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Welcome to the Be Good podcast,

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 where we explore the application of behavioral economics for good in order to nudge better business and better lives.

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Hi,

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 and welcome to this episode of Be Good,

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 brought to you by BVN Nudge Consulting,

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 a global consultancy specializing in the application of behavioral science for successful behavior change.

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 Every month,

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 we get to speak with a leader in the field of behavioral science,

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 psychology,

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 and neuroscience in order to get

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 to know more about them,

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 their work,

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 and its application to emerging issues.

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 My name is Eric Singler,

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 Managing Director of the BVA family and CEO of BVA Nudge Consulting.

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 And with me is my dear colleague,

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 Suzanne Kirkendall,

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 CEO of BVA Nudge Consulting North America.

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 Hi,

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 Suzanne.

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Hi,

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 Eric.

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 Thanks for having me back.

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 I'm very happy to be part of another episode today and to be introducing our guest,

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 Professor Joe Devlin.

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 Joe is professor of cognitive neuroscience and a former head of experimental psychology at University College London,

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 or UCF.

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 Joe is a leading figure in the field of neuroscience,

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 especially renowned for his work in language processing and consumer neuroscience.

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 He's been a driving force in advancing our understanding of how the brain interprets and processes language,

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 as well as exploring its remarkable adaptability through neuroplasticity.

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 He's also widely recognized for his contributions to debunking common neuromyths,

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 such as those surrounding brain training programs and learning styles.

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 Joe is the author of over 80 articles in top scientific journals,

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 including Science,

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 Nature,

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 Nature Neuroscience,

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 Current Biology,

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 and Proceedings of the National Academy of Sciences.

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 But Joe is also interested in the application of the most recent advances in neuroscience,

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 behavioral science,

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 nudge,

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 and AI to finding solutions for

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 businesses.

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 His work has expanded into areas such as advertising effectiveness and using neuroscience tools like fMRI to measure the brain's response to marketing strategies,

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 which is research that's becoming increasingly relevant for business leaders and marketers alike.

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 So today we're very honored to have Joe join us on the Be Good podcast to share his insights and discuss his recent work at the intersection of neuroscience and leadership.

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 Welcome,

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 Joe.

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Thank you so much.

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 I really appreciate the invitation to be here.

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 So thank you,

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 Suzanne.

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 Thank you,

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 Eric.

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So,

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 Joe,

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 time to start this very promising conversation.

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 I think we met a few years ago when we both attended a conference in

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 Japan.

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 I was,

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 I have to confess,

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 very impressed by your presentation.

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 And since then,

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 I have been closely following your fascinating work and publication,

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 particularly on LinkedIn.

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 It's impressive how you are active.

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 on LinkedIn with very detailed and insightful posts.

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 So before talking about this,

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 I'd like to start our conversation by going back to the beginning of your career.

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 I believe you earned a PhD in artificial intelligence,

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 but you found it more interesting to focus on human intelligence and how the brain works.

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 I don't know if you remember,

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 I think it is a quote.

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 attributed to Amos Versky.

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 My colleague works on artificial intelligence,

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 and I work on natural stupidity.

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 So it reminds me of this.

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 Could you tell us more about why this interest in cognitive neuroscience?

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Yeah.

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 Well,

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 when I was a kid,

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 I really love the idea from science fiction,

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 really,

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 of being able to speak to people or creatures or whatever that were different from us.

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 The idea of aliens,

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 right?

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 But I also liked the idea of being able to speak to computers.

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 And they just fired me up when I was a young lad reading these stories.

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 So,

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 when it actually came time to do my PhD,

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 I thought,

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 this is great.

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 I want to be part of the artificial intelligence movement and try to be able to communicate with computers.

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 But...

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 As you said,

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 I did my PhD a long time ago,

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 and the tech really wasn't there.

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 Finally got there about two years ago.

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 And it made me a little bit frustrated with what the state of the art was in AI in the

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 1990s. So I did some work in artificial neural networks,

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 and that was the basis of my

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 PhD thesis.

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 But I got frustrated with how artificial they were and how far they were removed from the things I wanted them to be able to do,

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 like chat with them.

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 So I thought,

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 well,

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 I should learn something about the brain.

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 And the time was right because all...

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 And at that moment,

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 these new non-invasive brain imaging tools had become available,

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 positron emission tomography,

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 functional magnetic resonance imaging.

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 And it allowed you to look at people using language in vivo,

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 like as they were doing it,

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 without doing any of the more invasive things that neuroscience sometimes does.

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 So it was such an exciting opportunity.

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 I thought,

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 I'll learn a little bit about the brain.

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 I'll come back to the whole AI thing.

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 I got stuck for 25 years learning about the brain.

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 And fortunately for me,

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 I feel like AI has come back to me with all of the advances in the last couple of years.

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Your journey into neuroscience has led now to significant,

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 very significant contribution in understanding language processing in the brain.

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 What initially drove you to this field and how did your early experience shape your research path?

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Well,

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 I was...

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 I was always convinced that language was the thing that differentiated us from other species.

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 So fundamentally,

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 we're all animals,

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 but we do a bunch of things that other species don't,

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 right?

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 And language seemed to be at the heart of it for me.

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 So that seemed to be the key aspect of being a human.

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 And that's why I was so fascinated by it.

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 I was very fortunate early on in my career to get to work with

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 Kathy Price,

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 who is based at University College London.

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 who is a real pioneer in studying language in human beings using these kind of non-invasive tools.

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 And the opportunity to work with her and learn from her meant that that just fired up my enthusiasm.

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 I was thinking,

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 this is this brand new space that there's so little known,

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 and there's so much opportunity to contribute.

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 And I was fortunate to be in the right place at the right time to be able to contribute my part to those things.

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 It was a very fortunate time because there were a lot of brilliant people around me who I had the opportunity to learn from.

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 Kathy was one.

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 Paul Matthews was a mentor of mine when I was at Oxford.

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 And Paul was stupendously influential in terms of being able to give hard advice with a smile,

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 which is a real skill,

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 right?

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 Like I tried to learn that from Paul even at the time.

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 But I remember one thing Paul said to me was,

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 Joe,

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 you do good work.

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 but nobody cares because you don't make it interesting,

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 which is like a tough message,

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 right?

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Okay,

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 it reminds me,

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 we have just interviewed some weeks ago,

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 Kim Scott,

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 who has written a wonderful book,

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 Radical Candor,

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 which is exactly about care and being demanding and which is supposed to be the good way to manage people.

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Well,

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 it's certainly the case that I admire Paul's leadership to this day,

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 and he's had such a lasting influence on my career.

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 Because once

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 I could actually hear his message,

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 it took me a little bit of time,

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 I really started thinking about,

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 well,

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 how do I share this information?

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 How do I make it accessible?

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 And to some extent,

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 that's kind of culminated in things like my LinkedIn profile at this point,

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 where I regularly try to communicate science and make it interesting for a general population,

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 which is something I really enjoy.

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 And honestly,

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 I don't think I would be here.

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 but for that level of candor from my supervisor.

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You have started to talk about your mentors.

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 Any other mentors or influential figures that guided your focus towards studying the neural basis of language and cognition?

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Well,

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 one of the people who really made a big difference early on in my career was

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 Jay McClellan,

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 who's one of the founders of artificial neural networks.

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 So some of the work that Jay and

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 David Rommelhart and Jeff Hinton...

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 who just won a Nobel,

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 was incredibly influential.

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 So,

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 he was this towering figure in my academic life,

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 but I had the opportunity to meet him early on and he was such a wonderful man.

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 He was absolutely lovely and very interested in what a young graduate student was doing and helped encourage me.

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 And it was funny because that made a big difference because I thought,

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 oh,

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 okay,

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 if you can be as important and influential as Jay,

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 member of the National Academy of Sciences,

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 et cetera,

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 and still have time to listen to your junior colleagues and promote them and be helpful.

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 That was a big deal.

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 Like it made a difference and it shaped the way I try to mentor my students over time.

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 And then later,

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 obviously Kathy and Paul had a big influence in my career,

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 but

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 I've been very fortunate to just be in a very rich community of incredibly smart people,

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 both the people who are

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 sort of more senior than I am.

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 And often my students,

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 you know,

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 who more junior,

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 but incredibly sparky and bright people with great questions who just don't stop.

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 They want to answer it and they want to do it in a good way.

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 And that is incredibly inspiring to me.

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To transition from understanding your career path and to talking more about the content of your work,

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 I want to first start by grounding us with some fundamental questions about the brain.

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 So can you just start at the most basic level?

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 telling us what our brain's for.

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 What is the fundamental role of the brain in human life and behavior?

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So this is admittedly a controversial answer because people argue about it.

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 But from my perspective,

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 if I just look at it from the lens of evolution,

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 the reason that we have a brain at all is to help us survive and pass on our genes,

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 which is true at a species level,

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 not necessarily at an individual level.

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 It doesn't mean that anyone who hasn't passed on their genes doesn't

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 a perfectly good brain.

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 I'm not trying to say that at any level.

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 But the reason that all of us have brains is to adapt to our environment and survive and pass on those genes,

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 right?

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 So,

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 what that means is that

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 Your brain takes a ton of energy to do this.

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 So,

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 the more effective it is at helping you survive in your environment,

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 the better.

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 But also surviving now is slightly different than surviving in our,

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 you know,

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 Neanderthal caveman kind of era.

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 But the brain hasn't changed that much in those 10,000 years or 100,000 years,

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 which means that some of the things the brain does that were very effective back then are a little bit maladaptive now.

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 Just as an example.

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 Throughout most of our history,

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 the central problem that we faced in survival was getting enough calories.

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 Literally,

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 do you have enough to eat and live and survive for you and your family?

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 Which means that things that are high in calories are incredibly rewarding in our brain,

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 like fats and sugars in particular.

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 The problem is that now,

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 many of us have access to all the calories we need plus.

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 I'm certainly an example of that.

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 But it does mean that

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 your brain still responds incredibly strongly to things like chocolate that combine sugar and fat.

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 And it's a problem because it can lead to things like type 2 diabetes if you sort of overindulge in these things.

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 So,

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 even though the response was perfectly sensible when it evolved,

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 it's a little bit maladaptive now.

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 And there are lots of examples of that,

262
00:12:25.943 --> 00:12:30.585
 which is one of the things I think is really important about trying to understand why we have a brain,

263
00:12:30.725 --> 00:12:31.425
 how it functions,

264
00:12:31.445 --> 00:12:32.286
 where it came from,

265
00:12:32.726 --> 00:12:34.387
 and why it's doing what it's doing now.

266
00:12:34.847 --> 00:12:35.187
 Because...

267
00:12:35.547 --> 00:12:37.509
 sometimes it doesn't seem like it makes sense.

268
00:12:37.729 --> 00:12:42.653
 You have to understand it in context to understand why it acts the way it does,

269
00:12:42.994 --> 00:12:46.797
 and then to try to manage it appropriately in the environment that we actually live in.

270
00:12:47.337 --> 00:12:48.719
I think we can all relate to that.

271
00:12:49.179 --> 00:12:54.103
 So there's a growing focus in neuroscience now on the relationship between the brain,

272
00:12:54.344 --> 00:12:54.804
 the body,

273
00:12:54.964 --> 00:12:55.805
 and the environment.

274
00:12:56.365 --> 00:13:00.809
 So can you tell us a little bit about how those three things interact to shape our thoughts,

275
00:13:00.829 --> 00:13:01.530
 our actions,

276
00:13:01.550 --> 00:13:02.571
 our overall cognition?

277
00:13:02.983 --> 00:13:03.103
Yeah,

278
00:13:03.123 --> 00:13:08.406
 I think this is a really exciting area in neuroscience and it goes by the name of embodied cognition.

279
00:13:08.927 --> 00:13:12.229
 The sort of central idea is that our thinking,

280
00:13:12.389 --> 00:13:12.849
 reasoning,

281
00:13:12.889 --> 00:13:16.211
 emotional things aren't just a product of our mind.

282
00:13:16.611 --> 00:13:20.974
 They're actually influenced by our body and our body's interactions with its environments.

