managers of all their offices. So the management team of all their offices around the world went through. What they did was, at the end of it, they wrote an if-then plan on a card, right? On a big card at the end of the workshop. And this is on the days when we had in-person workshops. They wrote an if-then plan big on a card and they were photographed holding this app. And those photos were put in the lobby of their offices around the world.
And people come in, employees, customers, everything coming into the office would see these commitments people had to mitigating bias. It was such a powerful way of really ensuring this work gets used, and is public, and all that. And we've seen lots of different ways clients have tried to make this kind of top of mind for people. There's this wonderful cube that an organization built with us. That's kind of the bias cube. We see posters on the walls. We see all sorts of ways that we've been experimenting with customers to kind of make this really present. But that was kind of the most fun one, I think, in the early days.
[00:23:44] EM: Very exciting. Actually, I want to continue walking through this story. So we have this initial launch. You've touched on some of the different ways that companies have rolled out Decide, and practice it, and sustained it. What have you learned over the years as you've iterated on Decide and created different versions of it to suit the different needs of organizations?
[00:24:05] DR: Well, it's been seven years, and it's over 300 organizations. And we don't have a count of the number of people who've used it. But we're now impacting about 4 million people a year. And probably one-and-a-half to 2 million people managers a year are learning the SEEDS model now. So that's kind of 10 million people's boss, something in that order. So it's definitely having an impact. But it's been such an interesting journey.
Look, there's kind of three different levels to think at when you're trying to build habits in a large population. And breaking bias is one of the hardest habits to build. But we've been really inspired by how much momentum we've been able to get. But like in any of the habits, breaking bias, or having more of a growth mindset, or being more inclusive, or getting people to speak up, like all of these are habits that can get woven into an organization. You can't do them all at once. You've got to kind of focus on one thing at a time.
But sort of what we've learned is there's kind of three levels at which to think. The first level at which to think is have we got the right habits, right? Like, are we teaching people as few possible habits? Are they the right habits? Do they really work? That's the hard thing. Got to get that right. That took us three-and-a-half years, right?
The second thing is are you teaching individuals in a way that it will really, really stick? So it’s one thing to have the right habits. It's another thing to just put people into a half-day or one-day classroom. You actually don't get much stickiness. In fact, we've got a piece coming out in Fast Company in the next couple of weeks. Sharing out our data for the first time, we're going to be able to be really solid on the difference between workshops and doing things virtually. And it turns out doing things virtually the right way kills workshops, like hands down, beats hands down, for building habits, because you can follow the right principles of doing things one at a time, go and applying them, doing things socially, spacing out learning. There's a whole bunch of things you can do in a virtual learning environment that you can't do in a workshop.
So the first thing is you got to get the habits right. And for us, we iterate and experimented over and over and over to try and work out what those habits were. We had SEEDS, one of the habits, right? And what do we teach first? And what do we teach second? And what do we teach third. And so the architecture of the learning journey is sort of step one. But step two is how do you teach it in a way that really, really sticks? And most companies get that second thing really, really wrong. But there's a third thing that very few companies get right, and that is how to change a large number of people?
And if you've been following us, you saw the Boeing case study recently. We're really excited about that. We'll be able to talk about that a bit more publicly shortly with a white paper we're coproducing. But Boeing was a good example of kind of doing things the right way and listening to our team about kind of the right way to impact a large population.
So the wrong way to get a company to address bias is just teach it to your top team and hope things change, or what we call the sort of trickle-down effect. Training is often done in this sort of trickle-down effect that we're going to teach the top 100 leaders and we're going to hope that the next 1000 people get it. But we've been thinking about this for a really long time. How you change an organization? And it's not just around bias. But it's even more important around bias, because bias is one of the hardest things to do. And that is, if you just put this as a module for people to learn if they feel like. That's okay. You'll get some return. But you'll get a radically better return if you actually treat this as a campaign. And you have a relatively short amount of time that the whole organization goes through this. And it doesn't matter if it's 100 people, or 1000 people, or 100,000 people, even a million people. Using the digital strategies we built, you can literally get an entire company of any size to all be focused in the same quarter, or even the same month, on addressing this in more of a campaign format.
