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Speaker 1: Welcome to tech Stuff, a production of I Heart Radios

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Speaker 1: How Stuff Works. Hey there, and welcome to tech Stuff.

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Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with

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Speaker 1: How Stuff Works in My Heart Radio and I love

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Speaker 1: all things tech And recently I attended a Techonomy conference

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Speaker 1: in New York City where people from different parts of

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Speaker 1: the technology space came together to give presentations and interviews

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Speaker 1: about stuff like technology, government, society, and business. And most

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Speaker 1: of the focus of the talk sort of gravitated toward

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Speaker 1: a big question, will technology save us or will it

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Speaker 1: destroy us? Now? I think ultimately everyone at that conference

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Speaker 1: all agreed that that question, while compelling, masks the real question,

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Speaker 1: which is will we work to save ourselves or will

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Speaker 1: we allow ourselves to be destroyed? Technology, as it turns out,

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Speaker 1: is really just a tool. It can facilitate either outcome.

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Speaker 1: The determining factor, however, is us how we design and

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Speaker 1: implement that technology. Now, that being said, technology can have

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Speaker 1: real effects on us, and sometimes we might not even

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Speaker 1: be fully aware of those effects. There was a lot

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Speaker 1: of talk during the conference about how we tend to

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Speaker 1: think about the Internet as a connective tissue that allows

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Speaker 1: us to communicate with practically anyone anywhere on Earth. For

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Speaker 1: many years, that was how we described the Internet. In fact,

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Speaker 1: I would argue we still describe the Internet in this fashion.

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Speaker 1: It's this global network of networks and you can easily

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Speaker 1: get in contact with practically anybody at a moment's notice.

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Speaker 1: But in reality, we've seen the Internet also serve as

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Speaker 1: a means of creating silos of people who grow increasingly

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Speaker 1: separated and insulated from each other, mostly from people who

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Speaker 1: don't share their views, so they all end up an

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Speaker 1: individual echo chambers that reinforce their views while simultaneously dismissing

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Speaker 1: or denying the views of other people. So rather than

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Speaker 1: a uniting force, the Internet is enabling greater division than ever.

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Speaker 1: And there are a lot of reasons for that. And

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Speaker 1: you could even argue that that is too narrow a view,

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Speaker 1: that yes, that is happening, but it may be that

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Speaker 1: that's not the only thing is happening, or not even

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Speaker 1: the primary thing that's happening. So maybe someday I'm going

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Speaker 1: to do a full episode or or perhaps even a

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Speaker 1: short series about that topic. But today I just wanted

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Speaker 1: to look at one specific component of this overall picture

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Speaker 1: that factors into these discussions, and that component is addiction

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Speaker 1: to technology, and addiction is a strong word. Uh, it

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Speaker 1: may not be fully appropriate to use the word addiction,

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Speaker 1: but it is the one that a lot of people

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Speaker 1: do use to describe the kind of behaviors I'll be

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Speaker 1: talking about. So for the purposes of simplicity, I'm going

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Speaker 1: to use the word largely because I don't have an

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Speaker 1: alternative that is as good at summing up the general meaning. Now,

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Speaker 1: to understand the ideas behind this addictive nature of technology,

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Speaker 1: I thought we could look at an older tech that

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Speaker 1: I've covered before, and uh, it's from a Tech Stuff

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Speaker 1: classic episode. I'm talking about slot machines. The technology of

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Speaker 1: slot machines, when you really boil it down, is pretty simple,

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Speaker 1: But the principle behind slot machines depends upon something that

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Speaker 1: has nothing to do with the technology when you really

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Speaker 1: boil it all down. Instead, it's depending upon human psychology

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Speaker 1: and how through technology we can exploit the way we

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Speaker 1: humans behave and make a profit from that behavior, because

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Speaker 1: that's at the very heart of what we're looking at

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Speaker 1: in tech today. Now, just in case you aren't familiar

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Speaker 1: with a slot machine, it's like ambling device. Typically it

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Speaker 1: has a panel that has divided up into columns, and

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Speaker 1: each column is a reel or a wheel, if you

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Speaker 1: can think of it that way. But it's a reel

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Speaker 1: that has a selection of symbols on the outer side

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Speaker 1: of that reel. So you put whatever the amount of

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Speaker 1: money is into the slot machine for that particular machine.

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Speaker 1: You know they're penny slots, they're hundred dollar slots, and

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Speaker 1: then of course if you're in another country, it'll relate

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Speaker 1: to whatever currency that country uses. But then you after

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Speaker 1: you put the money in, you typically will pull a lever,

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Speaker 1: or more frequently you'll push a button, and the reels

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Speaker 1: begin to spin. The reels, by the way, it can

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Speaker 1: be physical or they can be virtual. They can be

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Speaker 1: digital reels on a video screen, or they can be

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Speaker 1: actual physical reels that are spinning on a electro mechanical spindle.