283
00:13:21.394 --> 00:13:21.514
 So,

284
00:13:21.574 --> 00:13:22.214
 for instance,

285
00:13:23.455 --> 00:13:29.439
 there was an amazing study that Sarah Garfink and her colleagues did a few years ago where they were looking at gut instincts,

286
00:13:29.579 --> 00:13:29.739
 right?

287
00:13:29.879 --> 00:13:31.960
 So everybody knows intuitively what that is.

288
00:13:31.960 --> 00:13:35.302
 You have this gut feeling and sometimes you ignore it and sometimes you go with it.

289
00:13:37.343 --> 00:13:50.490
 But it turns out there's a whole part of the nervous system called the enteric nervous system that are nerve cells that line your gut that actually give you information about its internal state and that affects your sort of mental processes and emotional processes.

290
00:13:51.271 --> 00:13:51.671
 And of course,

291
00:13:51.751 --> 00:13:52.191
 vice versa,

292
00:13:52.191 --> 00:13:53.132
 it also affects the gut.

293
00:13:54.332 --> 00:13:59.115
 And what they did was this study with financial traders where they looked at a series of these.

294
00:13:59.355 --> 00:14:03.037
 people who worked in financial trading on the trading floors.

295
00:14:04.618 --> 00:14:09.821
 And they measured how sensitive they were to their sort of gut reactions.

296
00:14:09.861 --> 00:14:11.222
 And you can do this a lot of different ways,

297
00:14:12.062 --> 00:14:12.763
 and they used a few.

298
00:14:13.303 --> 00:14:20.948
 But what they found was that the people who were more sensitive were more successful financially in the year that they studied them.

299
00:14:21.228 --> 00:14:25.370
 But also the people who are more sensitive were the people who lasted longer in financial trading.

300
00:14:25.710 --> 00:14:26.751
 So it seems to have

301
00:14:27.363 --> 00:14:32.906
 absolutely real world applications that go beyond just our almost gut instinct to say,

302
00:14:32.966 --> 00:14:33.106
 yeah,

303
00:14:33.186 --> 00:14:33.366
 sure,

304
00:14:33.687 --> 00:14:34.307
 I believe that,

305
00:14:34.367 --> 00:14:35.307
 that's the way I feel.

306
00:14:35.768 --> 00:14:38.849
 But it's so often easy to ignore your gut,

307
00:14:39.050 --> 00:14:39.530
 as it were,

308
00:14:41.111 --> 00:14:43.852
 and make decisions that you think are cognitively rational,

309
00:14:44.412 --> 00:14:47.634
 even though they don't necessarily fit your instincts.

310
00:14:48.034 --> 00:14:50.236
 And there's a reason we have those instincts.

311
00:14:50.276 --> 00:14:53.998
 It's part of our nervous system and it's part of our survival mechanisms.

312
00:14:54.858 --> 00:14:55.759
 So not all of us are,

313
00:14:55.899 --> 00:14:56.139
 you know,

314
00:14:56.711 --> 00:14:57.451
 financial traders,

315
00:14:57.651 --> 00:15:01.313
 but all of us have these interactions between the body and the brain,

316
00:15:01.433 --> 00:15:04.034
 and they really very much influence the way we act,

317
00:15:04.134 --> 00:15:04.354
 think,

318
00:15:04.514 --> 00:15:04.774
 live,

319
00:15:04.854 --> 00:15:05.355
 and feel.

320
00:15:05.875 --> 00:15:05.995
 So,

321
00:15:06.375 --> 00:15:10.837
 it's an important area in neuroscience and really developing quickly,

322
00:15:10.877 --> 00:15:11.197
 I'd say.

323
00:15:12.238 --> 00:15:13.078
Super interesting.

324
00:15:13.758 --> 00:15:13.918
 And,

325
00:15:14.058 --> 00:15:14.298
 you know,

326
00:15:14.318 --> 00:15:15.559
 beyond that gut instinct,

327
00:15:15.739 --> 00:15:24.863
 can you talk about how the brain processes and integrates all sensory information from the environment and how that affects how we respond to our surroundings?

328
00:15:26.019 --> 00:15:26.239
Again,

329
00:15:26.259 --> 00:15:27.340
 a controversial one,

330
00:15:27.400 --> 00:15:28.620
 so I'm going to go with it anyway.

331
00:15:28.980 --> 00:15:32.602
 But there's a traditional perception that we have this world outside of us,

332
00:15:33.102 --> 00:15:35.023
 and it impinges on us through our senses.

333
00:15:35.083 --> 00:15:36.103
 We can see things,

334
00:15:36.584 --> 00:15:37.504
 we can taste things,

335
00:15:37.504 --> 00:15:38.064
 we can smell,

336
00:15:38.084 --> 00:15:38.224
 etc.

337
00:15:39.405 --> 00:15:41.146
 And what happens is that gets into the brain,

338
00:15:41.406 --> 00:15:42.166
 we process it,

339
00:15:42.226 --> 00:15:43.967
 and then we can act on that information.

340
00:15:44.847 --> 00:15:49.709
 I would say that the dominant thinking in neuroscience these days is that that's actually backwards.

341
00:15:50.189 --> 00:15:53.691
 That our brain is actively trying to predict our environment.

342
00:15:53.891 --> 00:15:54.532
 all the time.

343
00:15:54.552 --> 00:15:56.115
 And it's not something you're conscious of.

344
00:15:56.215 --> 00:15:57.438
 It's just what brains do.

345
00:15:58.279 --> 00:16:02.908
 And the reason it does this is because if it's effective in predicting its environment,

346
00:16:03.428 --> 00:16:05.172
 then when the sensory signals come in...

347
00:16:05.672 --> 00:16:09.174
 they don't really need to be processed very much because it already knew roughly what they should be.

348
00:16:09.515 --> 00:16:10.615
 You have little differences,

349
00:16:10.776 --> 00:16:13.477
 but that's relatively computationally simple to do.

350
00:16:14.118 --> 00:16:14.818
 In contrast,

351
00:16:15.098 --> 00:16:19.662
 if all you're doing is constantly processing signals that are changing millisecond by millisecond,

352
00:16:20.062 --> 00:16:23.564
 that turns out to be an incredibly computationally intensive task,

353
00:16:23.884 --> 00:16:27.827
 which means that your brain's spending a ton of energy on it and we're back to calories,

354
00:16:27.907 --> 00:16:28.147
 right?

355
00:16:28.247 --> 00:16:29.248
 It's a hard thing to do.

356
00:16:30.029 --> 00:16:30.149
 So,

357
00:16:31.950 --> 00:16:34.952
 we have these signals that we encounter all the time.

358
00:16:35.260 --> 00:16:37.941
 And the more you are familiar with your environment,

359
00:16:37.961 --> 00:16:41.403
 the more you are good at predicting it unconsciously,

360
00:16:41.463 --> 00:16:43.064
 not really an active thing,

361
00:16:44.084 --> 00:16:44.965
 the easier life is.

362
00:16:46.045 --> 00:16:48.626
 But the problem with that is it leads to kind of a fixed mindset,

363
00:16:49.026 --> 00:16:49.207
 right?

364
00:16:49.467 --> 00:16:52.308
 So that is if you're good at it and life is fine,

365
00:16:52.628 --> 00:16:54.429
 you're getting enough calories for you and your family.

366
00:16:55.266 --> 00:16:55.526
Fine.

367
00:16:55.566 --> 00:16:57.387
 You don't really seem to need anything else.

368
00:16:57.387 --> 00:16:58.167
 You don't have to learn.

369
00:16:58.187 --> 00:16:58.967
 You don't have to grow.

370
00:16:59.887 --> 00:17:05.569
 Which makes it challenging for us because we have to consciously override that if we want to continue to grow and learn.

371
00:17:05.709 --> 00:17:05.949
 I mean,

372
00:17:05.969 --> 00:17:06.249
 you do.

373
00:17:06.569 --> 00:17:07.409
 You'll just do it slowly.

374
00:17:07.690 --> 00:17:10.850
 But if you're actually looking for opportunities to improve in things,

375
00:17:10.870 --> 00:17:11.511
 in your job,

376
00:17:11.531 --> 00:17:12.591
 in your relationships,

377
00:17:12.651 --> 00:17:14.251
 in your family life,

378
00:17:14.271 --> 00:17:14.552
 whatever,

379
00:17:14.892 --> 00:17:16.012
 in your sports that you're playing,

380
00:17:16.472 --> 00:17:22.554
 then you almost have to actively seek out feedback because your brain is basically content to say,

381
00:17:23.074 --> 00:17:23.194
 yeah.

382
00:17:23.478 --> 00:17:25.139
 These signals all match basically what I thought.

383
00:17:25.379 --> 00:17:25.859
 Life is good.

384
00:17:25.979 --> 00:17:27.320
 I don't need to do anything to get better.

385
00:17:27.600 --> 00:17:28.640
 Whereas if you want to get better,

386
00:17:29.000 --> 00:17:31.161
 you need to find the places where you're not doing well.

387
00:17:31.361 --> 00:17:33.842
 And that's where the feedback from the outside world makes a big difference.

388
00:17:34.242 --> 00:17:34.883
Fascinating.

389
00:17:35.063 --> 00:17:35.223
 Well,

390
00:17:35.323 --> 00:17:39.585
 I thought we were going to get into the controversy with Eric's questions on neuromis.

391
00:17:40.025 --> 00:17:40.285
Yes.

392
00:17:40.505 --> 00:17:49.468
 Now that we know a little more about the brain and the interaction with the environment and the body,

393
00:17:50.189 --> 00:17:50.729
 I would like,

394
00:17:50.749 --> 00:17:52.810
 because I have been very interested by your...

395
00:17:53.270 --> 00:17:55.671
 post on LinkedIn about,

396
00:17:56.411 --> 00:17:56.951
 I think,

397
00:17:57.771 --> 00:17:58.591
 key topics,

398
00:17:59.572 --> 00:18:00.792
 neuromyths,

399
00:18:01.152 --> 00:18:04.833
 or I think you have called it neuromilks,

400
00:18:05.093 --> 00:18:08.874
 which are common misconceptions about how the brain works.

401
00:18:09.494 --> 00:18:11.055
 So could you explain,

402
00:18:11.175 --> 00:18:11.435
 Joe,

403
00:18:11.595 --> 00:18:17.156
 what neuromyths are and share maybe some of the most prevalent examples?

404
00:18:18.697 --> 00:18:22.638
Neuromyths are these common misconceptions that are kind of culturally shared.

405
00:18:22.858 --> 00:18:26.621
 And a really common example is we only use 10% of our brain.

406
00:18:27.522 --> 00:18:27.642
 So,

407
00:18:28.483 --> 00:18:31.485
 we've known forever that that's just not true.

408
00:18:31.665 --> 00:18:31.885
 You know,

409
00:18:31.885 --> 00:18:33.307
 you use 100% of your brain.

410
00:18:33.587 --> 00:18:35.889
 If you didn't use 90% of it,

411
00:18:35.989 --> 00:18:38.891
 it would die and sort of dribble out your ears and you'd smell like a zombie.

412
00:18:39.332 --> 00:18:39.452
 So,

413
00:18:40.713 --> 00:18:41.353
 it's just a myth.

414
00:18:41.894 --> 00:18:44.456
 But it's incredibly prevalent in popular culture.

415
00:18:44.496 --> 00:18:46.818
 You see it in movies,

416
00:18:47.018 --> 00:18:48.439
 in self-help books.

417
00:18:48.579 --> 00:18:50.100
 You see it all over the place.

418
00:18:51.141 --> 00:18:51.782
 It doesn't have...

419
00:18:52.258 --> 00:18:54.779
 that many serious implications,

420
00:18:55.119 --> 00:18:55.299
 right?

421
00:18:55.319 --> 00:18:55.559
 I mean,

422
00:18:55.819 --> 00:18:57.980
 whether you use 10% or 100% of your brain,

423
00:18:58.260 --> 00:19:00.381
 how does that affect you on a day-to-day life?

