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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.