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Speaker 1: Then each reel stops. Typically they stop left to right,

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Speaker 1: so if it's a three reel slot machine, it would

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Speaker 1: go one to three, and if you have the right

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Speaker 1: symbol that are aligned in a specific way, you win.

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Speaker 1: There's no skill involved in playing a slot machine. There's

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Speaker 1: only chance the symbols, like I said, could be permanently

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Speaker 1: affixed to those physical wheels, or it could be a

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Speaker 1: video screen that simulates a spinning wheel. I know people

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Speaker 1: who won't play those games because they think of them

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Speaker 1: as being somehow fixed that the video screen can show

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Speaker 1: you any any, any collection of symbols at once, quote

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Speaker 1: unquote it once, whereas a physical machine is different. But

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Speaker 1: here's a secret, they're not really different at all. Now,

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Speaker 1: some games will allow you to add in extra features,

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Speaker 1: like you could play multiple credits at once, which typically

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Speaker 1: means you get an increased payout if you do happen

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Speaker 1: to win um, but it could also unlock extra features

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Speaker 1: such as numerous potential lines that could represent a win. Typically,

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Speaker 1: on a very basic machine, the three symbols have to

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Speaker 1: line up in the center of each of those slots,

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Speaker 1: and it has to be the same symbol on all

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Speaker 1: three reels, and then you win. If one of those

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Speaker 1: is offset, if it's a little too high or a

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Speaker 1: little too low, it's the same symbol as the first two,

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Speaker 1: but it's not in line, then it doesn't count. Some

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Speaker 1: slot machines allow you to have multiple lines of play

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Speaker 1: so that you can actually have those count, But otherwise

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Speaker 1: there's not really that's not really skill. It's just that

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Speaker 1: you're spending more money for a slightly increased chance of

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Speaker 1: winning something. Um now I say slightly, and even that

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Speaker 1: is a little misleading, because at the heart of a

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Speaker 1: modern slot machine, there's a microchip that determines what result

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Speaker 1: you're going to get, and typically it's based off the

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Speaker 1: exact moment you either pull the lever or you push

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Speaker 1: the button. When you do that, it stops a random

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Speaker 1: number generator or r n G, and that r NGG

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Speaker 1: is just cycling through millions or even billions of numbers

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Speaker 1: for every set, and it's just going super fast. So

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Speaker 1: the moment it stops that number is what determines whether

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Speaker 1: or not you've won. It determines which stop each wheel

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Speaker 1: or reel will hit. So you can think of that

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Speaker 1: real is having numerous stops, some of which correspond to

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Speaker 1: a symbol and some of which correspond to the blank

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Speaker 1: space between symbols, and this random number generator figures out

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Speaker 1: which ones those are for any given spin, and so

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Speaker 1: it determines whether or not you win. In fact, you

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Speaker 1: could technically strip all that other stuff out of a

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Speaker 1: slot machine, the reels, the symbols, all that stuff, all

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Speaker 1: the bells, and whistles. You could just have a random

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Speaker 1: number generator, and you could just have a schedule or

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Speaker 1: a sheet that indicates whether any particular number represents a win,

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Speaker 1: and that would be the same thing, but you lose

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Speaker 1: the theater of slot machines, the presentation, which is part

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Speaker 1: of the appeal. So you could do that where just

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Speaker 1: have a random number of generator. It tells you whether

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Speaker 1: you want or lost, but that's not nearly as sexy

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Speaker 1: as the slot machine. Modern slot machines use a lot

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Speaker 1: of sensory stimuli to kind of entice and reward players. So,

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Speaker 1: as I said, there's no skill in the game, there's

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Speaker 1: not really any way to meaningfully improve your chances. You

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Speaker 1: could boost a payout, but your chance of actually hitting

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Speaker 1: a payout doesn't improve. Um, you could add lines of

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Speaker 1: play and that might move the needle a little bit,

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Speaker 1: but so little that it doesn't make a huge difference.

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Speaker 1: And also, when you pay more money when you do lose,

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Speaker 1: it means you're losing more money on that spend than

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Speaker 1: you would on a regular spend. So how the heck

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Speaker 1: are slot machines even popular if the odds are bad

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Speaker 1: and you know the payouts are rare and it's all

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Speaker 1: based on random number of generators. How can they be

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Speaker 1: so popular? And when I say popular, I mean really popular.