424
00:19:01.722 --> 00:19:01.982
 It does,

425
00:19:02.042 --> 00:19:02.302
 however,

426
00:19:02.362 --> 00:19:03.683
 make for movies like,

427
00:19:04.123 --> 00:19:04.383
 you know,

428
00:19:04.903 --> 00:19:06.784
 Limitless or Lucy and things like that,

429
00:19:06.824 --> 00:19:08.285
 which can be entertaining.

430
00:19:08.885 --> 00:19:09.525
 It's always good to hear

431
00:19:10.585 --> 00:19:13.127
 Morgan Freeman explaining how you only use 10% of your brain,

432
00:19:13.147 --> 00:19:14.367
 because he's very believable.

433
00:19:15.948 --> 00:19:16.128
 But

434
00:19:16.788 --> 00:19:19.449
 I would say that the neuromyths are kind of the low end of the spectrum.

435
00:19:19.649 --> 00:19:21.410
 Things get a little bit more serious.

436
00:19:22.350 --> 00:19:22.470
 So,

437
00:19:23.190 --> 00:19:28.492
 there's another myth or misconception about lizard brains.

438
00:19:28.692 --> 00:19:28.812
 So,

439
00:19:28.872 --> 00:19:29.552
 this idea that,

440
00:19:29.672 --> 00:19:29.952
 you know,

441
00:19:30.192 --> 00:19:31.853
 your brain actually is three parts.

442
00:19:31.973 --> 00:19:39.815
 There's sort of a lizard brain down at the center and that's the oldest evolutionarily speaking and basically is centered on simple needs,

443
00:19:40.935 --> 00:19:41.275
 feeding,

444
00:19:41.395 --> 00:19:41.755
 fighting,

445
00:19:41.815 --> 00:19:42.156
 fleeing,

446
00:19:42.196 --> 00:19:42.756
 those kind of things.

447
00:19:43.816 --> 00:19:44.516
 And then above that,

448
00:19:44.576 --> 00:19:47.377
 maybe you have some sort of mammal brain like a chimp brain,

449
00:19:47.457 --> 00:19:48.497
 sometimes people call it,

450
00:19:48.617 --> 00:19:50.958
 where you get some more emotional information in that.

451
00:19:51.194 --> 00:19:56.356
 And then on top of that sits this human brain that sort of tries to regulate all the little monsters underneath.

452
00:19:57.257 --> 00:19:59.338
 And this one,

453
00:19:59.638 --> 00:19:59.998
 I think,

454
00:20:00.798 --> 00:20:02.019
 is obviously false.

455
00:20:02.579 --> 00:20:03.780
 We've known that for a long time.

456
00:20:03.860 --> 00:20:05.941
 We actually knew that when it was proposed in the

457
00:20:06.321 --> 00:20:09.963
 60s. But it leads to making decisions that aren't ideal,

458
00:20:10.103 --> 00:20:10.303
 right?

459
00:20:10.383 --> 00:20:10.503
 So,

460
00:20:10.923 --> 00:20:13.684
 this is really common in the neuromarketing field.

461
00:20:14.024 --> 00:20:17.206
 And we have agencies that are making decisions.

462
00:20:17.850 --> 00:20:21.952
 to try to appeal to people's lizard's brains because they think that that's where they make their decisions.

463
00:20:22.753 --> 00:20:23.173
 They don't.

464
00:20:23.993 --> 00:20:28.036
 And it's a misunderstanding of the way evolution works to even think about it that way.

465
00:20:28.296 --> 00:20:30.237
 It's a misunderstanding of the way we make decisions.

466
00:20:30.597 --> 00:20:30.717
 So,

467
00:20:30.957 --> 00:20:32.618
 if you're making business decisions on that,

468
00:20:32.978 --> 00:20:34.199
 it's not an ideal solution.

469
00:20:34.239 --> 00:20:35.700
 It has real world consequences.

470
00:20:36.160 --> 00:20:36.660
 To my mind,

471
00:20:36.880 --> 00:20:41.763
 even worse is that there are some areas of therapy that are based on this lizard brain idea.

472
00:20:42.203 --> 00:20:42.323
 So,

473
00:20:42.423 --> 00:20:42.744
 literally,

474
00:20:42.744 --> 00:20:47.026
 if you're trying to help patients based on a misunderstanding of how their brain works.

475
00:20:47.530 --> 00:20:49.912
 I'm not at all convinced that you're helping them at all,

476
00:20:50.493 --> 00:20:53.035
 which maybe that doesn't make things worse,

477
00:20:53.255 --> 00:20:56.417
 but it does stop them for the opportunity to getting therapy that would help,

478
00:20:56.818 --> 00:20:56.998
 right?

479
00:20:57.919 --> 00:20:58.039
 So,

480
00:20:58.179 --> 00:21:05.485
 I think that there's levels from myths that are shared that maybe aren't super important that we get wrong,

481
00:21:05.585 --> 00:21:07.887
 but bother me as a little neuroscientist,

482
00:21:08.567 --> 00:21:12.551
 to misconceptions that I think do have real-world implications,

483
00:21:12.931 --> 00:21:15.713
 all the way to kind of the misuse of neuroscience.

484
00:21:16.094 --> 00:21:16.234
 And-

485
00:21:17.102 --> 00:21:18.443
 There are lots of examples of that.

486
00:21:18.883 --> 00:21:19.423
 You see it,

487
00:21:20.364 --> 00:21:20.724
 I mean,

488
00:21:20.744 --> 00:21:23.286
 a silly example is things called like neuro water.

489
00:21:23.906 --> 00:21:32.131
 You can buy these bottles of water that say neuro water and they're about three times the price of a bottle of non-neuro water.

490
00:21:32.471 --> 00:21:37.534
 And all they've done is they've just plunked the word neuro in front as if that's meaningful and they say,

491
00:21:37.554 --> 00:21:37.834
 you know,

492
00:21:38.054 --> 00:21:39.075
 you need this for your brain.

493
00:21:40.236 --> 00:21:40.376
 Well,

494
00:21:40.376 --> 00:21:40.536
 yeah,

495
00:21:40.556 --> 00:21:41.276
 that's true.

496
00:21:41.576 --> 00:21:44.198
 You do need water for your brain and for the rest of you.

497
00:21:45.070 --> 00:21:48.836
 But that doesn't mean you should be spending three times the amount of money on it.

498
00:21:50.038 --> 00:21:51.901
 That's just exploiting consumers in my mind.

499
00:21:53.069 --> 00:21:53.189
Yeah,

500
00:21:53.469 --> 00:21:54.390
 very important.

501
00:21:55.271 --> 00:21:59.834
 And I think for those in our audience who are interested to know more,

502
00:22:00.934 --> 00:22:09.440
 you described precisely the 10 main neuro misconceptions that you have identified.

503
00:22:10.221 --> 00:22:17.205
 So why do so many people believe these false ideas?

504
00:22:17.506 --> 00:22:20.308
 And it's about close to fake news.

505
00:22:21.408 --> 00:22:21.748
 He said...

506
00:22:22.509 --> 00:22:24.229
 specific kind of fake news.

507
00:22:24.610 --> 00:22:24.750
Yeah,

508
00:22:24.750 --> 00:22:26.070
 that's exactly the way I see it too.

509
00:22:26.530 --> 00:22:28.551
 It's a very specific example of fake news.

510
00:22:29.471 --> 00:22:33.652
 I think that there are a couple reasons and they're linked to the fake news phenomenon.

511
00:22:34.332 --> 00:22:36.053
 One is just that brains are pretty complicated.

512
00:22:36.353 --> 00:22:39.534
 Most of us have never really been taught anything about brains.

513
00:22:39.794 --> 00:22:43.075
 So you hear a story that sort of explains something that sounds sensible.

514
00:22:43.695 --> 00:22:43.875
 Sure,

515
00:22:44.075 --> 00:22:44.455
 you're happy.

516
00:22:44.455 --> 00:22:44.695
 You know,

517
00:22:44.675 --> 00:22:45.335
 if it's a good story,

518
00:22:45.715 --> 00:22:46.535
 it's easy to process.

519
00:22:46.535 --> 00:22:48.356
 You remember it well and you can then relate it.

520
00:22:48.676 --> 00:22:50.777
 And that's kind of the advantage of stories.

521
00:22:51.677 --> 00:22:52.037
 The problem...

522
00:22:52.317 --> 00:22:54.738
 is that some stories are more damaging than others,

523
00:22:54.938 --> 00:22:55.098
 right?

524
00:22:55.098 --> 00:22:56.459
 And you see this with fake news.

525
00:22:57.299 --> 00:22:58.520
 One of the things that's happening,

526
00:22:59.200 --> 00:22:59.480
 you know,

527
00:22:59.480 --> 00:23:05.043
 right at the moment is there have been these hurricanes in Florida that have caused enormous amounts of damage,

528
00:23:05.103 --> 00:23:05.283
 right?

529
00:23:05.883 --> 00:23:13.506
 And there's a narrative among some people in the United States that the deep state controls the weather and is purposely,

530
00:23:14.267 --> 00:23:14.507
 you know,

531
00:23:14.827 --> 00:23:16.387
 attacking Florida with these things.

532
00:23:17.688 --> 00:23:18.989
 That's a damaging narrative,

533
00:23:19.349 --> 00:23:19.629
 right?

534
00:23:20.249 --> 00:23:22.050
 The fact that the deep state controls the weather,

535
00:23:22.230 --> 00:23:22.850
 that's just goofy.

536
00:23:23.290 --> 00:23:25.751
 But the fact that it's being used against people,

537
00:23:27.671 --> 00:23:35.413
 that's not the kind of story that in a perfect world you'd like to share because it's not true and it has direct influence on many people's lives,

538
00:23:35.453 --> 00:23:36.474
 particularly vulnerable people.

539
00:23:36.774 --> 00:23:36.894
 So,

540
00:23:36.954 --> 00:23:39.814
 I don't think any of this is specific to neuroscience.

541
00:23:39.974 --> 00:23:40.195
 I mean,

542
00:23:40.215 --> 00:23:41.255
 that's the area that I know.

543
00:23:42.075 --> 00:23:49.177
 But the prevalence of stories and their role in our society means that they're really powerful.

544
00:23:49.497 --> 00:23:49.697
 And

545
00:23:50.878 --> 00:23:55.262
 I think it's important that we try to tell stories that are at least based in evidence.

546
00:23:56.983 --> 00:23:59.365
 That doesn't mean that we have to just give people the dry facts,

547
00:23:59.385 --> 00:23:59.505
 right?

548
00:23:59.505 --> 00:24:00.306
 Because that doesn't work.

549
00:24:00.666 --> 00:24:02.688
 It's really boring and nobody remembers.

550
00:24:03.309 --> 00:24:06.471
 You have to make sure that your stories fit the evidence.

551
00:24:07.992 --> 00:24:08.713
 And that's not hard.

552
00:24:08.773 --> 00:24:10.755
 That's a relatively easy thing to do.

553
00:24:11.435 --> 00:24:16.119
 But I think that sometimes the science community gets a little bit messed up and they think,

554
00:24:16.500 --> 00:24:16.620
 no,

555
00:24:17.020 --> 00:24:18.141
 stories are the problem.

556
00:24:19.065 --> 00:24:21.906
 So we're just going to give you the evidence and you can decide for yourself.

557
00:24:22.647 --> 00:24:24.567
 And fair enough.

558
00:24:25.028 --> 00:24:30.050
 But if somebody then comes along with a quick and easy story that contradicts that evidence,

559
00:24:30.410 --> 00:24:31.310
 that's easy to remember.

560
00:24:31.870 --> 00:24:34.511
 Most people will remember the story and forget the evidence.

561
00:24:35.012 --> 00:24:38.133
 And you haven't been very effective in your communication in that case.

562
00:24:39.634 --> 00:24:41.414
So from your perspective,

563
00:24:41.494 --> 00:24:47.777
 what can be done to debunk or prevent the spread of this myth in both?

564
00:24:48.097 --> 00:24:50.639
 educational and professional settings?

565
00:24:52.641 --> 00:24:53.402
Debunking is hard.

