Something You Should Know - How the Internet Makes You a Better Consumer & Why the Experts Are So Often Wrong

Episode Date: May 2, 2019

Restaurants want you to spend more money. And the menu can be a powerful tool to accomplish that. This episode begins with exactly how restaurant menus entice you to buy more expensive items and spend more money in general. Listen and you are sure to save money. https://www.lifehack.org/articles/money/15-sneaky-restaurant-menu-tricks-that-tempt-you-spend-more.html In the old days, you had very little influence or impact as a consumer. You either bought products or services or you didn’t and there wasn’t an easy way to give feedback or talk with other customers like yourself. Then came the Internet. It has launched a new era for consumers and businesses alike. Joining me to talk about this is David Weinberger who has been a strategic marketing VP a “writer in residence” at Google a researcher, consultant and author of the book Everyday Chaos: Technology Complexity and How We’re Thriving in a New World of Possibility (https://amzn.to/2XPioxZ).   Little behaviors mean a lot. How you shake hands, eye contact, whether or not you are late – they all send a message to other people. Listen as I explain what message they send and how to maximize the impact. (Travis Bradberry author of “Emotional Intelligence 2.0”) Sometimes the answer is right in front of you but you completely miss it. It happens to everyone – even the experts. Gordon Rugg – a British researcher and author of the book Blind Spot: Why We Fail to See the Solution Right in Front of Us (https://amzn.to/2GFXQCa) joins me to explain why this happens. Sometimes it is because we ask the wrong questions or we ask to wrong expert. Listen as Gordon shares some fascinating insight into this common problem. This Week's Sponsors -Fab Fit Fun. For $10 off your first box go to www.FabFitFun.com and use the promo code: something -ADT. To get a secure smart home designed just for you go to www.ADT.com -BetterHelp. Get help with a counselor you will love at www.BetterHelp.com/SYSK -Capital One. What's in your wallet? www.CapitalOne.com Learn more about your ad choices. Visit megaphone.fm/adchoices

Today on Something You Should Know, the little tricks restaurants use to get you to spend more money. Then, how the Internet has given you so much more power as a consumer compared to the way it used to be. Where we were passive consumers and the business was the supplier. And if we wanted to talk with them, we basically couldn't in the old days. You'd call up customer support or whatever, but you were isolated. You go online, and if the business won't talk to you, the other customers will. Then, the little behaviors you do that have a big impact on what people think of you. And why experts so often get it wrong when they try to solve a problem.

Look at the types of experts who are working on it. Because experts are only experts in their own tightly bounded area. And if they stray just a little bit out of that, they're no better than ordinary mortals. All this today on Something You Should Know. As a listener to Something You Should Know, I can only assume that you are someone who likes to learn about new and interesting things and bring more knowledge to work for you in your everyday life. I mean, that's kind of what Something You Should Know was all about.

And so I want to invite you to listen to another podcast called TED Talks Daily. Now, you know about TED Talks, right? Many of the guests on Something You Should Know have done TED Talks Daily. Now, you know about TED Talks, right? Many of the guests on Something You Should Know have done TED Talks. Well, you see, TED Talks Daily is a podcast that brings you a new TED Talk every weekday in less than 15 minutes. Join host Elise Hu. She goes beyond the headlines so you can hear about the big ideas shaping our future. Learn about things like sustainable fashion, embracing your entrepreneurial spirit,

the future of robotics, and so much more. Like I said, if you like this podcast, Something You Should Know, I'm pretty sure you're going to like TED Talks Daily. And you get TED Talks Daily wherever you get your podcasts. Something You Should Know. Fascinating intel. The world's top experts.

And practical advice you can use in your life. Today, Something You Should Know with Mike Carruthers. Hi, welcome to Something You Should Know. If you dine out much, I'm about to save you some money, or potentially save you some money, by revealing some of the tricks that restaurants use to get you to spend more. They do this primarily with the menu, and if you know them, you may be less likely to fall for them. For example, if there are no prices listed, there's a good chance you will spend more.