So we've been getting sort of more confident in that as we get more and more data. We can literally show an organization like, “This is what will happen if you just put it in your learning portal. This is what will happen if you sort of do it this way. But this is what will happen if you do it as a campaign. We can show people the difference in how many folks now mitigate bias every week.” So you really want to do it as a campaign, often branded. It doesn't have to be called Decide. So a lot of our partner clients call it something else, weave it into a different solution, tie it to existing business goals, launched by the CEO. These kinds of things are really, really important.
So there's sort of three levels to get right. And the first level is literally what are the habits? The second level is how do you embed those habits in people? And the third level is how do you make that work at scale across a large organization? That's the third one. And that's one that I think we've got more data and expertise in now than anyone over the last five to 10 years?
[00:28:53] EM: Definitely. Well, thank you for providing that framing. It really speaks to me as somebody with a marketing background, particularly thinking about the idea of like pushing things – Or not even pushing. Pushing is not the right terminology. But making something, I think you said this, compelling rather than mandatory is more effective. And then, of course, I know our organization talks about the concept of stickiness, which, in my mind, I always connect it to Mad Men and their – What's the quote? Make it simple, but significant.” And so I see kind of those principles in play.
[00:29:23] DR: Can we get back to something you said, because it's actually a really important point? And we've argued with organizations about this. This is definitely not something you want to make mandatory. And as you said it, you want to make it compelling. And we actually wrote a whole piece on this. And there's a lot of evidence that diversity training that is mandatory can backfire and make things worse. We wrote a piece. I think it's called Is Your Unconscious Bias Training Making You More Biased? Or is your diversity program making you more biased? It was in strategy and business. And there's a lot of good evidence that forcing people to learn about this stuff will tend to make things worse. People think if they don't make it mandatory, people won't do it. What happens if you make it mandatory is you get like 90% of people do it. But most of that 90% is annoyed. And the people that really need it most are really annoyed and become even more kind of annoyed than they were before. Because, generally, the people who are the most biased don't believe that they have bias. And now they feel accused and forced into something that they think is a waste of time.
Remember, you don't see your own biases, but you do see other people's, right? So if you have a bunch of bias, you're still seeing other people's bias. People see other’s bias. So if you force people into education, it can really backfire. This is – Again, maybe it's not as important with other things. But with bias mitigation, it's really important that you make this compelling and not mandatory.
[00:30:46] EM: That makes a lot of sense to me. And it also has me thinking about where organizations are at when they're thinking about, “Oh, I need to do something about unconscious bias,” especially when you say a lot of people – Or people don't generally recognize that they hold unconscious bias due to it’s unconscious.
So I want to step backward a little bit and think, where does something like a Decide live in a pathway? Like, how do people arrive at getting into unconscious bias at scale, or unconscious –
[00:31:19] DR: No. It's a good question. So we've had a DEI practice basically for seven years since 2015. And it kicked off with mitigating bias. And we didn't mean to build a DEI practice. We just literally wanted to solve the biggest problems that needed the most solving. And it turned out bias was one. And once we started doing work on bias, a whole bunch of companies said, “Hey, what about inclusion? And so we started a whole lot of research on inclusion. And we built a solution called Include after a couple of years research. That was a much easier solution to develop. Less feisty. We got three really clean, clear habits that have now also gotten to a few million people. And then after inclusion, people were like, “Oh, okay, but what about getting folks to speak up? It's similar to inclusion, but not exactly the same. And then what about allyship? What's all that about?”
So we sort of, by accident, became a big provider of solutions in the DEI space by listening to what customers said they wanted next and what was important. But this question always came up. Like, do we do bias first? Do we do inclusion first? What do we do? And how do we do it? And how many things should we do? We're starting to get some data on this and some insight on this from a lot of practice.