566
00:24:54.262 --> 00:24:54.783
 Any question?

567
00:24:54.783 --> 00:24:54.903
 Yeah,

568
00:24:55.063 --> 00:24:55.203
 yeah.

569
00:24:57.025 --> 00:25:02.729
 It's one of the reasons why I think it's so important to tell the stories that are evidence-based,

570
00:25:03.050 --> 00:25:03.250
 right?

571
00:25:03.310 --> 00:25:11.297
 To try to educate people who are busy producing the evidence in not only doing good science or producing this new evidence,

572
00:25:11.777 --> 00:25:14.079
 but in conveying it to a general audience.

573
00:25:14.279 --> 00:25:16.301
 And one of the good ways to do that is...

574
00:25:16.901 --> 00:25:18.382
 developing a good story around it,

575
00:25:18.662 --> 00:25:21.663
 coming up with case studies that illustrate the fundamental principles,

576
00:25:22.123 --> 00:25:24.544
 sharing anecdotes that are actually based in fact,

577
00:25:24.965 --> 00:25:25.685
 as opposed to,

578
00:25:26.265 --> 00:25:26.505
 you know,

579
00:25:26.645 --> 00:25:28.786
 opinion or whatever the case may be.

580
00:25:29.106 --> 00:25:29.226
 So,

581
00:25:29.226 --> 00:25:31.527
 I think that from the scientific community,

582
00:25:32.128 --> 00:25:36.730
 there's an obligation on us to do a better job conveying our information to the world.

583
00:25:37.290 --> 00:25:39.291
 And if all you do is sit around and say,

584
00:25:39.891 --> 00:25:40.011
 oh,

585
00:25:40.271 --> 00:25:40.391
 no,

586
00:25:40.491 --> 00:25:41.051
 that's wrong,

587
00:25:43.212 --> 00:25:44.353
 you'll interest a few people.

588
00:25:44.789 --> 00:25:48.853
 Everybody likes the idea that everything you know is wrong and they can feel clever at dinner parties.

589
00:25:49.273 --> 00:25:53.016
 But I don't think you'll have the sort of widespread sort of benefits that we need.

590
00:25:53.917 --> 00:25:56.399
 The other side that I think is really important is early education.

591
00:25:57.580 --> 00:26:04.526
 And I feel like this is something that we don't necessarily do that great a job of here in the UK or in the US.

592
00:26:05.646 --> 00:26:05.987
 As I said,

593
00:26:06.047 --> 00:26:06.968
 brains are complicated.

594
00:26:07.128 --> 00:26:10.911
 You don't want to take a kid who's eight years old and try to explain brain structure.

595
00:26:11.271 --> 00:26:12.132
 That's a nightmare.

596
00:26:12.792 --> 00:26:13.173
 However.

597
00:26:14.709 --> 00:26:18.292
 All of those kids are experiencing the same things that,

598
00:26:18.692 --> 00:26:18.952
 you know,

599
00:26:19.332 --> 00:26:21.934
 adults are in terms of trying to understand who they are,

600
00:26:22.034 --> 00:26:23.175
 why they think the way they do,

601
00:26:23.455 --> 00:26:24.676
 how they feel the way they do,

602
00:26:25.156 --> 00:26:28.059
 why people are different from them and think differently and feel differently.

603
00:26:28.779 --> 00:26:31.361
 That's a very familiar experience to a kid growing up.

604
00:26:31.881 --> 00:26:35.604
 And we can start to address that from an early age and say,

605
00:26:35.644 --> 00:26:35.784
 look,

606
00:26:36.444 --> 00:26:38.266
 it's not the case that you just have,

607
00:26:38.466 --> 00:26:41.368
 you're a left brain kid and that kid over there is a right brain kid.

608
00:26:42.128 --> 00:26:42.729
 You have different.

609
00:26:42.949 --> 00:26:44.630
 personalities and you have different interests,

610
00:26:44.891 --> 00:26:46.472
 but your brain's actually very,

611
00:26:46.532 --> 00:26:48.033
 very similar between the both of you.

612
00:26:49.114 --> 00:26:54.558
 And what's different are your personality and things like your life experiences.

613
00:26:54.838 --> 00:26:56.540
 And I think that by understanding those things,

614
00:26:56.640 --> 00:27:06.067
 you're actually going to try to promote a more critical thinking in kids as they grow up and sort of seed the correct stories from the beginning.

615
00:27:06.583 --> 00:27:08.945
 If you're answering questions that they're wondering about,

616
00:27:09.506 --> 00:27:09.986
 they care.

617
00:27:10.667 --> 00:27:14.630
 If you're trying to give them facts about numbers of brain cells or something like that,

618
00:27:15.190 --> 00:27:15.431
 man,

619
00:27:15.471 --> 00:27:16.091
 they don't care.

620
00:27:17.032 --> 00:27:18.693
Good advice for eight-year-olds and adults,

621
00:27:18.733 --> 00:27:19.054
 I think.

622
00:27:20.094 --> 00:27:20.215
 So,

623
00:27:20.575 --> 00:27:20.815
 Joe,

624
00:27:20.815 --> 00:27:21.436
 in our audience,

625
00:27:21.436 --> 00:27:23.677
 we have a lot of business leaders and professionals,

626
00:27:23.757 --> 00:27:29.182
 and I know that part of your work is to help leaders apply learnings from neuroscience in specific areas.

627
00:27:30.535 --> 00:27:31.875
 So I know in recent years,

628
00:27:31.915 --> 00:27:34.996
 you've explored the connection between neuroscience and education,

629
00:27:35.076 --> 00:27:36.737
 as you were just talking about a little bit.

630
00:27:37.437 --> 00:27:44.899
 Can you talk more about how you think your work on language processing specifically can inform teaching methods and how we approach learning?

631
00:27:46.060 --> 00:27:46.180
Yeah,

632
00:27:46.220 --> 00:27:48.340
 I think this is an area that's changing.

633
00:27:48.641 --> 00:27:50.041
 Certainly in higher education,

634
00:27:50.201 --> 00:27:50.461
 for me,

635
00:27:50.561 --> 00:27:52.802
 it's been changing over the last 10-15 years.

636
00:27:53.622 --> 00:27:56.543
 The old school model was that you just kind of

637
00:27:57.031 --> 00:27:58.312
 talked at students.

638
00:27:58.372 --> 00:27:59.612
 You gave them the information,

639
00:27:59.652 --> 00:28:02.233
 you had some slides or in the old days,

640
00:28:02.233 --> 00:28:06.515
 you wrote on a blackboard and they copied everything down and then sort of went away and thought about it.

641
00:28:07.555 --> 00:28:09.736
 And I think that that is a very limited model.

642
00:28:10.016 --> 00:28:11.537
 It works to some extent.

643
00:28:12.477 --> 00:28:12.797
 We all,

644
00:28:13.598 --> 00:28:13.738
 well,

645
00:28:13.998 --> 00:28:14.738
 I'm older than you guys,

646
00:28:14.738 --> 00:28:16.059
 so maybe it was just for me.

647
00:28:16.319 --> 00:28:17.739
 But nonetheless,

648
00:28:19.460 --> 00:28:23.342
 there's a lot more opportunity to engage and make learning an active process.

649
00:28:23.942 --> 00:28:26.123
 And one way to do that is to...

650
00:28:26.483 --> 00:28:35.809
 intersperse the kind of learning that you're just providing in terms of lecture material or whatever with more interactive sessions where they have question and answer periods,

651
00:28:35.869 --> 00:28:37.571
 they're doing interactive quizzes,

652
00:28:38.551 --> 00:28:46.296
 even quizzes that don't count towards your final mark because that leads to a lot of anxiety for many people.

653
00:28:47.137 --> 00:28:52.501
 Have an important role in consolidating the information that you're learning and help people learn more quickly and more effectively.

654
00:28:53.281 --> 00:28:53.401
 So,

655
00:28:53.401 --> 00:28:55.663
 I feel like there's a lot of good neuroscience out there.

656
00:28:56.079 --> 00:29:00.761
 That's suggesting ways of enhancing the teaching methods that we currently have.

657
00:29:01.401 --> 00:29:05.663
 And very much the same from early kid education,

658
00:29:06.043 --> 00:29:06.624
 kindergarten,

659
00:29:06.764 --> 00:29:07.444
 five-year-olds,

660
00:29:07.564 --> 00:29:09.865
 all the way through higher education like universities.

661
00:29:10.585 --> 00:29:14.267
 And those are really important.

662
00:29:14.627 --> 00:29:19.469
 The other thing that comes up here is related to this myth of learning styles,

663
00:29:19.549 --> 00:29:19.729
 right?

664
00:29:19.769 --> 00:29:19.890
 So,

665
00:29:20.510 --> 00:29:21.810
 for anybody who's not familiar,

666
00:29:21.930 --> 00:29:22.951
 there's this idea that...

667
00:29:23.479 --> 00:29:24.960
 Some people are visual learners,

668
00:29:25.341 --> 00:29:26.622
 some people are auditory learners,

669
00:29:26.682 --> 00:29:28.243
 some people might be kinesthetic learners,

670
00:29:28.303 --> 00:29:30.205
 meaning that they're more with their hands and touching.

671
00:29:31.326 --> 00:29:31.986
 And to some extent,

672
00:29:32.026 --> 00:29:36.810
 this is really appealing because everybody knows somebody who learns differently than them.

673
00:29:37.371 --> 00:29:37.971
 That happens.

674
00:29:38.091 --> 00:29:41.394
 And all of us have a sense of what they prefer when they're learning.

675
00:29:42.155 --> 00:29:44.937
 The problem is that whenever we've actually gone and tested this,

676
00:29:45.738 --> 00:29:47.279
 it turns out to just be false.

677
00:29:47.299 --> 00:29:52.163
 If you just give people information in the form that they most prefer it.

678
00:29:52.715 --> 00:29:55.898
 They learn the information less well than if you give it to them in multiple forms.

679
00:29:56.438 --> 00:29:58.180
 And when we look at what's happening in your brain,

680
00:29:58.640 --> 00:30:02.943
 this makes a great deal of sense because when you sort of combine sensory modalities,

681
00:30:03.384 --> 00:30:03.784
 vision,

682
00:30:04.044 --> 00:30:04.445
 hearing,

683
00:30:04.585 --> 00:30:04.925
 touch,

684
00:30:05.025 --> 00:30:05.165
 etc.,

685
00:30:05.886 --> 00:30:08.168
 you get a much deeper processing of the information.

686
00:30:08.208 --> 00:30:10.029
 It gets encoded in memory more deeply.

687
00:30:10.850 --> 00:30:10.970
 So,

688
00:30:11.591 --> 00:30:15.934
 you definitely wouldn't want to just limit learning to individual styles.

689
00:30:16.394 --> 00:30:20.198
 You really want to constantly integrate all of them as much as possible.

690
00:30:20.458 --> 00:30:21.779
 And these are the things that I think are...

691
00:30:22.243 --> 00:30:22.483
 you know,

692
00:30:22.663 --> 00:30:23.823
 really prevalent in education.

693
00:30:24.104 --> 00:30:26.444
 And these are positive changes that are happening.

694
00:30:27.445 --> 00:30:27.645
Yeah.

695
00:30:27.745 --> 00:30:28.865
 So more myth busting,

696
00:30:29.045 --> 00:30:30.065
 learning styles,

697
00:30:30.165 --> 00:30:32.106
 not a thing for those who are listening,

698
00:30:32.146 --> 00:30:33.106
 just to reiterate.

699
00:30:33.926 --> 00:30:38.328
 So another area you've recently been focusing on is advertising effectiveness,

700
00:30:38.668 --> 00:30:42.729
 examining how neuroscience can help us better understand what makes an ad successful.

701
00:30:43.409 --> 00:30:49.151
 So can you talk about the key insights your research has uncovered in terms of what drives consumer engagement with ads?

702
00:30:49.603 --> 00:30:49.803
Yeah,

703
00:30:49.943 --> 00:30:50.183
 sure.