A lot of people don't feel comfortable asking about prices for the food on a menu, but you wouldn't go to a department store and buy a sweater and not know the price of it, so why would you buy a meal and not know the price of it before you get it? Just the absence of a dollar sign can increase profits for a restaurant. You know when sometimes they'll put the price of an entree or an appetizer, but there's no dollar sign in front of it. It's just the number. Well, research shows that diners spend 8% more when there is no dollar sign. Tangy, zesty, succulent, and crispy. Those are some powerful menu words. Because if the menu can get your mouth watering with words like that, you will spend more money.

And restaurants like to use boxes on their menu. They'll often highlight things like high-profit items or more expensive items in decorative boxes, which draws your eye to them. And there's the old trick of inflating the price of the second cheapest wine. This is restaurant psychology at its best here, because a lot of people don't want to buy the really expensive wine, but they don't want to seem too cheap either, so they pick the second cheapest wine.

Restaurants know this, and they mark that bottle up a lot. And that is something you should know. Until recently, as a consumer, the way you have done business hasn't really changed much in a very long time. Businesses would offer you products and services that they thought you would like, and you could either buy them or not. And if not, maybe you would buy them somewhere else, or maybe you would buy something similar instead. With the internet now, that model has all changed. You as a consumer have a lot more choices at your fingertips. You also have a forum to rate your experiences as a consumer.

And as a business person offering products and services, you now have this tremendous ability to tap into your consumers and find out what they want or don't want, what they like or don't like, and what they think of it all. In many ways, it is a huge change with a lot of ramifications. And here to dive deep into this fascinating new world is David Weinberger. David has been a strategic marketing VP, a writer in residence at Google. He is a researcher and author, and his new book is called Everyday Chaos, Technology,

Complexity, and How We're Thriving in a New World of Possibility. Hi, David. Hi, Michael. It seems that this new way of doing business has kind of crept up on us in many ways. So let me have you explain it better and deeper with some examples to start. So one of the examples that I think is particularly helpful is you look at Henry Ford, you know, pre-internet. And he's just this master of anticipating what his customers are going to want in a Model T. And he nails it so exactly. 1908, he basically does not change the thing for 19 years. He sells 15 million of them. So, you know, pretty awesome job. They're

going to want the car to ride high because they're riding over horse trails. None of them basically know how to drive a car, so the UI has to be really simple. He just nails it. And of course, we continue to do that and we'll continue to do that. But we're also doing this other thing simultaneously, a bunch of other things. So one of them is the minimum viable product idea, which a lot of software companies, services on the internet have adopted. So rather than figuring out exactly what your customers are going to need, you figure out the one thing, the key feature, you know, it's a big idea for your product, and you launch only with that single feature. You do this so that

you can then measure what people are doing. You can ask them, you can watch them, you can listen to how they are talking with one another and see what users actually want. Not what you're guessing they want, but what they actually want. And they probably don't know what they want until they have the product in their hands. This turns out to be, in many instances, a really successful way of launching a product. It is not Henry Ford's way. MVPs work because they consciously refuse to anticipate. They hold back, refrain from anticipation. It's unanticipation. And what's a good example of that today?

Henry Ford did it his way in his day. Who's doing that well, the minimally viable product idea, and hitting it out of the park? Dropbox is one. Slack is another. I mean, Dropbox started as a, here's the big idea. You'll be able to work on your files anywhere. And then over time, they saw what people needed. And now you can do multimedia. You can collaborate online. You can do revision tracking. They keep adding features in response to what their users actually want. But Slack's actually an example of another thing

as well. So Slack is a messaging app, very popular for teams, sometimes in very big companies. So it started as an MVP, but they also did this other thing, which is increasingly common and is so filled with unanticipation. So they have a fully formed product. They also now have and have had for a long time an open platform, an API technically, which allows any developer anywhere in the world, anybody connected to the web, to take Slack's product and to extend it, to alter it, to integrate that product, Slack, into the rest of that developer's client's set of tools for work into their workflow. Slack did this. In fact, Slack set up an $80 million fund to encourage people to do this

because it means that Slack does not have to anticipate every conceivable feature or tweak that somebody might want because they can't. And if they could, they wouldn't have the resources to implement them everything and it means that slack can become deeply integrated into the working tool set of multiple multiple clients without slack having to figure out what all those other tools are and make the changes and it's it extends the functionality of Slack. It makes Slack an integral part of a workflow and thus more valuable. And these sorts of open platforms are all over the place. Facebook has had one for a while.