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Speaker 1: If you visit a casino, especially in the United States,

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Speaker 1: they typically slop sans will typically take up about eight

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Speaker 1: percent of the casino floor space on the playing floor,

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Speaker 1: which means that you only have twenty percent reserved for

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Speaker 1: things like table games, like games like black jack and

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Speaker 1: roulette and craps and that kind of stuff. So slot

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Speaker 1: machines dominate the physical space of casinos. They also can

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Speaker 1: account for between seventy to eight percent of the profits

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Speaker 1: for the house. It's big business. There's some regions in

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Speaker 1: the United States where gambling is legal, but the only

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Speaker 1: type of gambling that's allowed our slot machines. So what's

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Speaker 1: going on? How come they're so popular if it's just

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Speaker 1: a random number generator. Well, at the heart of it

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Speaker 1: is the psychology behind playing a slot machine, and it's

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Speaker 1: pretty ingenious and more than a little scary. The psychological

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Speaker 1: design is largely based off the work of a famous

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Speaker 1: psychologist named B. F. Skinner, who heavily researched human behavior.

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Speaker 1: So back in the nineteen thirties, B F. Skinner researched

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Speaker 1: what he was calling operant conditioning. This is a method

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Speaker 1: of learning that relies upon either rewards or punishment for

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Speaker 1: a combination of the two, and the basic principle is

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Speaker 1: pretty darn easy to understand. If a behavior is followed

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Speaker 1: by pleasant consequences, were more likely to engage in that

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Speaker 1: behavior again. If it results in unpleasant consequences, were more

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Speaker 1: likely to avoid engaging in that behavior, which again follows

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Speaker 1: common sense right. If you do something and something good

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Speaker 1: happens as a result, you're more likely to do it again.

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Speaker 1: If you do something and something bad happens to you,

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Speaker 1: you're probably not as eager to try it again. So

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Speaker 1: if I bite into a chocolate bar, I'm going to

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Speaker 1: have the sense of pleasure as I taste the chocolate,

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Speaker 1: and I'm gonna think, oh, I want to do that

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Speaker 1: again in the future. But if I bide into i

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Speaker 1: don't know, an old sneaker, I'm probably not gonna enjoy

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Speaker 1: it very much, and I'm probably not likely to go

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Speaker 1: and do that again in the future. So by the

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Speaker 1: nineteen forties, Skinner developed what he called an operant conditioning box.

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Speaker 1: Just about everyone else uses the term Skinner box, and

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Speaker 1: it was a box that you would put a small

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Speaker 1: animal into, like a rat or a pigeon, and typically

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Speaker 1: would have a lever in the box. UM there would

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Speaker 1: be in the classic skinner box and electric grid on

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Speaker 1: the floor. UM. Some of them would also have speakers,

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Speaker 1: a couple of indicator lights, and a food cup. And

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Speaker 1: he would put animals like pigeons or rats in the

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Speaker 1: box and train them to see how or not even

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Speaker 1: train them, just really letting them learn. Through this method,

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Speaker 1: he wanted to sort out three types of responses that

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Speaker 1: can follow any given behavior. So these responses or operant

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Speaker 1: fall into three categories. There's neutral oprint uh, this has

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Speaker 1: no effect on the probability that a particular behavior would

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Speaker 1: be repeated or not. Then you have reinforcers. This is

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Speaker 1: a type of operant that would encourage behavior repetition and

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Speaker 1: thus increase the probability that the critter inside the box

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Speaker 1: would do whatever that thing was again in the future.

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Speaker 1: And reinforcers can be either positive reinforcers or negative reinforcers.

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Speaker 1: A positive reinforcement encourages repeated behavior in return for a reward. Well,

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Speaker 1: a negative reinforcement encourages repeated behavior by removing something unpleasant.

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Speaker 1: So some people will conflate negative reinforcement with punishment. Those

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Speaker 1: are two different things. Punishment is the third operant. By

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Speaker 1: the way, punishment is where you punish a subject for

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Speaker 1: making the wrong choice, as opposed to rewarding a subject

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Speaker 1: for making the right choice. Negative reinforcement remains removing something

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Speaker 1: unpleasant when the person or a thing makes the correct choice.

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Speaker 1: So for example, let's say that I've got a room

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Speaker 1: and there's a button on a little table in the room,

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Speaker 1: and you are put into the room, and then the

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Speaker 1: ramans are blasting at a very uncomfortable volume, and you

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Speaker 1: want to just have some peace and quiet, and you

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Speaker 1: know that if you push the button it will stop

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Speaker 1: the um the ramons blasting at you. The behavior I'm

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Speaker 1: trying to get you to do is to push the button.

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Speaker 1: So you push the button, the negative stimuli goes away.