704
00:30:50.283 --> 00:30:53.444
 This is a really interesting area for me because a colleague,

705
00:30:53.484 --> 00:30:54.184
 Daniel Richardson,

706
00:30:54.204 --> 00:30:59.446
 and I have developed a method for trying to measure audience engagement non-invasively,

707
00:30:59.506 --> 00:31:00.806
 like without asking people.

708
00:31:01.686 --> 00:31:04.827
 And we've tested lots of different creative content,

709
00:31:05.027 --> 00:31:05.688
 TV shows,

710
00:31:05.828 --> 00:31:06.108
 ads,

711
00:31:06.168 --> 00:31:06.768
 movie trailers,

712
00:31:06.788 --> 00:31:07.188
 et cetera.

713
00:31:08.548 --> 00:31:12.469
 And one of the things that we find is that for advertisements,

714
00:31:12.629 --> 00:31:16.130
 the thing that drives engagement the most is a good narrative.

715
00:31:16.711 --> 00:31:16.831
 Now,

716
00:31:16.831 --> 00:31:17.971
 that's not to say that

717
00:31:18.151 --> 00:31:19.571
 all ads need a narrative.

718
00:31:19.651 --> 00:31:21.032
 It serves different purposes.

719
00:31:21.252 --> 00:31:23.233
 Like some ads are just purely informational.

720
00:31:23.533 --> 00:31:23.693
 Hey,

721
00:31:23.993 --> 00:31:25.933
 this week there's a sale on at the grocery store,

722
00:31:26.313 --> 00:31:28.174
 get over why you can take advantage of it.

723
00:31:28.814 --> 00:31:31.075
 There's no real narrative to that and that's fine.

724
00:31:31.115 --> 00:31:32.375
 It doesn't need one.

725
00:31:33.075 --> 00:31:36.496
 But for things that are intended to develop brand awareness,

726
00:31:36.556 --> 00:31:37.457
 brand consideration,

727
00:31:37.557 --> 00:31:38.197
 things like that,

728
00:31:39.037 --> 00:31:42.018
 then you do see a real value in the narrative.

729
00:31:42.018 --> 00:31:44.839
 And that seems to be the biggest single factor.

730
00:31:45.119 --> 00:31:47.140
 It doesn't have to be any particular kind of narrative.

731
00:31:47.140 --> 00:31:48.621
 It just has to be an interesting one.

732
00:31:49.841 --> 00:31:52.962
 And interesting in this case means it's got to have an emotional connection.

733
00:31:53.743 --> 00:31:55.644
 It doesn't have to be positive,

734
00:31:55.944 --> 00:31:57.044
 laughing kind of emotion.

735
00:31:57.164 --> 00:32:02.106
 Sometimes the right emotions are sort of darker or more introspective kind of things.

736
00:32:02.987 --> 00:32:04.608
 Sometimes a combination works very well.

737
00:32:05.028 --> 00:32:09.149
 But if you don't engage any kind of emotional response from your audience,

738
00:32:09.810 --> 00:32:10.050
 then...

739
00:32:10.818 --> 00:32:12.759
 the narrative doesn't tend to land with them.

740
00:32:15.139 --> 00:32:15.699
 Having said that,

741
00:32:16.139 --> 00:32:17.460
 there are other things that influence it.

742
00:32:17.560 --> 00:32:20.001
 So we can measure the effect of the soundtrack.

743
00:32:20.301 --> 00:32:22.641
 Like above and beyond the sort of spoken component,

744
00:32:23.061 --> 00:32:28.803
 you can then just layer on music and you can see the effect that that has an increasing engagement.

745
00:32:29.083 --> 00:32:29.343
 You know,

746
00:32:29.323 --> 00:32:31.084
 an appropriate music track can,

747
00:32:31.764 --> 00:32:31.904
 well,

748
00:32:31.924 --> 00:32:32.764
 in our data,

749
00:32:33.604 --> 00:32:35.745
 increase engagement levels by about 4%,

750
00:32:36.185 --> 00:32:37.205
 which doesn't sound like a lot,

751
00:32:37.365 --> 00:32:40.126
 but if you're having massive reach with your ad,

752
00:32:40.550 --> 00:32:42.992
 then it could be really significant.

753
00:32:45.194 --> 00:32:48.136
 Getting your themes right of your story makes a big difference too.

754
00:32:48.737 --> 00:32:51.959
 So we did some work with an energy company here in the UK,

755
00:32:52.720 --> 00:32:58.224
 and they had these two ads that they were putting out where they were brand consideration kind of ads,

756
00:32:58.265 --> 00:32:58.785
 brand building.

757
00:32:59.405 --> 00:33:00.526
 And one was around,

758
00:33:00.787 --> 00:33:01.007
 well,

759
00:33:01.247 --> 00:33:04.370
 they're the biggest green energy source in the country.

760
00:33:04.830 --> 00:33:07.832
 And one was around using smart meters and basically saving you money.

761
00:33:08.153 --> 00:33:09.594
 And their sort of intuition was,

762
00:33:09.998 --> 00:33:10.198
 Well,

763
00:33:10.638 --> 00:33:13.479
 saving you money has direct influence on your pocketbook.

764
00:33:13.500 --> 00:33:13.940
 Of course,

765
00:33:14.260 --> 00:33:15.820
 that's going to be the ad that's going to do better.

766
00:33:16.401 --> 00:33:18.762
 But what was really interesting was it wasn't.

767
00:33:19.162 --> 00:33:22.123
 The ad that produced the greater engagement was this idea that,

768
00:33:22.223 --> 00:33:22.343
 oh,

769
00:33:22.383 --> 00:33:26.745
 this is a company that's getting like 80% of their energy from renewable sources.

770
00:33:27.845 --> 00:33:27.966
 So,

771
00:33:28.046 --> 00:33:30.627
 more than I can save £3.50 a week.

772
00:33:31.447 --> 00:33:38.510
 I was interested in the idea that maybe this is reliably environmentally sourced energy and that I can...

773
00:33:38.690 --> 00:33:44.193
 contribute a little bit and feel better about my green credentials by using them as a supplier.

774
00:33:44.733 --> 00:33:44.853
 So,

775
00:33:45.493 --> 00:33:45.753
 you know,

776
00:33:46.013 --> 00:33:48.134
 getting those themes right makes a big difference.

777
00:33:48.134 --> 00:33:48.475
 And of course,

778
00:33:48.495 --> 00:33:50.656
 that means understanding who your audience are,

779
00:33:50.776 --> 00:33:51.336
 what they want,

780
00:33:51.396 --> 00:33:52.236
 what they're looking for,

781
00:33:52.517 --> 00:33:55.038
 which is what traditional market research is really,

782
00:33:55.618 --> 00:33:55.858
 you know,

783
00:33:55.898 --> 00:33:56.478
 a lot about.

784
00:33:57.279 --> 00:33:57.439
Yeah.

785
00:33:57.539 --> 00:33:57.659
 So,

786
00:33:57.679 --> 00:34:01.601
 it sounds like brands should be focusing on narrative,

787
00:34:01.721 --> 00:34:02.241
 emotion,

788
00:34:02.441 --> 00:34:03.782
 perhaps music and

789
00:34:04.390 --> 00:34:07.373
 Getting the right themes to create more impactful content.

790
00:34:07.413 --> 00:34:12.677
 Is there anything else that you would give advice about when the world's getting more and more sophisticated with its marketing?

791
00:34:13.638 --> 00:34:13.838
Well,

792
00:34:14.059 --> 00:34:17.141
 the other thing that makes a difference is standing out from your competitors.

793
00:34:18.042 --> 00:34:18.642
 And of course,

794
00:34:19.023 --> 00:34:20.584
 different companies do this in different ways.

795
00:34:20.644 --> 00:34:22.145
 Sometimes they use humor for this.

796
00:34:22.266 --> 00:34:28.931
 Sometimes they just simply do things that are a little bit weird with the idea that,

797
00:34:28.931 --> 00:34:29.171
 you know,

798
00:34:29.252 --> 00:34:30.513
 all attention is good attention.

799
00:34:32.454 --> 00:34:33.274
 But it makes a difference,

800
00:34:33.334 --> 00:34:33.454
 right?

801
00:34:33.474 --> 00:34:34.895
 If everything is very samey,

802
00:34:35.275 --> 00:34:39.477
 it's really hard to remember the content as related to this brand or that brand.

803
00:34:40.077 --> 00:34:43.258
 And not to call anybody out,

804
00:34:43.338 --> 00:34:44.899
 but car ads are very,

805
00:34:44.999 --> 00:34:46.620
 very similar to one another in general,

806
00:34:46.700 --> 00:34:46.960
 right?

807
00:34:46.980 --> 00:34:51.862
 There's a drone shot of a car going through some dramatic landscape and then another dramatic landscape.

808
00:34:52.762 --> 00:34:56.964
 And it's very difficult to remember which car company we're actually talking about.

809
00:34:57.084 --> 00:35:01.986
 So some of these companies that are actually doing things that are a little bit different make it stand out.

810
00:35:02.166 --> 00:35:02.846
 a little bit too,

811
00:35:03.106 --> 00:35:03.347
 you know,

812
00:35:03.387 --> 00:35:03.607
 again,

813
00:35:03.667 --> 00:35:10.369
 within the context of having a good narrative and making sure that the themes that you're pushing are the things that your consumers are actually interested in.

814
00:35:11.210 --> 00:35:11.750
Absolutely.

815
00:35:12.050 --> 00:35:15.011
 And you talked about measuring in non-invasive ways,

816
00:35:15.151 --> 00:35:20.353
 but there are also neuroscience tools like fMRI that can also measure the brain's response to advertising.

817
00:35:20.754 --> 00:35:24.695
 How do you think those findings should be used and will influence the future of marketing?

818
00:35:25.896 --> 00:35:26.416
Yeah,

819
00:35:26.416 --> 00:35:31.418
 I've done some of those studies and they're really interesting.

820
00:35:32.390 --> 00:35:38.894
 In the sense that I think that a lot of these companies are exploring opportunities to try different things.

821
00:35:40.255 --> 00:35:45.378
 And they try these experiments and then they measure return on investment.

822
00:35:45.378 --> 00:35:46.878
 They measure brand awareness and things like that.

823
00:35:46.878 --> 00:35:46.998
 So,

824
00:35:46.978 --> 00:35:49.480
 they have a feel for whether it works or it doesn't work.

825
00:35:49.960 --> 00:35:53.542
 What fMRI can bring to that is an understanding of why.

826
00:35:53.842 --> 00:35:59.305
 Like how is it landing in the consumer brain and what are the influences that it's instilling?

827
00:35:59.786 --> 00:35:59.906
 So,

828
00:35:59.946 --> 00:36:00.486
 for instance...

829
00:36:00.686 --> 00:36:05.389
 we did some work with a company called Finecast on addressable advertising,

830
00:36:05.429 --> 00:36:06.469
 addressable TV ads,

831
00:36:06.549 --> 00:36:09.171
 which are basically ads that are relevant to you as a consumer,

832
00:36:09.451 --> 00:36:10.972
 as opposed to ads that aren't.

833
00:36:11.712 --> 00:36:18.516
 And one of the things we know is we can identify brain systems that are involved in like emotion and attention and memory and things like that.

834
00:36:18.796 --> 00:36:24.459
 So we can measure how that activity changes when you're viewing relevant ads versus irrelevant ads.

835
00:36:25.019 --> 00:36:29.622
 So we didn't discover that addressable advertising was effective.

836
00:36:30.142 --> 00:36:31.243
 The industry already knew that.

837
00:36:31.383 --> 00:36:34.305
 What we could do is sort of provide a little information about why,

838
00:36:34.385 --> 00:36:35.465
 what difference does it make?

839
00:36:35.485 --> 00:36:41.609
 And it was particularly enhancing sort of the emotional engagement and the memorability of the ads,

840
00:36:42.250 --> 00:36:47.433
 which obviously is an important aspect of a successful ad from what we just talked about.

841
00:36:48.013 --> 00:36:54.237
 But we could then see the evidence for this play out in consumer minds and literally in their brains in this case.