People build things on it. Lots of nonprofits do this. New York Times has an open platform. I helped produce one for the Harvard Library System that makes resources that are already available more widely available. But can you take that model offline? And does it work with widgets, or it only works online with open platforms? Well, that's an interesting question. So it's much easier to do this. All these things are easier to do. And many of these changes, I think, and how we think about how the world works, how complex it is and how we deal with the future are has real laws and it's really sort of important. But cause and effect is – we can see in this new world, it's just one way in which things interact.

Particularly important one, of course, but it's one way in which things interact. And online, the internet exists only, well, only is too strong. The internet exists as a way of allowing pieces to interact with other pieces. It's interoperability is what it's called, right? So that's what makes the internet an open, fluid environment in which everything can move around. You can reuse stuff and repurpose it and the rest of it. Offline, that's harder. I'd say it's the same thing that we see happening overall with the internet in the real world,

where online businesses have been, I think, for at least the past decade, to a large extent, driving the way the offline parts of the business thinks about itself. Overall, there's more customer interaction, more customer listening to customers, more involvement of customers in product, early product design cycles, more feedback from customers, more bringing customers together to interact with one another and learning from them and doing that both online and offline. But it always seems to me that businesses are, offline businesses are doing that, not so much because they want to, but because they have to. Because the online businesses are so touchy-feely with their customers, I guess we better do it too. Yes, there's a lot of reluctance to engage in all of these new, not just tactics and programs, but also ways of thinking about

things. I think the net and now machine learning are changing our ideas about how things go together. And there's tremendous resistance. There has been resistance in each sector, and there's offline resistance as well, for sure. But you have to ask, why is the pressure there? Why has the internet so reshaped our ideas about what it means to be a customer, what it means to be a business, and what the relationship should be? That offline feels, even though it doesn't want to, it doesn't like it, it thinks it's all just touchy-feely stuff.

Nevertheless, they feel obliged to start engaging in ways that they may not be very comfortable with. So even if you're a business that is traditionally thought of as an offline business, you still need to incorporate some component of online something in order to stay competitive. Yes, I think that's right. I think online has shaped our understanding of what our relationship to a business is. We are less patient, I think, offline with the impersonal and, well, let's say impersonal mass relationships that we used to only have, where we were passive consumers and the business was the supplier and if we wanted to talk with them we basically couldn't in the old days you'd call up customer support or whatever but you were isolated you go online and if the business won't talk to you the other customers will sometimes often very, very happily and exploring new ways of using a product, but also when they're not happy talking with one another in that way as well.

And once you get and that's a sense, I think that gives customers has given customers already a sense of of power and and agency. We're not the passive recipients of things. We have a voice as well. We can have an influence and we can affect by sharing knowledge and ideas among customers. We can change the way that we use products. We can even make changes to products. We got used to the idea that there isn't a single source of information about products and that source is the business, and the source only wants to tell us what it wants us to know. Those days are way over. That's been over for 20 years. That has given us customers, all of us, I think, a very different idea of our relationship to the

business. And it doesn't stop at the edge of the internet. It continues out into the real world. It has changed our understanding. But is that coming back in a sense when I think of the retail business? I mean, Amazon is so dominant that it seems like they can do whatever they want. Yeah, I mean, the Internet has slipped all too easily into a sort of re-centralization of big powers. That's regrettable. At the same time, the way that Amazon customers interact with one another on the site and off the site to decide what product they want to buy or how to get this thing to work or what else they can do with it

or does this car really work in a Boston winter? All that sort of stuff, whether it's coming through a giant like Amazon or from a local car dealership. We expect now to be able to deal with other customers and get honest answers about that power relationship. The change in the power relationship, I think, who knows, I think is permanent, even as there's this tremendous centralization of power in retail and other sectors as well. I'm speaking with David Weinberger, and his book is called Everyday Chaos, Technology, Complexity, and How We're Thriving in a New World of Possibility. You know, there are times in everyone's life, I don't care who you are, there are times when something interfer life, I don't care who you are, there are times when something interferes with your happiness or prevents you from achieving

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Every episode is a conversation with a fascinating guest. Of course, a lot of podcasts are conversations with guests, but Jordan does it better than most. Recently, he had a fascinating conversation with a British woman who was recruited and radicalized by ISIS and went to prison for three years. She now works to raise awareness on this issue. It's a great conversation. And he spoke with Dr. Sarah Hill about how taking birth control not only prevents pregnancy, it can influence a woman's partner preferences, career choices, and overall behavior due to the hormonal changes it causes.