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Speaker 1: That's negative reinforcement. Uh, And when it comes back, you

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Speaker 1: push the button again. So now I have essentially trained

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Speaker 1: you on this behavior where you know if you push

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Speaker 1: the button you will prevent having the ramones blasted at you.

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Speaker 1: The positive reinforcement would be you come in, You're in

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Speaker 1: a room, there's a table with a button on it,

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Speaker 1: You push the button and then you get a reward

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Speaker 1: of some sort like a slice of pizza or something.

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Speaker 1: So those are the basic operant categories neutral reinforcers punishment.

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Speaker 1: So a typical experiment when involved putting a hungry rat

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Speaker 1: inside a Skinner box and if the rat were to

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Speaker 1: move the lever, typically it was done accidentally as the

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Speaker 1: rat was just exploring its box. UH. That would cause

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Speaker 1: a pellet of food to fall down a little shoot

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Speaker 1: into the food cup inside the box, and so the

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Speaker 1: rat would then get a food pellet, and before long

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Speaker 1: the rats would learn to associate that moving the lever

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Speaker 1: meant that a food pellet would come down, and so

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Speaker 1: they would start to press the lever again and again

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Speaker 1: in order to get the rewards. Uh. Skinner also did

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Speaker 1: an experiment with negative reinforcement in which he would run

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Speaker 1: a weak current through that electric grid in the box,

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Speaker 1: which would cause the rats to experience discomfort. It wasn't

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Speaker 1: like a strong enough electric current to truly shock the rat,

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Speaker 1: but it was not a pleasant sensation, and hitting the

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Speaker 1: lever would shut off the current for a while. So

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Speaker 1: the rats would learn to hit the lever and turn

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Speaker 1: off the current as quickly as possible. Now that bit

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Speaker 1: doesn't really fall into what we use was lot machines,

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Speaker 1: because as far as I know, casinos aren't using negative

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Speaker 1: reinforcement to keep people playing, at least not yet. However,

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Speaker 1: Skinner then went a step further to learn more about

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Speaker 1: the reinforcement method of learning. He wanted to see what

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Speaker 1: would happen if you were to change the schedule of reinforcement.

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Speaker 1: What happens if you stop dispensing pellets when the rat

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Speaker 1: hits the lever? So first the rat learns that hitting

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Speaker 1: the lever dispenses pellets, Then you stop dispensing pellets. How

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Speaker 1: many times will the rat hit the lever before it

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Speaker 1: gives up, before it realizes that the thing that was

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Speaker 1: working is no longer working and that behavior fades away.

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Speaker 1: How long does it take for it to abandon that behavior.

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Speaker 1: Skinner worked with other behavioral lists to determine things like

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Speaker 1: response rate, which is how frequently an animal like a

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Speaker 1: rat would hit the lever in an effort to get

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Speaker 1: a pellet, and the extinction rate, and that's the rate

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Speaker 1: at which animals would give up if they were not

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Speaker 1: being rewarded. Then, by adjusting the frequencies at which a

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Speaker 1: reward would come out. Skinner and others could determine the

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Speaker 1: balance that would encourage the most work for the slowest

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Speaker 1: rate of extinction. So, in other words, how frequently do

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Speaker 1: you need to dispense a reward so that the rat

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Speaker 1: doesn't give up and is incentivized to continue engaging in

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Speaker 1: that behavior. Skinner discovered that the best approach was to

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Speaker 1: use a variable ratio method, meaning there was no set

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Speaker 1: number of lever pushes needed between rewards. It would change.

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Speaker 1: So it might be that the first time you hit

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Speaker 1: the lever you get a pellet. Then you have to

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Speaker 1: hit the lever four more times before the next pellet

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Speaker 1: comes out. Then two times and another pellet comes out,

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Speaker 1: then three times and another pellet comes out. And they

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Speaker 1: found that by using this variable ratio approach, you could

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Speaker 1: extend the amount of time that the animal would engage

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Speaker 1: in the behavior you wanted it to do. Now, I

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Speaker 1: would like to tell you that we human beings are

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Speaker 1: better than rats, but as it turns out that it's

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Speaker 1: not true. We humans behave the same way, and that's

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Speaker 1: what the design of slot machines is ultimately predicated upon.

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Speaker 1: A slot machine promises payouts. In fact, a lot of

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Speaker 1: slot machines in casinos have a payout rate of or more, meaning,

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Speaker 1: over the life span of the slot machine, it will

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Speaker 1: pay out about of the money it takes in in

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Speaker 1: the long run. But the key phrase of that is

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Speaker 1: in the long run, not in a play session. Over

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Speaker 1: the entire lifetime of the slot machine, the likelihood of

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Speaker 1: any one spin resulting in a jackpot is very low.