842
00:36:54.758 --> 00:36:58.200
 So I think that fMRI can sometimes answer why questions.

843
00:36:58.632 --> 00:37:07.217
 And knowing why can then help you make informed decisions about how to implement those aspects in your ad campaigns or in your marketing.

844
00:37:08.677 --> 00:37:08.978
Maybe,

845
00:37:09.118 --> 00:37:09.358
 Joe,

846
00:37:09.418 --> 00:37:13.100
 now we are still speaking about communication,

847
00:37:13.260 --> 00:37:15.761
 but leadership communication.

848
00:37:16.282 --> 00:37:27.968
 And I would like to have your perspective on how can leaders use the insight from your research on language processing to communicate more effectively?

849
00:37:28.488 --> 00:37:29.448
 with their teams.

850
00:37:31.589 --> 00:37:33.129
Another fun topic,

851
00:37:33.249 --> 00:37:34.230
 because it's such a big one.

852
00:37:35.310 --> 00:37:38.431
 There's some interesting parallels here with effective education.

853
00:37:39.551 --> 00:37:40.491
 Part of it is,

854
00:37:41.652 --> 00:37:41.892
 you know,

855
00:37:42.712 --> 00:37:45.433
 communication is fundamentally a two-way process.

856
00:37:45.993 --> 00:37:52.074
 It's not me as a leader conveying information to you as the followers or my team members or things like that.

857
00:37:52.494 --> 00:37:54.855
 It actually needs to be bi-directional.

858
00:37:55.455 --> 00:37:56.836
 And as part of that,

859
00:37:57.676 --> 00:37:57.916
 you know,

860
00:37:58.156 --> 00:37:59.436
 leaders need to not only speak,

861
00:37:59.456 --> 00:38:00.217
 but they need to listen.

862
00:38:00.537 --> 00:38:04.078
 And the listening part is at least as important as the sharing,

863
00:38:04.138 --> 00:38:08.619
 because it gives you an opportunity to understand where your team members are,

864
00:38:08.719 --> 00:38:09.539
 where they're coming from,

865
00:38:10.760 --> 00:38:11.940
 what their concerns are,

866
00:38:12.380 --> 00:38:15.141
 and allows you to sort of customize your message to your audience,

867
00:38:15.301 --> 00:38:16.201
 which is a big deal.

868
00:38:16.581 --> 00:38:19.222
 Because one thing that we know is as you make things more relevant,

869
00:38:19.482 --> 00:38:20.622
 people find it more engaging,

870
00:38:20.902 --> 00:38:21.863
 they remember it better,

871
00:38:22.203 --> 00:38:23.403
 they listen more closely.

872
00:38:25.124 --> 00:38:25.244
 So...

873
00:38:26.528 --> 00:38:29.450
 I think the best leaders know all this implicitly.

874
00:38:29.490 --> 00:38:32.652
 I think that these are people who are already doing all these things.

875
00:38:32.813 --> 00:38:33.993
 They may not be able to say,

876
00:38:34.093 --> 00:38:34.234
 well,

877
00:38:34.294 --> 00:38:36.615
 this is the neuroscience behind why I do it,

878
00:38:37.216 --> 00:38:39.998
 but they've seen its effectiveness in their teams,

879
00:38:39.998 --> 00:38:40.698
 in their companies,

880
00:38:40.698 --> 00:38:41.719
 in their organizations,

881
00:38:42.299 --> 00:38:47.143
 and they have tailored their communication style with that in mind.

882
00:38:49.528 --> 00:38:51.390
 Simple things that sort of everybody knows,

883
00:38:51.390 --> 00:38:51.650
 you know,

884
00:38:51.830 --> 00:38:54.973
 you can make your slides better and less noisy and all the rest of that.

885
00:38:55.213 --> 00:38:56.995
 And there's some good neuroscience behind those things.

886
00:38:57.695 --> 00:39:02.319
 But I think that's less interesting than the fact that communication is two way.

887
00:39:02.880 --> 00:39:07.884
 And that's an important part of leading is not only sharing your vision,

888
00:39:08.604 --> 00:39:10.506
 but getting people on board to follow with.

889
00:39:12.408 --> 00:39:13.609
There is something which is,

890
00:39:14.169 --> 00:39:14.570
 I think,

891
00:39:14.570 --> 00:39:17.192
 a fascinating mechanism.

892
00:39:18.757 --> 00:39:26.403
 which is about how shared language can align brain activity between speakers and listeners.

893
00:39:26.903 --> 00:39:33.769
 So could you explain how this finding might help leaders foster better understanding,

894
00:39:34.069 --> 00:39:37.032
 better collaboration within their organization?

895
00:39:37.752 --> 00:39:37.872
Yeah,

896
00:39:37.933 --> 00:39:40.975
 this actually brings together some of the things we've been talking about,

897
00:39:41.956 --> 00:39:45.579
 in that there's a kind of embodied cognition aspect to it,

898
00:39:45.739 --> 00:39:46.399
 and then there's...

899
00:39:47.528 --> 00:39:48.249
 And there's,

900
00:39:48.589 --> 00:39:48.749
 yeah,

901
00:39:48.789 --> 00:39:49.649
 there's an engagement part.

902
00:39:50.070 --> 00:39:50.190
 So,

903
00:39:50.230 --> 00:39:51.871
 there's some interesting studies that just say,

904
00:39:53.192 --> 00:39:59.456
 there's one that asked a young woman to tell a story of an event in her life and they had her in a brain scanner,

905
00:39:59.496 --> 00:40:00.517
 recorded her brain activity.

906
00:40:01.097 --> 00:40:08.042
 And what they did was they got 15 volunteers to come in to the brain scanner and then listen to her story while their brains were being scanned.

907
00:40:08.342 --> 00:40:13.866
 And what was fascinating was that there was incredible alignment in the pattern of activation in the speaker,

908
00:40:14.866 --> 00:40:15.207
 excuse me,

909
00:40:15.227 --> 00:40:16.087
 and in the listeners.

910
00:40:16.768 --> 00:40:16.888
 So...

911
00:40:17.608 --> 00:40:19.550
 When she was talking about visual events,

912
00:40:19.610 --> 00:40:21.851
 you'd see bits of her visual cortex light up.

913
00:40:22.151 --> 00:40:24.553
 And this is what I mean by this kind of embodied experience.

914
00:40:25.354 --> 00:40:30.237
 You actually have sensory cortices activating without any particular sight,

915
00:40:30.417 --> 00:40:36.381
 like lying in an MRI scanner is the least visually exciting thing you can do short of being sound asleep.

916
00:40:38.122 --> 00:40:38.883
 But nonetheless,

917
00:40:39.063 --> 00:40:44.006
 just hearing language about this kind of vision or whatever activates those part of your brain.

918
00:40:44.006 --> 00:40:46.488
 And so it seems like what happens in the...

919
00:40:46.688 --> 00:40:51.211
 audience is their brain is kind of simulating the experience of the person who's speaking.

920
00:40:51.671 --> 00:40:56.135
 And your ability to do that depends very much on your experience,

921
00:40:56.135 --> 00:40:57.455
 your alignment with that person.

922
00:40:57.876 --> 00:40:57.996
 So,

923
00:40:58.536 --> 00:41:00.758
 if you started telling me about,

924
00:41:00.958 --> 00:41:01.218
 you know,

925
00:41:02.379 --> 00:41:06.982
 physics or French tax law or something,

926
00:41:07.502 --> 00:41:09.764
 I just don't know enough to really engage.

927
00:41:09.864 --> 00:41:11.905
 But as soon as we start talking behavioral science,

928
00:41:12.486 --> 00:41:12.806
 I'm there,

929
00:41:12.926 --> 00:41:13.106
 right?

930
00:41:13.126 --> 00:41:13.346
 I mean,

931
00:41:13.346 --> 00:41:15.768
 I've heard you speak about it and just...

932
00:41:15.888 --> 00:41:18.369
 been really excited and follow along.

933
00:41:18.630 --> 00:41:20.791
 And that's due to this kind of alignment issue.

934
00:41:20.891 --> 00:41:21.011
 So,

935
00:41:21.471 --> 00:41:24.753
 I think that when leaders are trying to use this,

936
00:41:25.093 --> 00:41:27.915
 they need to make sure that they understand where their audience is coming from.

937
00:41:27.955 --> 00:41:28.975
 What are their concerns?

938
00:41:29.075 --> 00:41:30.576
 Are you speaking to those concerns?

939
00:41:30.596 --> 00:41:35.359
 And are you making it accessible in a way that they can understand and empathize with?

940
00:41:35.699 --> 00:41:36.920
 Because as soon as you do that,

941
00:41:37.300 --> 00:41:44.404
 you get this kind of alignment in sort of the brain activity that leads to sort of alignment and intention and planning.

942
00:41:46.140 --> 00:41:50.424
There is another very important concept in neuroscience,

943
00:41:50.444 --> 00:41:53.946
 but I think it is exactly the same in behavioral science,

944
00:41:54.267 --> 00:41:57.389
 which is the importance of context.

945
00:41:57.869 --> 00:41:58.910
 And here for you,

946
00:41:59.931 --> 00:42:03.193
 the importance of context is understanding language.

947
00:42:03.514 --> 00:42:11.580
 So how can leaders apply this idea when making complex decisions or delivering messages to?

948
00:42:12.256 --> 00:42:13.717
 diverse teams.

949
00:42:14.657 --> 00:42:17.398
I think the key there may be the diverse teams.

950
00:42:17.978 --> 00:42:24.881
 The fact that they're different from one another means that they probably have slightly different issues and concerns for them.

951
00:42:25.522 --> 00:42:25.642
 So,

952
00:42:26.922 --> 00:42:32.284
 knowing what those are and then tailoring your message to fit their interests,

953
00:42:32.304 --> 00:42:33.965
 their concerns makes a big difference.

954
00:42:33.965 --> 00:42:34.085
 So,

955
00:42:34.445 --> 00:42:36.386
 the theme of the message may be exactly the same,

956
00:42:36.906 --> 00:42:39.808
 but by making it directly relevant to your audience,

957
00:42:40.388 --> 00:42:40.528
 you

958
00:42:41.228 --> 00:42:42.508
 engage them in a deeper manner.

959
00:42:43.509 --> 00:42:58.353
 One sort of simple example of this is there's a bank company here in the UK that does investing and they tailor the messages to their investors based on their own,

960
00:42:58.573 --> 00:42:59.853
 the investor's personalities.

961
00:43:00.233 --> 00:43:03.614
 So they are essentially showing exactly the same information,

962
00:43:03.674 --> 00:43:09.236
 but the way they frame it depends on your personal scores on a series of personality measures.

963
00:43:09.536 --> 00:43:10.497
 Your risk tolerance,

964
00:43:10.537 --> 00:43:11.377
 your extroversion,

965
00:43:11.437 --> 00:43:12.057
 introversion,

966
00:43:12.157 --> 00:43:14.979
 your interest in new ideas,

967
00:43:15.479 --> 00:43:17.220
 openness to that versus tradition,

968
00:43:17.260 --> 00:43:17.400
 etc.

969
00:43:18.181 --> 00:43:18.801
 And what they found,

970
00:43:19.001 --> 00:43:19.522
 for instance,

971
00:43:19.542 --> 00:43:23.144
 during the COVID lockdown that happened,

972
00:43:23.464 --> 00:43:26.405
 the basic advice to investors was hold the fort for the moment,

973
00:43:26.485 --> 00:43:26.646
 right?

974
00:43:26.666 --> 00:43:30.928
 There's a lot of uncertainty and your best bet here is to just sort of ride things out.

975
00:43:31.768 --> 00:43:33.890
 But if you're a very high risk tolerance,

976
00:43:34.930 --> 00:43:37.992
 you're going to hear that message differently than if you're very low risk tolerance.

977
00:43:38.172 --> 00:43:39.993
 So what they did was they just tailored it different.

978
00:43:40.053 --> 00:43:42.913
 So they would say to the low-risk people,

979
00:43:43.454 --> 00:43:44.874
 this is a really risky environment,

980
00:43:45.074 --> 00:43:49.455
 and the safest course by far is essentially keeping the investments as they are.