Apple named The Jordan Harbinger Show one of the best podcasts a few years back, and in a nutshell, the show is aimed at making you a better, more informed critical thinker. Check out The Jordan Harbinger Show. There's so much for you in this podcast. The Jordan Harbinger Show on Apple Podcasts, Spotify, or wherever you get your podcasts. Hi, I'm Jennifer, a co-founder of the Go Kid Go Network. At Go Kid Go, putting kids first is at the heart of every show that we produce. That's why we're so excited to introduce a brand new show to our network called The Search for the Silver Lightning, a fantasy adventure series about a spirited young girl named Isla who time travels to the mythical land of Camelot. During her journey, Isla meets new friends, including King Arthur and his Knights of the

Round Table, and learns valuable life lessons with every quest, sword fight, and dragon ride. Positive and uplifting stories remind us all about the importance of kindness, friendship, honesty, and positivity. Join me and an all-star cast of actors, including Liam Neeson, Emily Blunt, Kristen Bell, Chris Hemsworth, among many others, in welcoming the Search for the Silver Lining podcast to the Go Kid Go Network by listening today. Look for the Search for the Silver Lining on Spotify, Apple, or wherever you get your podcasts. So David, now I'm asking you to predict the future, but where's the next step in this evolution if there is one? I'm old enough to know that I don't know what's going to happen. But I think that especially with the rise of machine learning and the way that machine learning thinks about the world, I think that is in fact bringing us to an evolutionary step.

So we got used to the chaos and information overload, which we continued to not just not to flee from, but to demand we want more and more information. The Internet got us used to that environment, an environment in which in in various ways, we've gotten used to the idea that we will open up more possibilities, we will do what we can in order to make things more reusable. As individuals and as businesses, we want more and more possibilities rather than a narrowing of possibilities. Machine learning, I think, is giving us a way of understanding that in some sense and giving us a different model of how the world works. And I think that we are well down the path of accepting that implicitly. Since you brought up machine learning, artificial intelligence a moment ago, explain how that fits into this discussion. So a normal computer, when you want to program it to do something, let's say it's to predict quarterly sales, you tell it what the main factors are.

Number of salespeople, number of leads, incentives, all the rest of that. And then you tell it how those factors are related. So maybe if you increase incentives, maybe you'll get more sales, et cetera. That's a model, right? You specify the factors and the relationships. With machine learning, you don't do that. This is why it's really a big step. You do not have a human say, okay, here's what we think the relationships are. Instead, you just give it this huge bag full of data, millions and millions of data points if you can. And then it uses math stuff to go through and find statistical relationships among the parts and the parts – the little pieces of data in all their relationships with the other pieces of data. Sort of weighted relationships, probabilistic correlations from this point

to 10,000 others, and then each of those. So you get this massive model of interdependencies of small particulars. And when it works, it works really nicely. It can predict sometimes better than we can and classify faster or more accurately. That's why we use it. But these models that it's building for itself, which are in some sense a representation of the world, don't rely upon coming up with general formulas

and the relation of incentives to sales. And it's millions of points in intricate, complex relationships with millions of points in intricate complex relationships with millions of points that type of model seems to me to be a better representation of how the world works we couldn't see that because our brains are too small but now our machines can they can handle all these particulars without having to reduce them to some generalizations or principles that are ones that we can understand. That is a way of envisioning and understanding and even working with the chaos of particulars in their relationship of everything to everything that is a powerful new model for us and very different from the one that we've had for a long time.