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Speaker 1: It could be just a fraction of a fraction of

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Speaker 1: a percentage point. Lower payouts have better odds, and if

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Speaker 1: you sit at a slot machine long enough, you're likely

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Speaker 1: to at least get a low payout hit. Now, that

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Speaker 1: hit might not be enough to offset the amount of

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Speaker 1: money you poured into the machine. In fact, more often

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Speaker 1: than not it won't be, but it could be enough

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Speaker 1: to keep you playing the game, and that's the rub.

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Speaker 1: Here are a couple of other tricks that slot machines

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Speaker 1: used in order to keep you playing the game. The

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Speaker 1: odds of a specific combination coming up depends in part

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Speaker 1: on how many of the corresponding symbols there are on

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Speaker 1: the stops of each wheel or reel in that machine.

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Speaker 1: So let's say you've gotten old fashioned three real slot machine.

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Speaker 1: It's a physical one. You've got these three wheels, uh,

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Speaker 1: and on that outer edge you've got the symbols on them.

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Speaker 1: And the symbols include things like cherries and oranges and

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Speaker 1: the good old bar sign. And let's say that the

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Speaker 1: the jackpot symbol is a bag of money. It's got

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Speaker 1: a bag and a little dollar symbol on it, and

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Speaker 1: that represents the really big jackpot. Each reel also has

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Speaker 1: a number of stops on it, and these are all

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Speaker 1: the possible positions the real could be and when it

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Speaker 1: stops rotating, which is completely determined by that microchip. Some

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Speaker 1: of those stops have a symbol associated with them, you know,

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Speaker 1: a cherry or an orange or the bag of money.

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Speaker 1: Some of the stops actually represent the blank space between

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Speaker 1: symbols on the reel. So let's say our machine has

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Speaker 1: fifty stops per real, so each reel could stop in

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Speaker 1: one of fifty different configurations. The bag of money represents

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Speaker 1: just one stop on each of the three reels. So

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Speaker 1: you do have a bag of money on real one,

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Speaker 1: Reel two, and Real three, but you have forty nine

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Speaker 1: other things on those reels as well. So what are

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Speaker 1: the odds that you would hit all three of those well,

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Speaker 1: it's one out of fifty times one out of fifty

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Speaker 1: times one out of fifty and then multiplying by a

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Speaker 1: hundred to get the percentage, which comes out to point

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Speaker 1: zero zero zero eight chance. That's the chance you have

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Speaker 1: of hitting the jackpot. Not great odds. But we're not

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Speaker 1: done yet. I'll explain more in just a second, but

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Speaker 1: first let's take a quick break. All right. So I

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Speaker 1: mentioned earlier that the big jackpot might have a really

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Speaker 1: low likelihood of popping up. But slot machine manufacturers have

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Speaker 1: come up with ways to avoid discouraging players. They built

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Speaker 1: in systems that would make it more likely that that

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Speaker 1: bag of money symbol, for example, might appear lined up

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Speaker 1: on the first two reels more frequently, which gives the

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Speaker 1: player the sense of a near miss. So you get

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Speaker 1: a bag of money, a bag of money, and oh,

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Speaker 1: shoot cherries or a blank spot. That's nothing right there.

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Speaker 1: There's no payout with that, but it feels like it

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Speaker 1: was almost something because you had two out of the

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Speaker 1: three bags you needed to hit the jackpot. It's like

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Speaker 1: you almost got that big payout, but in reality, you

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Speaker 1: didn't almost do anything at all. You've got a result

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Speaker 1: based on a random number generator in the machines circuitry

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Speaker 1: that amounted to a loss. The way the machine displayed

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Speaker 1: that loss to you was in a way that made

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Speaker 1: it seem like it was almost a win. So to us,

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Speaker 1: it feels like we near really grabbed that brass ring,

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Speaker 1: so if we just stick at it, we're gonna get it. Meanwhile,

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Speaker 1: other symbols might take up far more space on the reels,

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Speaker 1: symbols that would result in a much lower payout, thus

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Speaker 1: increasing the likelihood that you'll at least get some combination

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Speaker 1: that represents a more modest wind if you play long enough.

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Speaker 1: At least that's the way it looks on the outside right,

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Speaker 1: that the odds of hitting a low payout might be

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Speaker 1: closer to So we get two types of rewards. One

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Speaker 1: are of these small payouts, which, if the machine is

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Speaker 1: working properly, tends to be less than what we've poured

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Speaker 1: into the machine in the first place, or at least

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Speaker 1: the payout is less than what the machine has been

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Speaker 1: collecting for that day. And another are these near misses

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Speaker 1: that make us feel like we're getting closer to that goal. Now.