981
00:43:49.755 --> 00:43:52.436
 It's unlikely to be bad in the long run,

982
00:43:52.576 --> 00:43:55.097
 as long as you don't need to do anything right the second,

983
00:43:55.277 --> 00:43:55.697
 hold the fort.

984
00:43:56.337 --> 00:43:57.338
 For the high-risk people,

985
00:43:57.758 --> 00:43:58.858
 they said the same message,

986
00:43:58.898 --> 00:44:00.099
 but they said it entirely differently.

987
00:44:00.199 --> 00:44:00.559
 They said,

988
00:44:00.639 --> 00:44:00.799
 right,

989
00:44:01.159 --> 00:44:02.619
 tons of volatility in the market.

990
00:44:02.839 --> 00:44:04.620
 There's a real chance that you could-

991
00:44:04.864 --> 00:44:05.144
 gain,

992
00:44:05.264 --> 00:44:09.048
 but the volatility means that there's at least an equal chance that you're going to lose.

993
00:44:09.408 --> 00:44:15.693
 Your best course through this is to just stay with what you're doing right now and take advantage once the trends become clearer.

994
00:44:15.953 --> 00:44:16.073
 So,

995
00:44:16.113 --> 00:44:17.595
 the message is the exact same,

996
00:44:17.695 --> 00:44:20.497
 but the way you tailor it to your audience makes a big difference.

997
00:44:20.957 --> 00:44:31.846
 And their experience has been that the investors are much happier with the advice and they feel like they understand the advice better since they've adopted this kind of personalization message.

998
00:44:33.087 --> 00:44:33.228
Yeah,

999
00:44:33.388 --> 00:44:33.608
 great.

1000
00:44:35.012 --> 00:44:35.673
 You have also,

1001
00:44:36.633 --> 00:44:37.033
 I think,

1002
00:44:37.113 --> 00:44:39.814
 strong interest in neuroplasticity.

1003
00:44:40.535 --> 00:44:47.638
 So what strategy would you recommend for leaders who want to cultivate something which I think is very important,

1004
00:44:47.838 --> 00:44:51.540
 adaptive thinking and learning within their organization?

1005
00:44:52.580 --> 00:44:59.103
One of the things that I'm really impressed by are organizations that try to promote a growth mindset.

1006
00:44:59.243 --> 00:45:01.144
 So one of their values is...

1007
00:45:01.424 --> 00:45:04.325
 This idea that we're all always learning and we're on a journey.

1008
00:45:04.685 --> 00:45:07.726
 So you may be incredibly successful in whatever you do,

1009
00:45:08.346 --> 00:45:11.807
 but there's still an opportunity to be more successful and to keep learning.

1010
00:45:11.907 --> 00:45:12.387
 And in fact,

1011
00:45:12.687 --> 00:45:14.688
 the most successful organizations,

1012
00:45:14.728 --> 00:45:15.028
 teams,

1013
00:45:15.048 --> 00:45:17.048
 and individuals are precisely those people.

1014
00:45:18.069 --> 00:45:18.829
 It's a hard process.

1015
00:45:20.489 --> 00:45:23.930
 So if one of the values that they really promote is feedback,

1016
00:45:24.390 --> 00:45:26.331
 getting feedback from clients,

1017
00:45:26.391 --> 00:45:28.471
 getting feedback from your manager,

1018
00:45:28.651 --> 00:45:29.212
 your team,

1019
00:45:29.292 --> 00:45:30.552
 or the people that you lead.

1020
00:45:31.248 --> 00:45:31.448
 Um,

1021
00:45:31.909 --> 00:45:33.170
 that's a big deal,

1022
00:45:33.410 --> 00:45:33.610
 right?

1023
00:45:33.650 --> 00:45:35.271
 Because for a lot of us,

1024
00:45:35.392 --> 00:45:36.893
 feedback is incredibly threatening.

1025
00:45:37.133 --> 00:45:39.495
 You just don't want to be told all the things that you're not very good at.

1026
00:45:39.775 --> 00:45:40.356
 Um,

1027
00:45:40.676 --> 00:45:43.178
 I certainly feel that way every time I get feedback on a paper.

1028
00:45:43.578 --> 00:45:44.079
 Um,

1029
00:45:44.999 --> 00:45:48.162
 but it's an important way to continue your growth process.

1030
00:45:48.282 --> 00:45:51.845
 And if it's a value that the company sort of supports and promotes,

1031
00:45:52.225 --> 00:45:54.947
 then it doesn't have to be threatening if it's done on a regular basis.

1032
00:45:55.488 --> 00:45:57.169
 There's a strong emotional response to,

1033
00:45:57.169 --> 00:45:57.910
 uh,

1034
00:45:57.910 --> 00:45:58.290
 feedback,

1035
00:45:58.350 --> 00:45:59.391
 both positive and negative.

1036
00:45:59.691 --> 00:46:00.292
 And these have.

1037
00:46:00.876 --> 00:46:06.619
 potential to benefit growth mindsets in your employees and in your senior management team.

1038
00:46:07.339 --> 00:46:07.939
 So for me,

1039
00:46:08.019 --> 00:46:17.104
 I think that's one of the core issues that leaders face is how do you try to ensure that growth mindset and promote it within your organization?

1040
00:46:18.304 --> 00:46:18.764
So Joe,

1041
00:46:18.785 --> 00:46:25.828
 we've talked about some of your research on understanding how neuroscience can be applied to education and organizational development.

1042
00:46:26.516 --> 00:46:31.857
 What future developments in neuroscience do you think will have the biggest impact on leadership and learning?

1043
00:46:32.938 --> 00:46:33.138
Wow,

1044
00:46:33.578 --> 00:46:35.298
 future neuroscience.

1045
00:46:36.619 --> 00:46:37.939
 So in the short term,

1046
00:46:39.340 --> 00:46:42.360
 the prevalence of these kind of wearable biometric sensors,

1047
00:46:42.740 --> 00:46:43.321
 Apple Watch,

1048
00:46:43.461 --> 00:46:44.141
 Samsung Watch,

1049
00:46:44.281 --> 00:46:44.621
 Fitbit,

1050
00:46:44.681 --> 00:46:45.361
 those kind of things,

1051
00:46:45.941 --> 00:46:48.322
 actually does offer some interesting potential.

1052
00:46:48.582 --> 00:46:50.022
 So for years,

1053
00:46:50.463 --> 00:46:52.523
 you couldn't really get access to the data,

1054
00:46:52.743 --> 00:46:55.304
 but Apple has now provided an API so that...

1055
00:46:55.704 --> 00:47:12.620
 you can and if people choose to opt in you get this kind of real-time sense of the physiology of for instance your team right um and you can measure for instance levels of arousal during meetings or um

1056
00:47:13.830 --> 00:47:16.812
Or if you're doing change management projects within the company,

1057
00:47:17.192 --> 00:47:17.432
 you know,

1058
00:47:17.912 --> 00:47:20.074
 in response to those messages and things like that.

1059
00:47:20.554 --> 00:47:20.674
 So,

1060
00:47:20.914 --> 00:47:28.438
 I feel like there's already an intense sort of datification of both consumers and employees,

1061
00:47:29.099 --> 00:47:30.019
 particularly digitally.

1062
00:47:31.040 --> 00:47:31.240
 But,

1063
00:47:32.801 --> 00:47:34.261
 and that's kind of whether we want it or not.

1064
00:47:35.042 --> 00:47:37.703
 But there's an opportunity to do this at the physiological level too.

1065
00:47:37.883 --> 00:47:42.346
 And it seems to me that as long as people opt in in an informed way.

1066
00:47:42.786 --> 00:47:47.108
 then there's real possibility to get additional information about the way they respond.

1067
00:47:48.008 --> 00:47:50.689
 And whether they respond well or not,

1068
00:47:51.290 --> 00:47:54.211
 you can normally define post hoc and then sort of go back and look and say,

1069
00:47:54.251 --> 00:47:54.451
 okay,

1070
00:47:54.491 --> 00:47:54.651
 well,

1071
00:47:54.811 --> 00:47:55.691
 this is what was happening.

1072
00:47:56.692 --> 00:47:59.773
 I can then start to take those learnings and apply them in real time,

1073
00:48:00.173 --> 00:48:00.393
 right?

1074
00:48:00.453 --> 00:48:02.074
 Like I can start looking at,

1075
00:48:02.214 --> 00:48:02.714
 for instance,

1076
00:48:02.754 --> 00:48:08.277
 how my various teams are performing and whether or not my leaders are engaging them as well as they could be.

1077
00:48:08.457 --> 00:48:11.818
 And there's an opportunity for some feedback and growth in those opportunities.

1078
00:48:11.938 --> 00:48:12.619
 in that space.

1079
00:48:13.159 --> 00:48:16.081
 I feel like that's essentially available now.

1080
00:48:16.701 --> 00:48:17.642
 That tech exists.

1081
00:48:17.662 --> 00:48:20.684
 I don't feel like it's being used that way very much,

1082
00:48:21.325 --> 00:48:24.487
 except for possibly in big companies like Apple who own the tech.

1083
00:48:26.748 --> 00:48:28.449
 But that's something that has real potential.

1084
00:48:29.290 --> 00:48:38.897
 The other thing that's happening is that there's just incredible growth in non-invasive measurements of responses from a distance.

1085
00:48:39.117 --> 00:48:39.237
 So,

1086
00:48:39.517 --> 00:48:40.838
 tech requires that you're wearing it.

1087
00:48:41.510 --> 00:48:42.410
 But nowadays,

1088
00:48:42.670 --> 00:48:46.651
 you can do like eye tracking from the camera on your phone or on your computer.

1089
00:48:47.012 --> 00:48:49.292
 That's not like world class,

1090
00:48:49.352 --> 00:48:51.693
 but it's certainly sufficient for a lot of things that you might want to do.

1091
00:48:52.433 --> 00:48:57.094
 And like an obvious use of this that I haven't seen yet,

1092
00:48:57.174 --> 00:49:00.415
 but seems like it's got to be coming is on e-commerce sites.

1093
00:49:01.015 --> 00:49:04.636
 So if I can track in addition to your sort of clicking and scroll through,

1094
00:49:04.636 --> 00:49:10.378
 but actually see what on the page you're looking at and where it may be you're coming back with your visual attention and things like that.

1095
00:49:11.014 --> 00:49:15.638
 there's an opportunity to then use that to sort of pop up information or incentives like,

1096
00:49:15.858 --> 00:49:16.018
 hey,

1097
00:49:16.199 --> 00:49:16.899
 and if you buy now,

1098
00:49:16.919 --> 00:49:17.820
 you get 10% off.

1099
00:49:19.301 --> 00:49:19.482
 This,

1100
00:49:19.822 --> 00:49:20.182
 to me,

1101
00:49:20.582 --> 00:49:25.126
 seems like it's a gray area in terms of the ethics.

1102
00:49:25.227 --> 00:49:25.387
 Like,

1103
00:49:25.407 --> 00:49:29.510
 I think that if you make it clear to people that that's what's happening,

1104
00:49:29.550 --> 00:49:35.396
 you're using this information from where their eyes are to give them sort of customized information or offers,

1105
00:49:35.696 --> 00:49:36.136
 that's fine,

1106
00:49:36.296 --> 00:49:36.476
 right?

1107
00:49:36.496 --> 00:49:38.098
 Because then they can make an informed decision.

1108
00:49:38.714 --> 00:49:38.834
 If,

1109
00:49:38.854 --> 00:49:39.134
 however,

1110
00:49:39.174 --> 00:49:42.777
 you're recording information that you're essentially using against them,

1111
00:49:44.078 --> 00:49:45.739
 that's where I think it's dubious.

1112
00:49:46.440 --> 00:49:46.720
 However,

1113
00:49:48.061 --> 00:49:50.343
 the history suggests that when the tech is available,

1114
00:49:50.583 --> 00:49:51.444
 people will use it.

1115
00:49:51.624 --> 00:49:53.946
 And this is already in place for out of home.