But in the case of a very relevant but very traditional offline business, dry cleaner, break shop, bakery, do they need to get on board with this or are they going to be able to do just fine as a traditional dry cleaner, break shop, bakery? So that's a really good question. So if I had to guess, yeah, they're going to do fine. But they should also recognize that underneath the stability that guides them, that they rely upon, and we think it's long-term stability, the world is nevertheless chaotic. And so it's quite likely, I would guess, as I think you would too, that the local dry

cleaner is going to do fine. The local dry cleaner, however, may also be disrupted by factors way beyond its control. Who knows what? Some local disaster or some change in laws or the shortage of this or that or change in fashion where people don't care about clothes that, you know, an invention of clothing that doesn't need dry cleaning. That sort of disruption is always there. It would be good to keep that in mind, even though there may not be much you can do about it. And the way that you keep in mind is try to stay as involved in as much information overflow as you possibly can, because that's where you're going to see the early signals.

You know what's scary about this in some ways is that if you go back 50 years and look into the future, nobody could have predicted the internet and what we have now and how it's changed, how business has done and all the things you've been talking about for the last 15 minutes or so, which makes you wonder what's going to be in the next 50 years that we can't even begin to imagine. I mean, it just, it seems chaotic. Yes, yes it is. And it is scary, but it's also, I think, the truth. I think it's the truth of the world that we too frequently in our long histories as a species,

we want to avoid. But it is the truth. And I think it's in one sense getting worse, another getting better. histories as a species we want to avoid. But it is the truth. And I think it's in one sense getting worse and in another getting better. It's getting worse in that because we now have tools that enable us consciously to mint new possibilities, to create new possibilities, to open source our stuff if we want to. Toyota just recently open sourced its electric car patents. Tesla had done that before. That has the possibility of now suddenly much more progress,

many more new ideas in electric cars. And that's a generative type of change. That is, it's a change that produces more change. And we have been creating this type of generative technology, especially on the internet from, well, since the internet took off in the early 1990s, became, you know, became some, became something that everybody in businesses care about. So we are actually, I think, making, I think we are actually, I think, making a world that is even less predictable than it was. On the other hand, the positive side of this is not only do I think this chaos is the truth of the world, but we're able to do so much more because we no longer have to do everything ourselves. Computer games have been very early in making their technology reusable by users. It's called modding. People have been doing it since the early 1980s, where you can take a game and you can change its map or its rules or new equipment. The game makers frequently not only allow that, but they encourage it by

making available the tools that their own developers use. And so if you're a game maker, you get the benefit of repeatable, you know, a game that has much longer lifetime. As a culture, taking games as a cultural item,

we get much, much more. Everybody can build on what everybody else has done. Well, I remember when people were first talking about this, how users could put their own two cents and help develop a product. And I remember thinking, and I'm sure everybody else thought, why would people do that? They're not getting paid to do that. Why would they do that? Nobody's going to do that.

And yet everybody does that. Yeah. I mean, people care about the things that they buy. You know, it's not as some stuff is just, you know, think about and that these days go online, maybe do a little reading, that we have a human relationship with those objects. They mean something to us beyond their mere utility. So, yeah, and always have. That's not new. But now we have an opportunity to find other people who also care about it and to learn from them and joke with them and the rest of it.

So it's not surprising to me that customers want to do this. Yeah, you're probably right. It's just that before the Internet and before all the things that you've just been speaking about, we didn't have the ability to do that. It was just the old way of Henry Ford's way of doing business. My guest has been David Weinberger, and he is the author of a new book called Everyday Chaos, Technology, Complexity, and How We're Thriving in a New World of Possibility. You will find a link to his book in the show notes for this episode of the podcast.

Thanks, David. Oh, thank you, Michael. People who listen to something you should Know are curious about the world, looking to hear new ideas and perspectives. So I want to tell you about a podcast that is full of new ideas and perspectives, and one I've started listening to called Intelligence Squared. It's the podcast where great minds meet. Listen in for some great talks on science, tech, politics, creativity, wellness, and a lot more.