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Speaker 1: Once in a blue moon, these machines will do the

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Speaker 1: jackpot payout Uh, that's part of what keeps people playing

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Speaker 1: these games is the promise that it can happen, but

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Speaker 1: it doesn't happen freak ly. The odds alone tell you

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Speaker 1: that it's pretty rare. Now, in addition to all that,

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Speaker 1: we humans are also really good at recognizing patterns. This

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Speaker 1: becomes more important with video slot machines. In fact, we're

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Speaker 1: so good at recognizing patterns we will frequently perceive a

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Speaker 1: pattern where there is no pattern, or at least no

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Speaker 1: pattern that has been consciously created. So, for example, when

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Speaker 1: you look at clouds and you see faces in them

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Speaker 1: or other complex shapes, that's your brain applying a pattern

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Speaker 1: to something that is actually random and not ordered. With

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Speaker 1: slot machines, we're looking at the creation of patterns. Three

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Speaker 1: symbols in a row would be a pattern. So there's

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Speaker 1: another little psychological boost that keeps us playing even if

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Speaker 1: we're not in a lucky streak, because we're looking for

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Speaker 1: those patterns. We find that very satisfying. Now, there are

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Speaker 1: a lot of people who give advice on how to

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Speaker 1: play slot machines well, but at the very end of

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Speaker 1: the day, you have to acknowledge the slot machines are

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Speaker 1: designed to take money. There's no way to skillfully play

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Speaker 1: a slot machine. You can use some wisdom to help

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Speaker 1: pick out machines that might have more favorable odds for

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Speaker 1: a payout, but those odds are are favorable because they

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00:23:07,320 --> 00:23:11,920
Speaker 1: ultimately benefit the house. You have very few decisions when

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Speaker 1: it comes to playing a slot machine, and generally speaking,

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Speaker 1: in house games, in casino games, gambling games, you narrow

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Speaker 1: the odds between you and the house in those games

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Speaker 1: where you have more options as a player, assuming that

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Speaker 1: you are pursuing optimal play, that you're playing without mistakes.

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00:23:30,359 --> 00:23:32,959
Speaker 1: That's asking a lot because optimal play is a pretty

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00:23:32,960 --> 00:23:36,239
Speaker 1: tough skill to develop. But with slot machines, there's not

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Speaker 1: really much you can optimize, so you're not really going

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Speaker 1: to narrow those odds very much. Now, in addition to

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Speaker 1: all I've just said are the more flashy slot machines

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Speaker 1: that have come out over the last couple of decades.

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Speaker 1: Many of these include using licensed i P to attract

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Speaker 1: players to them. So if you walk around a modern casino,

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Speaker 1: you're gonna see a lot of slot machines that are

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00:23:56,440 --> 00:24:01,080
Speaker 1: modeled after licensed material there licensed from popular movies like

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Speaker 1: the Lord of the Rings franchise. That's one that my

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00:24:03,000 --> 00:24:07,359
Speaker 1: friends Shannon really likes, or television shows like the series Friends.

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Speaker 1: These machines frequently include music and video clips to help

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Speaker 1: lure people over to play them there they're more demographically

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Speaker 1: aligned to capture certain types of people, and then the

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00:24:20,119 --> 00:24:23,320
Speaker 1: gameplay is what keeps them there. Um. They might also

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Speaker 1: include bonus features that make the game more exciting to

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Speaker 1: play without significantly increasing the likelihood of a big payout. Okay,

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00:24:30,359 --> 00:24:33,120
Speaker 1: so I've covered the psychology of slot machines, So why

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Speaker 1: did I spend so much time on that. It's because

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Speaker 1: many developers of both software platforms and apps rely upon

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Speaker 1: those same sort of designs when they're creating their work.

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Speaker 1: They designed the experience to have that same sort of

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Speaker 1: reward system for users, and that encourages users to spend

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00:24:49,280 --> 00:24:53,560
Speaker 1: more time on the platform, which ultimately benefits the developer

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Speaker 1: in some way. Now, that way could be through advertising.