1116
00:49:54.306 --> 00:49:56.728
 A lot of billboards have cameras on them.

1117
00:49:56.928 --> 00:49:58.129
 So that when you look at the billboard,

1118
00:49:58.129 --> 00:49:59.009
 the billboard looks at you.

1119
00:50:00.170 --> 00:50:05.014
 And they're recording this information that's actually used to shape what...

1120
00:50:05.254 --> 00:50:05.775
 on the screen,

1121
00:50:05.815 --> 00:50:08.617
 but also to give information back to the advertising clients.

1122
00:50:09.398 --> 00:50:10.278
 So the tech there,

1123
00:50:10.879 --> 00:50:15.162
 it hasn't been incorporated into e-commerce in a big way yet,

1124
00:50:15.583 --> 00:50:19.045
 but it seems like it's inevitable in the next handful of years.

1125
00:50:19.686 --> 00:50:26.251
And I'll just jump in with a quick terminology definition for those of you who aren't familiar with the scientific research word.

1126
00:50:26.732 --> 00:50:31.255
 Arousal in this case refers to any kind of physical activation.

1127
00:50:31.376 --> 00:50:32.356
 So like sweat,

1128
00:50:32.496 --> 00:50:33.097
 heart rate,

1129
00:50:33.477 --> 00:50:34.298
 usually stuff related.

1130
00:50:34.498 --> 00:50:37.200
 you stress or just being engaged with your environment.

1131
00:50:37.960 --> 00:50:38.141
Right.

1132
00:50:38.201 --> 00:50:38.541
 Thank you.

1133
00:50:38.621 --> 00:50:38.901
 I'm sorry.

1134
00:50:38.921 --> 00:50:39.742
 I forget to say that.

1135
00:50:42.764 --> 00:50:43.044
Joe,

1136
00:50:43.244 --> 00:50:44.045
 unfortunately,

1137
00:50:44.125 --> 00:50:47.007
 we are close to the end of this conversation.

1138
00:50:47.047 --> 00:50:49.809
 I would like to ask you two final questions.

1139
00:50:51.089 --> 00:50:56.073
 First one is for those leaders who might be new to neuroscience,

1140
00:50:56.533 --> 00:51:00.116
 but are curious about its application in the workplace,

1141
00:51:00.716 --> 00:51:03.458
 what would you recommend as a starting point?

1142
00:51:03.538 --> 00:51:05.720
 point for an initial application?

1143
00:51:06.941 --> 00:51:11.625
There's a really great book by Lisa Feldman Barrett called Seven and a Half Lessons About the Human Brain.

1144
00:51:12.105 --> 00:51:14.727
 And it's great because it's very well written,

1145
00:51:14.787 --> 00:51:16.209
 but it's also great because it's short.

1146
00:51:16.569 --> 00:51:18.891
 She conveys a lot of information in a short space,

1147
00:51:18.951 --> 00:51:21.293
 which makes it accessible for many people.

1148
00:51:22.234 --> 00:51:24.015
 So I think that's a really good place to start.

1149
00:51:24.816 --> 00:51:27.118
 There are also online courses.

1150
00:51:27.198 --> 00:51:27.998
 So for instance,

1151
00:51:28.519 --> 00:51:29.300
 Thomas Ramsey,

1152
00:51:29.540 --> 00:51:32.202
 and I'm sure I'm not quite pronouncing Thomas's last name right.

1153
00:51:32.422 --> 00:51:40.827
 has a Coursera course about consumer neuroscience that's free to join and that's very interesting and more application-based.

1154
00:51:41.247 --> 00:51:43.628
 And Thomas is one of the pioneers in this area.

1155
00:51:44.309 --> 00:51:44.429
 So,

1156
00:51:44.589 --> 00:51:46.670
 I would certainly recommend that as well.

1157
00:51:48.411 --> 00:51:53.514
 For those who are interested in learning a little bit more about the brain and maybe how it functions and thinking about how it might be relevant,

1158
00:51:53.814 --> 00:51:56.735
 there's a book by Andy Clark called The Experience Machine.

1159
00:51:57.456 --> 00:51:57.716
 And

1160
00:51:58.316 --> 00:52:00.898
 I found that particularly accessible and exciting.

1161
00:52:01.358 --> 00:52:01.478
 So...

1162
00:52:01.998 --> 00:52:10.028
 I think that's a book that anyone who really likes the neuroscience idea would enjoy because it really is open to everyone.

1163
00:52:10.149 --> 00:52:12.832
 You don't have to be a neuroscientist by any stretch to read it.

1164
00:52:13.384 --> 00:52:16.666
And maybe a new book from you.

1165
00:52:17.206 --> 00:52:17.686
I hope.

1166
00:52:18.427 --> 00:52:18.607
 Well,

1167
00:52:18.687 --> 00:52:19.007
 I hope.

1168
00:52:19.187 --> 00:52:19.848
 I'm writing one.

1169
00:52:21.308 --> 00:52:23.249
 But I'm still in the early days.

1170
00:52:23.530 --> 00:52:30.633
 And I very much look forward to being able to offer a new book for people that hopefully will be fun and engaging as well.

1171
00:52:30.793 --> 00:52:33.815
 And it will definitely have a strong consumer neuroscience component to it.

1172
00:52:34.796 --> 00:52:35.076
Okay,

1173
00:52:35.236 --> 00:52:35.536
 great.

1174
00:52:35.556 --> 00:52:37.077
 That's great news.

1175
00:52:37.577 --> 00:52:38.898
 Last question for you,

1176
00:52:39.358 --> 00:52:39.798
 Joe.

1177
00:52:40.399 --> 00:52:43.080
 Is there any emerging research or?

1178
00:52:43.200 --> 00:52:52.548
 project you are working on now that you believe will be particularly impactful for professionals outside the neuroscience field?

1179
00:52:54.029 --> 00:52:54.169
Yeah,

1180
00:52:54.269 --> 00:52:54.789
 very much so.

1181
00:52:55.450 --> 00:52:55.690
 Again,

1182
00:52:55.710 --> 00:52:56.791
 with Daniel Richardson,

1183
00:52:57.231 --> 00:53:00.254
 we've been doing this work on measuring audience engagement.

1184
00:53:00.434 --> 00:53:00.674
 And

1185
00:53:01.815 --> 00:53:08.320
 I feel like the advertising industry uses approaches that are fine,

1186
00:53:08.581 --> 00:53:09.601
 but they're just out of date,

1187
00:53:09.762 --> 00:53:09.962
 right?

1188
00:53:10.002 --> 00:53:12.704
 So there's a ton of work that relies on self-report.

1189
00:53:13.148 --> 00:53:13.668
 interviews,

1190
00:53:13.848 --> 00:53:14.569
 focus groups,

1191
00:53:15.189 --> 00:53:15.869
 those kind of things.

1192
00:53:16.089 --> 00:53:18.530
 And it's reasonable and you definitely should.

1193
00:53:19.291 --> 00:53:26.114
 But there's very little that tries to actually get at your response at a neurological level to these ads.

1194
00:53:26.294 --> 00:53:30.876
 The things like facial coding and sort of very simple kind of biometric measures,

1195
00:53:30.936 --> 00:53:35.018
 none of which I'm convinced are particularly informative for a variety of different reasons.

1196
00:53:36.498 --> 00:53:40.180
 But I do think that there's a new approach in neuroscience.

1197
00:53:40.380 --> 00:53:41.781
 that's around neural synchrony,

1198
00:53:41.961 --> 00:53:46.323
 sort of measuring how similar the brain responses are across people that

1199
00:53:46.883 --> 00:53:50.745
 Daniel and I have been working on a lot in terms of very simple measurements,

1200
00:53:50.805 --> 00:53:51.045
 you know,

1201
00:53:51.125 --> 00:53:53.586
 using kind of these available biometric tools.

1202
00:53:53.706 --> 00:53:53.826
 So,

1203
00:53:53.826 --> 00:53:56.607
 you don't need an MRI machine or an EEG machine to do it.

1204
00:53:56.867 --> 00:54:00.269
 You can just do it using the kind of tech tools that are available already.

1205
00:54:01.089 --> 00:54:01.890
 And to my mind,

1206
00:54:02.030 --> 00:54:05.651
 it's incredibly promising because in relatively small groups of people,

1207
00:54:06.032 --> 00:54:06.712
 you can get

1208
00:54:07.400 --> 00:54:12.882
 very quantitatively second by second detailed information about how people actually respond to the content,

1209
00:54:13.282 --> 00:54:14.102
 whether that's an ad,

1210
00:54:14.422 --> 00:54:15.002
 a trailer,

1211
00:54:15.342 --> 00:54:15.903
 TV show,

1212
00:54:16.243 --> 00:54:17.683
 whatever the live performances.

1213
00:54:19.224 --> 00:54:22.024
 And I think that this is going to be a bit of a game changer,

1214
00:54:22.284 --> 00:54:23.805
 but of course it's my own work.

1215
00:54:23.845 --> 00:54:26.946
 So I'm probably overblowing it because I'm excited about it.

1216
00:54:28.366 --> 00:54:31.007
 But it does seem to me something that's its time is here.

1217
00:54:31.467 --> 00:54:31.767
 And

1218
00:54:32.567 --> 00:54:34.448
 I'm very much hopeful that...

1219
00:54:35.180 --> 00:54:39.222
 There'll be people outside of the labs who are very interested in trying these things too.

1220
00:54:39.922 --> 00:54:40.402
Amazing.

1221
00:54:40.682 --> 00:54:40.842
 Well,

1222
00:54:40.862 --> 00:54:43.724
 we're definitely looking forward to all of that coming soon.

1223
00:54:43.944 --> 00:54:44.084
 And

1224
00:54:44.624 --> 00:54:47.225
 Joe, I just want to say a huge thank you for joining us today.

1225
00:54:47.265 --> 00:54:48.926
 This was a fascinating conversation,

1226
00:54:49.126 --> 00:54:52.027
 lots of really interesting concrete learnings and examples.

1227
00:54:52.467 --> 00:54:54.048
 So I'm sure our audience is going to love it.

1228
00:54:54.508 --> 00:54:55.529
 If they want to learn more,

1229
00:54:55.809 --> 00:54:58.370
 where would you point them to find out more about you and your work?

1230
00:54:58.810 --> 00:55:03.472
I think that certainly my LinkedIn page is reasonably active.

1231
00:55:04.052 --> 00:55:04.472
Heck yeah,

1232
00:55:04.652 --> 00:55:05.352
 it's awesome.

1233
00:55:05.432 --> 00:55:05.553
Yeah,

1234
00:55:05.693 --> 00:55:06.153
 very good.

1235
00:55:06.733 --> 00:55:07.873
That's very kind of you.

1236
00:55:07.913 --> 00:55:08.273
 Thank you.

1237
00:55:10.074 --> 00:55:12.634
 And if you're interested in the consumer neuroscience stuff,

1238
00:55:12.854 --> 00:55:14.795
 I have a website called

1239
00:55:15.215 --> 00:55:19.176
 Applied Consumer Neuroscience Labs or acnlabs.co.uk.

1240
00:55:19.876 --> 00:55:22.977
 And that's where a lot of the case studies are and some of the work that we're doing.

1241
00:55:23.617 --> 00:55:24.938
 So either way.

1242
00:55:25.778 --> 00:55:26.258
Excellent.

1243
00:55:26.678 --> 00:55:27.418
 Thank you so much.

1244
00:55:28.159 --> 00:55:28.779
Thanks a lot,

1245
00:55:28.919 --> 00:55:29.159
 Joe.

1246
00:55:29.199 --> 00:55:32.560
 It was really a great conversation.

1247
00:55:33.240 --> 00:55:34.945
 Thanks a lot for joining.

1248
00:55:35.126 --> 00:55:35.908
It's such a pleasure.

1249
00:55:35.968 --> 00:55:37.854
 Thank you very much for having me on your podcast.

1250
00:55:38.275 --> 00:55:38.836
Be Good,

1251
00:55:39.137 --> 00:55:41.344
 a podcast by the BVA Nudge Unit.