A couple of recent examples, Mustafa Suleiman, the CEO of Microsoft AI, discussing the future of technology. That's pretty cool. And writer, podcaster, and filmmaker John Ronson, discussing the rise of conspiracies and culture wars. That's pretty cool. of person Intelligence Squared is meant for. Check out Intelligence Squared wherever you get your podcasts. Hey, everyone. Join me, Megan Rinks. And me, Melissa Demonts, for Don't Blame Me, But Am I Wrong? Each week, we deliver four fun-filled shows. In Don't Blame Me, we tackle our listeners' dilemmas with hilariously honest advice. Then we have But Am I Wrong?,

which is for the listeners that didn't take our advice. Plus, we share our hot takes on current events. Then tune in to see you next Tuesday for our listener poll results from but am I wrong. And finally, wrap up your week with fisting Friday, where we catch up and talk all things pop culture. Listen to Don't Blame Me, But Am I Wrong on Apple Podcasts, Spotify, or wherever you get your podcasts. New episodes every Monday, Tuesday, Thursday, and Friday. Have you ever tried to solve a problem and fail at it, and then when you did find out what the right answer was, say,

how did I miss that? It's happened to all of us, I imagine. Why? Why does it sometimes seem in retrospect that the answer was right in front of us and we didn't see it? Interesting question, and one that's been studied pretty thoroughly by Gordon Rugg. Gordon is a British researcher and author of the book Blindspot, Why We Fail to See the Solution Right in Front of Us. Hi, Gordon. Hello, good to meet you. So give me an example, a good teaching example of how this happens.

Yes, here's a very simple example from market research. Market researchers will ask you, what do you think of this product? And they'll usually give you a scale from dislike at one end to like at the other end. And that looks perfectly sensible and reasonable. And it's a pig to analyze because you get a lot of answers that are in the middle and you don't know what that means. So what happens if instead you treat those as two separate questions? How much do you like this and how much do you dislike this? And when you do that, and then you plot those two sets of numbers against each other, suddenly you get a completely different way of thinking about the problem that had been staring market researchers in the face forever and that they'd missed. So what you find is that for a lot of products, they're low on both liking and disliking. They're harmless and they're boring and there's nothing very amazing about them. And at the opposite extreme, you get some products where people love the product and hate it at the same time.

So, for example, if something's described as an exclusive resort, then that sends out the positive signal of very high quality, but also the negative signal of it might be very snooty and snobbish and unwelcoming. So by plotting those two things of liking and disliking separately, you can then start seeing what people's reactions are to your product or service or whatever, and you get a much richer idea of what you can do about it. So when I've taken that to some of the most prestigious companies in the world and shown them, it was very gratifying and entertaining for me to see the double take that they did as they realized that they'd looked right past that for their whole careers. And that's such a great question, because no one ever asks you, how much do you dislike something? And it's probably a lot more telling, or at least adds another layer of dimension to the answer rather than how much do you like this? Because everybody wants to kind of be in the meaty part of the curve, I guess.

Absolutely. And that sort of representation tells you what you have to do with your product. So if you're down in that low liking, low disliking, you have to add something to it. If you're in the high liking and high disliking, you have to subtract something from it. Another thing you can get is where some people love it completely and don't dislike it at all, and others hate it and don't like it at all. So it's what we call in the UK the Marmite effect. People either love Marmite or they hate it. You don't get it at all. So it's what we call in the UK, the Marmite effect. People either love Marmite or they hate it. You don't get anyone in the middle. So if you've got a Marmite product,

then what you do is say, we'll focus on this market. We won't try and change the taste, because if we do, we'll lose the people who love it. So very clear, precise guidance on what to do about your product or your service. It's interesting. I know you talk about how experts play into this and that part of the problem anyway is that people think, well, if you're going to find the solution, you get yourself an expert and an expert can find the solution, which often adds to the problem. But largely because they have influence. They tend to make the same types of mistakes that ordinary humans do. The trouble is that if the expert is designing something like a car or a medical intervention, then the scope for effect on ordinary human beings is much greater

than if you or I made a mistake. What is it about being an expert that makes you miss the obvious? One thing that's a real problem is what's called strong but wrong errors. Those are errors where you do the familiar thing instead of the right thing. So an everyday example is if you go to work every day and you lock your office every time you go out the office door, which a lot of people do, you'll use your office key much more often than your home front door key. If you're in that situation, you will find yourself occasionally trying to unlock your home with your office key, but you'll never find yourself doing the opposite to that. You're doing the thing that's familiar. You're at a door, you need to unlock it, and you do the most common thing.