And if you think that you got to transform DEI with one set of habits, good luck. Tell me what those habits are, please. We haven't found them. There's not one set of habits. Mitigating biases, three difficult habits. Learn them one at a time. Apply them across a whole company. We found a lot of value in starting with that. But you don't have to start with that. And what we've actually seen is it's great to start with growth mindset.
If you’re trying to really move the needle on DEI across a company of, say, 10,000, you probably want to start with growth mindset, which gives people this real openness and willingness to seek other perspectives. It literally opens their mind to often being wrong and to wanting to learn and recognizing our own – And not so much biases, but our own limitations in our own thinking.
So growth mindset is kind of a safe entry point. And the way I've been thinking about it lately is it's like the soil. It's very foundational. You can't grow plants without soil. But putting soil doesn't mean the plants grow, right? But if you have good soil, you'll potentially have good plants. So in the DEI space, kind of growth mindset is like the soil, it's the foundation. But from there, bias is a good next step. But we haven't seen anything in the data that says it's necessarily better than, say, doing inclusion next. You can kind of go either way. It depends on the willingness in the audience, the sort of pressure in the company. You can kind of go either way. What's exciting is you can scale something like breaking bias to any size company in literally a quarter and then move on a quarter later to, say, inclusion. And then move on a quarter later to, say, building allies.
But we've seen about four of these different solutions woven together either into kind of a year, to year-and-a-half, or up to two years. That's kind of become a common pattern. So organizations are impacting a large audience with three or four of these different big ideas over, say, a two-year period. And that seems digestible and really interesting.
[00:34:26] EM: Thank you. I saw a very interesting question. It ties to some of the conversations we were having about empathy on the show in recent weeks. Do we really see other’s bias? Or are we projecting our own onto them when we think we're having that perception?
[00:34:43] DR: That's a great question. I haven't thought of that before. It’s interesting. It's probably a mixture if I had to guess offhand. But you do see people's agenda. If you're in a meeting with a finance person, and a lawyer, and a marketing person, you're having a conversation about a new product. You'll see the lawyer speak from their agenda of being safety bias-focused, right? And you can kind of see that they're just managing their downside. That's their agenda. But then you'll see the marketing person managing their agenda. But what we don't see is that, literally, they're in different meetings. They're in the same meeting, but they're literally processing the same information really differently through their biases. So the lawyer has a lot of safety biases built in.
So we do see people acting from you might think of it as an agenda. But there's a bias, obviously, often, at the heart of it. We can see people just like not thinking deeply, skating over something. We can see someone saying, “Oh, Bob was a great salesperson. So let's assume he’ll be a great sales manager,” right? It’s like, “Hang on. Have you thought about what is different?” right? And so then that's an expedience bias, by the way. That's the first E in SEEDS.
So you can see people kind of haven't done thinking. And so you can see that bias. You can see people passionate about their perspective. And it comes from some kind of painful or exciting experience that they've had. And that's experience bias. You can see someone who's absolutely sure they're right, and yet the person next to them has a completely different experience, right? And you can call that out.
As you learn about biases, you do see them in other people. And some of them may point to – But you can see someone really liking someone and giving them too many free passes just because they like them. And that's a similarity bias. They wouldn't do that with someone else. So I mean, we've built the Decide solution and the whole practice on the insight that teams together can see biases in each other in real-time and in conversations that are happening, or decisions that are being made, or processes. And you can, as you learn it, you do see the biases in a decision, or a conversation, or a process, and it's outside of you.
[00:36:59] EM: Right. That makes a lot of sense to me. And I really appreciate the question from Paul, he was the person who surfaced it, because it got me thinking once more about the connection between bias mitigation and kind of the shared social learning and doing component. As we navigate these together, we're able to have conversations about unconscious bias.