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Speaker 1: If you go to advertisers with data a out how

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Speaker 1: many users you have and the average amount of time

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00:25:03,320 --> 00:25:06,520
Speaker 1: those users spend per day on your product, you've got

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Speaker 1: a pretty powerful tool in your sales toolbox. If you've

433
00:25:10,000 --> 00:25:12,280
Speaker 1: got a lot of users that use A that spend

434
00:25:12,320 --> 00:25:14,080
Speaker 1: a lot of time on your on your platform, you

435
00:25:14,080 --> 00:25:17,520
Speaker 1: can ask for better rates, and you can get better sponsors,

436
00:25:17,560 --> 00:25:20,320
Speaker 1: and you can assure those sponsors that people using your

437
00:25:20,359 --> 00:25:23,120
Speaker 1: services are spending more time doing that and less time

438
00:25:23,119 --> 00:25:27,960
Speaker 1: doing other things. So advertisers one eyeballs, right, if the

439
00:25:27,960 --> 00:25:31,200
Speaker 1: eyeballs are all on your app, they're not other places,

440
00:25:31,240 --> 00:25:33,360
Speaker 1: So they want to be where the eyeballs are. That's

441
00:25:33,400 --> 00:25:35,879
Speaker 1: your app. So it gives you a lot more leverage,

442
00:25:35,920 --> 00:25:39,680
Speaker 1: and it allows you to have much better rates, sales rates.

443
00:25:39,880 --> 00:25:41,880
Speaker 1: You're gonna make a lot more money, So you've got

444
00:25:41,880 --> 00:25:44,720
Speaker 1: a really strong incentive to encourage people to look at

445
00:25:44,760 --> 00:25:47,879
Speaker 1: your app or service for a long time and not

446
00:25:48,359 --> 00:25:51,720
Speaker 1: at other stuff. Another possibility is that maybe you're using

447
00:25:51,760 --> 00:25:55,280
Speaker 1: pay for content or pay for elements in your service,

448
00:25:55,800 --> 00:25:57,879
Speaker 1: and this could be done in place of or in

449
00:25:58,000 --> 00:26:02,680
Speaker 1: conjunction with advertising. A lot of mobile games use this method.

450
00:26:02,880 --> 00:26:04,920
Speaker 1: You play the game and you make a little progress,

451
00:26:05,200 --> 00:26:08,280
Speaker 1: so you receive that little psychological reward for achieving things

452
00:26:08,280 --> 00:26:11,040
Speaker 1: in the game, little dopamine going through your system. But

453
00:26:11,119 --> 00:26:13,920
Speaker 1: sooner or later you hit a barrier, maybe you run

454
00:26:13,920 --> 00:26:16,480
Speaker 1: out of turns or lives in a game. Maybe you

455
00:26:16,520 --> 00:26:18,480
Speaker 1: need a boost to get past a certain point in

456
00:26:18,520 --> 00:26:22,520
Speaker 1: the game. Whatever the case, you typically have two options

457
00:26:22,520 --> 00:26:26,040
Speaker 1: in most of these types of games. One is that

458
00:26:26,240 --> 00:26:28,600
Speaker 1: you wait a given amount of time before you can

459
00:26:28,640 --> 00:26:32,199
Speaker 1: try again, with no guarantee of success. So you might

460
00:26:32,240 --> 00:26:34,680
Speaker 1: have to wait thirty minutes or an hour before you

461
00:26:34,720 --> 00:26:36,840
Speaker 1: can try again and you aren't sure if you're gonna

462
00:26:36,920 --> 00:26:39,960
Speaker 1: make any progress. Option two is that you can pay

463
00:26:40,000 --> 00:26:43,680
Speaker 1: some money and in return you get immediate gratification, either

464
00:26:43,720 --> 00:26:46,840
Speaker 1: you get more turns or lives, or maybe some sort

465
00:26:46,840 --> 00:26:49,160
Speaker 1: of in game asset that makes it easier to get

466
00:26:49,200 --> 00:26:51,679
Speaker 1: beyond that part of the game. Now, this isn't just

467
00:26:51,760 --> 00:26:54,400
Speaker 1: something we see in mobile games. It's how the business

468
00:26:54,440 --> 00:26:57,920
Speaker 1: model of shareware works too. When I was in high school,

469
00:26:58,400 --> 00:27:03,000
Speaker 1: games like Castle Wolfenstein re D used that model. Developers

470
00:27:03,000 --> 00:27:05,639
Speaker 1: would release the first level or the first part of

471
00:27:05,680 --> 00:27:08,200
Speaker 1: a game for free so you could easily get your

472
00:27:08,240 --> 00:27:10,960
Speaker 1: hands on that version and you could play through to

473
00:27:11,040 --> 00:27:14,040
Speaker 1: your heart's content, and when you reach the end of

474
00:27:14,080 --> 00:27:16,960
Speaker 1: whatever that free section was, you would typically get a

475
00:27:17,000 --> 00:27:19,199
Speaker 1: message that would encourage you to purchase the rest of

476
00:27:19,200 --> 00:27:21,479
Speaker 1: the game if you enjoyed what you had done. And

477
00:27:21,520 --> 00:27:23,640
Speaker 1: it was an effective tool and one that a lot

478
00:27:23,640 --> 00:27:25,720
Speaker 1: of gamers actually approved of because it gave them a

479
00:27:25,800 --> 00:27:28,840
Speaker 1: chance to try out a game before committing real money

480
00:27:28,880 --> 00:27:31,960
Speaker 1: to it, and if the game was good, many people

481
00:27:32,000 --> 00:27:34,320
Speaker 1: were willing to cough up the cash to get the rest.