So as an expert, you'll be dealing with familiar cases a lot of the time, like a doctor who sees a particular condition over and over and over again, and they see someone else with the same the same symptoms and there's a real risk that they'll make a strong but wrong error so they're actually trained explicitly in strategies to overcome that risk well and it's i think everybody can see that in whatever industry they work in or in any organization where people who know think they know so they know so they don't have to think too hard about it. Yes, exactly. And you also get a lot of assumptions that everyone has made for so long that they've become treated as just self-evidently true, like the disliking and liking thing. And so people just don't look at those things because they're so familiar. They look right past them at whatever is new and whatever is right in their face, instead

of going back several steps and looking at their key assumptions and seeing if those assumptions are still true. What's the mathematics of desire? There are regularities in people's aesthetics, the things that they like. So, for example, there's a sweet spot for height, and it's equivalent in ordinary English to pretty whatever it is. So if you're pretty tall, fairly tall, then you're viewed as more prestigious, more attractive, a whole load of things like that. If you're very tall, then you've gone too far from that sweet point and you tend to be viewed as an oddity. And you tend to get the same distance from that average point, cropping up over and over again as the sweet spot so it's

statistically about one to two standard deviations from the mean which is the equivalent of fairly whatever it is so you've got a sweet spot for example for petite women and a sweet spot for tall women similarly with men there's a lot of other things like that where there are irregularities that people don't realize they're actually using. And this is what, human nature? What is causing this? I'm fairly sure it comes down to the way that brains process information. The brains try to keep things simple. So an example is symmetry.

People prefer symmetry, but so do animals, right down to the level of insects. So bees prefer symmetry to non-symmetry. So it's clearly not a human culture thing. And I think the reason is that if you've got symmetry, then essentially you'll need to remember half of what you're seeing, and then you can mirror image, predict what the other half will be. Whereas if you've got something that's asymmetric, you have to remember the whole of the image, so it's twice as much load. How else do we have blind spots that we might not be aware of or that because everybody's had that experience of oh yeah obviously sure there it is and we missed it but how else does this show up in life? One example is when you go to the ATM to take money out a very easy mistake to make is to take the money and walk away and leave the card in the machine.

That used to happen all the time with the very early machines. And the designers were software engineers and logical and rational. And they thought what sort of person would leave a valuable card behind. People like everybody is the answer. What was actually going on was that the human brain, when the human went to the ATM, was thinking, I'm going to this device to get money out. And once the money was out, it had accomplished its goal and taking the card after it got the money that came after it achieved its goal there was no reason to remember that so what they did was to

redesign so that first you have to take your card and then after that you get the cash so getting the cash is the last part of the transaction. And then you've achieved your goal. And so you've designed out that human error. That's really interesting because who hasn't done that? I mean, so many people have done that. And so understanding all of this, and it's really fascinating, but what's the big so what here what do we take from this and what can we learn from this what's the what's the big point here i think there's two big points one is that in everyday life there's a lot of room for making things much better very easily

very low cost like the example of the market researchers and liking and disliking, for example. There's a similar one I can tell you, which is about what's called expressive behavior versus instrumental behavior. Expressive behavior shows what sort of person you are. Instrumental behavior is about getting a job done. And I've been working with people in the medical services on this because they get a lot of problems with doctor-patient or nurse-patient interactions. So when I told them about instrumental and expressive behaviour, suddenly they could see how a lot of the problems they were getting was when there was a mismatch between an expressive patient, for example, who's saying, I'm so ill, I'm so worried. And they want a doctor who will

be expressive and say, don't worry, it's all right. If instead they've got an instrumental doctor who says, statistically, you're likely to be fine, I'm going to do these things, then the patient is going to be very uncomfortable because the doctor, in their language, isn't showing that they care. And conversely, if you've got an instrumental, fact-driven patient who says, I want to know what to do about this condition I've got, and the doctor says, there, there, you'll be fine, again, you've got a problem.