[00:37:20] DR: The new version of decide – We actually changed the habits. So it used to be accept, label, mitigate. So the first thing you learn in an earlier version of Decide was accept that all brains are bias. Label the kind of bias happening. And then mitigate according to that. And we actually kind of moved that further along and we said, “What we actually need to do is label, mitigate and engage.” So we need to teach people to label the kind of bias that they see around them, one of the five SEEDS things. Mitigate, ideally, with an if-then plan or a preventative measure. And then work to engage your team in and in the wider organization in that bias mitigation strategy. And so we realized that we needed to do more work. Because as Bob was bringing up, you can notice the bias and everyone hate you. How do you bring these things up? So the new program, the new Decide, is label, mitigate, engage, with more work on how do you actually get these mitigation strategies happening and alive?
[00:38:18] EM: Great. Speaking of kind of making these strategies happening and alive, I know that we've touched on this kind of in brief in some slides. But I understand that we are thinking of a Decide and Practice program. I want to hear a little bit more about what you're thinking for that program. But more importantly, I want to hear about what is it that you are trying to solve for and launching this next evolution of Decide?
[00:38:43] DR: If you follow us for a while, you'll see we do a lot of experiments. And we're about to do another big experiment. And our hypothesis has been the right way to change a culture is give a lot of people a few things that really work all at the same time. So if you've got 10,000 employees, don't take two years to put your top 100 into training. Give three simple habits to all 10,000 employees in the same month. And do that in a clever way that is aligned with the business and all this stuff. So that's been our strategy. So give people three simple things to do.
And we've got this amazing amount of data about how many habits people apply from that process. I think our head of CX, Katherine Milan, has got a session. It might be next week or sometime in the next month, on our whole measurement philosophy and how we measure habits and things. It's a fascinating field. But we kept having organizations saying that we love Decide. It actually has made a difference, but there's so much more work to do.
And we looked across all our solutions and said, “Hey, there might be a case for giving a whole company three things to focus on quickly, but then going deeper with maybe a smaller audience or maybe even the whole coming. But going deeper.” And so we conceptualize this thing we launched at the summit recently. It's called the In Practice Series. So we're going to start with Decide in practice. Then we'll probably do Grow in practice. And then Connect in practice, include in practice. So the kind of the bigger solutions. But Decide in-practice is essentially, we will do this as a HIVE. And a HIVE is a cohort every week for three weeks, 60 or 90 minutes, synchronous, on a Zoom. But it's a very challenging learning experience.
Anyway, HIVE stands for high-impact virtual experience. The Decide in-practice HIVE is literally a chance to practice label, mitigate and engage. And we're still kind of working on it. But the first week is like you're actually going to practice in all these different kinds of businesses, business and people decisions. You’re going to workshop together, and brainstorm together, and practice.
Literally, over three one-hour or 90-minute sessions, you're going to have a chance to dig much deeper into real cases, real scenarios and actually practice label, and mitigate, and engage, and just get a whole lot better at it. And one of the things that we're hoping out of this also is that we'll get a lot more preventative measures activated and if-then plans, but particularly preventative measures, which are the organizational systems that address bias at the source. So that's kind of our sub-goal in that initiative.
So Decide in practice, if you're from an organizations, or you run Decide, we can talk to you about what that looks like. We can start small, with some small cohorts and then scale it and all this stuff. So we're interested in kind of going deeper in that solution.
[00:41:25] EM: Great. There are two things that come up. If you've run programs like these before, how do you keep them fresh? Or how do you refresh them? I think Decide in practice kind of speaks to that idea of sustainment and keeping things in action for people. But have we thought about where storytelling factors into all of this? And I think that's an important question as we roll out programs. You touched on it a little bit in making things compelling. But can you give us a little more?
[00:41:52] DR: Yeah, we probably should do a whole session in Your Brain at Work Live on basically how you keep any of these habits alive in an organization, sustainment. And there's a whole world in that. And there’s like someone walking around with an iPhone and capturing people's stories in three minutes and kind of putting them together. There's the CEOs jumping into meetings and asking people about their bias mitigation practices lately, and all sorts of things. There’re also the sustainment practices to keep this alive.
I will say the way that we think about a rollout of breaking bias in an organization is not everyone's going to learn this for a month and then it's going to go. They’re going to learn it for a month, then we're going to follow up with like measuring. And then six months later, we're going to come back and measure again like how many times a week are they still applying this. But more importantly, what we see happening is organizations mostly have their own accord, start weaving the SEEDS into all sorts of everyday work practices.
Let me give an example. Qantas, that we taught SEEDS to, the great Australian airline. I can call them the great Australian airline, they built a checklist for talent reviews that was very similar. In fact, they have the same formatting as a flight takeoff checklist. That was literally, before you do a talent review, you should take into account these SEEDS biases and take these steps. And so that's a fun one. But we've seen all sorts of organizations do this. So SEEDS suddenly becomes not just like a model or a training, but it becomes embedded in your recruiting tools, your promotion tools, your performance management tools.
Now, sometimes, maybe a third to a half the time a company will come back to us and say, “Can you help us build those?” And we have a whole consulting team. We do that as well. But probably half or a bit more that companies just do that on their own. They've got their own internal consultants. So it should be embedded.
The other thing is the content, and the ideas, and the IP, a license to an organization for multiple years. And it should show up and does show up in all sorts of other leadership programs. Breaking bias should show up in your strategic decision-making programs, right? In your conflict resolution programs. In all sorts of places. So it ends up being this kind of – Almost like this sort of, I don't know, this kind of patch or meme or something that shows up in lots of different places, in forms, in other trainings, in language, in assessments. And this is how we keep it alive. It's not just a training. But it's something that becomes part of the organization's ecosystem.
[00:44:14] EM: Right. That makes a lot of sense. Fascinating. I really love seeing how so many of our different ideas are intersecting here, because I think you hear a lot of SCARF in here in terms of relatedness. And I know that we touched on autonomy earlier with making things compelling rather than mandatory. So what is it that you would like for the audience to know as we close out, David?
[00:44:35] DR: The thing that I'm really excited about at the moment is something I've been trying to do for three years. And the NLI team is sick of me saying this. But for three years I've been saying we've got so much insight and research on not just bias, but inclusion, and raising employee voice, and allyship across the DEI space. I literally can't keep up. And I realized we're like long overdue to kind of put together a syllabus of, this is NLIs point of view and approach to DEI. And of course, mitigating bias is a really important foundation, but there's a lot more.
And so I'm super excited that we're just launching what we're calling out DEI Practitioner Masterclass, a bit like the In Practice program. It'll be the first in a series. So we'll do a practitioner masterclass for people involved in leadership and learning. We'll do one for performance management. But we're launching, I think, in May, coming up, our first Practitioner Masterclass for DEI folks. And its application only. It does need to be internal practitioners and not external consultants. I've seen some of the people who've already start to apply this. Some incredible executives, DEI executives from some incredible organizations. It's going to be just such a brains’ trust to learn from each other, as well as to learn from our scientists and our research. So I'm super psyched that we're launching the DEI Masterclass.
And if you like learning about the sort of deeper stuff around bias, what I've shared today is probably like 5%, of what you'd want to know around the SEEDS model and all the different issues and all the different stuff. There's like so much more to kind of dive into just on bias to really understand the space. Super excited about that. And it's just been great to tell the story of the journey. It's been an incredible journey for seven years. I mean, we could do one of these just on inclusion, not to mention all the other work, because there's a lot that we kind of haven't shared in many ways. And maybe we should do one on inclusion, because that's also been a really surprising, challenging, interesting phenomena to really lean into.
So yeah, that's it for me. Thanks, Evynn. It’s great to collaborate with you this way. And I appreciate the opportunity to tell the stories.
[00:46:48] EM: Yeah, thank you so much. If you want to apply right the second, you can also visit neuroleadership.com/deinext. The application form is right there on the page.
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