So that very simple concept lets you teach the medics some simple stock phrases they can use to handle the two different types of patient. And suddenly everything improves for everyone. So let's talk about the verifier method because this is really interesting as it pertains to something called the Voynich Manuscript. And just briefly, the Voynich Manuscript is this book supposedly from the 15th century written in an unknown language. And codebreakers spent 93 years trying to figure it out, only to find out, and with your input as I understand it,

only to find out that it was all a hoax. And what you call the verifier method comes into play here. It works for problems where probably the experts have got all the information that they need and they're still stuck because that implies that they're putting their answer together in the wrong configuration so if you've got one of those cases what you then do is look at the types of expert who are working on it because experts are only expert in their own tightly bounded area and if they stray just a little bit out of that, they're no better than ordinary mortals. So in the case of the Voynich manuscript, for example, the people who'd been studying it were expert code breakers and experts on languages, but none of them was an expert on

hoaxing. So when they said it can't be a hoax, their opinion wasn't worth any more than anybody else's. So you need to look at the types of expert who are working on the problem and see if there's any expertise gaps. Then what you can do is take their chains of reasoning and evidence and just spell them out step by step. And something as simple as that can suddenly start showing you that everybody is making this assumption. But where is it coming from? What's the evidence behind it? So an extreme case of that was in archaeology, where somebody tried doing that for the literature and how to tell how old an animal was when it was slaughtered from its teeth. And he discovered that everyone had quoted previous researchers and quoted previous researchers who'd quoted previous researchers. And it all fanned back to just one paper in the 1800s, which had got it almost right, but not quite.

So if you look at the evidence that they're basing those assumptions on, you'll quite often spot where there's suddenly a gap. Your example just now of when they were looking at this manuscript for 90 years, and they had language experts, and they had all these experts determining it wasn't a hoax, but they didn't have a hoax expert. As soon as you say that, it's like, well, of course. It's always easy with hindsight. Yeah. Isn't that interesting?

I mean, the moment you said it, like, you know, in 90 years, somebody didn't bother to find an expert on hoaxes and ask them their opinion? Researchers are human, and humans are social animals. So if the consensus in your field is everyone's doing it this way, there's a lot of pressure on you to do it the same way as everyone else. Which has probably caused more mistakes and errors than anybody cares to admit. It's really great. It's fun to take a peek inside your brain because it works a

little different than everybody else's, so I appreciate that. Gordon Rugg has been my guest. He is a British researcher and author of the book Blindspot, Why We Fail to See the Solution Right in Front of Us. There's a link to his book in the show notes. Thanks, Gordon. Thank you very much. It's been a pleasure talking to you. You and I constantly make judgments about other people based on what we see them do. Humans do that and we cannot not do that. And here are some common everyday actions that people use to make judgments about you, according to Travis Bradbury, author of the book Emotional Intelligence 2.0.

Handshake. People associate a weak handshake with lack of confidence and an overall lackadaisical attitude. A firm handshake equates with being less shy, less neurotic, and more extroverted. Tardiness. Showing up late leads people to think that you lack respect and you tend to procrastinate, as well as being lazy or disinterested. How you treat waiters and receptionists. This has become a common interview tactic that a lot of employers use. By gauging how you interact with support staff on your way in and out of the building, interviewers get a sense for how you treat people in general. How often you check your phone. If you do it in the middle of a

conversation, that conveys a lack of respect, attention, listening skills, and willpower. And then there's eye contact. Staring at someone is creepy, but maintaining eye contact about 60% of the time is just the right amount.

And that is something you should know. If you're on Twitter, so are we. Check us out. We're at SomethingYSK. I'm Mike Carruthers. Thanks for listening today to Something You Should Know. Welcome to the small town of Chinook, where faith runs deep and secrets run deeper. In this new thriller, religion and crime

collide when a gruesome murder rocks the isolated Montana community. Everyone is quick to point their fingers at a drug-addicted teenager, but local deputy Ruth Vogel isn't convinced. She suspects connections to a powerful religious group. Enter federal agent V.B. Loro, who has been investigating a local church for possible criminal activity the pair form an unlikely partnership to catch the killer unearthing secrets that leave Ruth torn between her duty to the law

her religious convictions and her very own family but something more sinister than murder is afoot and someone is watching Ruth Chinook starring Kelly Marie Tran and Sanaa Lathan.

Listen to Chinook wherever you get your podcasts. Contained herein are the heresies of Rudolf Buntwine, erstwhile monk turned traveling medical investigator. Join me as I study the secrets of the divine plagues and uncover the blasphemous truth that ours is not a loving God and we are not its favored children. The heresies of Randolph Bantwine, wherever podcasts are available.