482
00:27:34,640 --> 00:27:37,119
Speaker 1: So while the shareware model followed a bit in the

483
00:27:37,119 --> 00:27:41,320
Speaker 1: wake of Skinner's work, it wasn't seen as predatory because

484
00:27:41,640 --> 00:27:44,160
Speaker 1: you could just say like, well, you know, I played it.

485
00:27:44,160 --> 00:27:46,720
Speaker 1: It didn't really impress me. I'm going to walk away.

486
00:27:46,960 --> 00:27:50,240
Speaker 1: Now that's not necessarily the case with apps and services

487
00:27:50,280 --> 00:27:53,480
Speaker 1: that are popular today, whether it's the algorithm that serves

488
00:27:53,560 --> 00:27:57,080
Speaker 1: up a feed of content on a social platform cough

489
00:27:57,320 --> 00:28:01,840
Speaker 1: Facebook cough, or the propensity of game features like looped

490
00:28:01,880 --> 00:28:05,359
Speaker 1: crates that became incredibly pervasive. Over the last couple of years.

491
00:28:05,600 --> 00:28:10,439
Speaker 1: We've seen developers exploit the same behavioral tendency, and we

492
00:28:10,520 --> 00:28:14,800
Speaker 1: as consumers, have engaged in those behaviors again and again,

493
00:28:15,040 --> 00:28:19,640
Speaker 1: just as predictably as the rats in Skinners experiments. Now,

494
00:28:19,640 --> 00:28:22,719
Speaker 1: this also plays into the larger concept of game theory.

495
00:28:23,000 --> 00:28:27,240
Speaker 1: How do you balance out different factors to maximize engagement

496
00:28:27,760 --> 00:28:32,159
Speaker 1: with games? Developers have to balance challenges and rewards carefully.

497
00:28:32,400 --> 00:28:35,560
Speaker 1: If a game is too easy, players may become bored

498
00:28:35,680 --> 00:28:38,640
Speaker 1: and move on to something else. If it's too challenging,

499
00:28:38,880 --> 00:28:42,040
Speaker 1: they become frustrated and they won't stick with it. So

500
00:28:42,120 --> 00:28:44,440
Speaker 1: it needs to be challenging enough to the player so

501
00:28:44,480 --> 00:28:46,400
Speaker 1: that when they win a game or achieve a goal,

502
00:28:46,480 --> 00:28:49,240
Speaker 1: there's a sense of accomplishment, and this needs to be

503
00:28:49,360 --> 00:28:52,479
Speaker 1: repeatable to keep the experience going. The same theory can

504
00:28:52,520 --> 00:28:56,040
Speaker 1: be applied to other stuff, not just too explicit games.

505
00:28:56,080 --> 00:29:00,000
Speaker 1: So let's take Tender for example. The dating app Share

506
00:29:00,040 --> 00:29:02,960
Speaker 1: is a lot in common with slot machines. Users flick

507
00:29:03,040 --> 00:29:07,240
Speaker 1: through photos of other users, swiping left or right, and

508
00:29:07,240 --> 00:29:10,960
Speaker 1: there's a quick psychological reward. Either you find someone attractive

509
00:29:11,200 --> 00:29:14,120
Speaker 1: or you don't, and you pass judgment, then you move on.

510
00:29:14,640 --> 00:29:17,320
Speaker 1: So if that person has similarly passed judgment upon you

511
00:29:17,360 --> 00:29:20,040
Speaker 1: and found you attractive, and you found them attractive, then

512
00:29:20,080 --> 00:29:23,960
Speaker 1: you can connect. All the elements are there. And I'm

513
00:29:23,960 --> 00:29:26,880
Speaker 1: not getting on a high horse here. I'm as guilty,

514
00:29:27,160 --> 00:29:30,800
Speaker 1: or probably even more guilty than any of you guys

515
00:29:30,800 --> 00:29:33,760
Speaker 1: out there. I find myself having to be mindful to

516
00:29:33,960 --> 00:29:37,600
Speaker 1: not be actively using some device that's got a screen

517
00:29:37,680 --> 00:29:40,959
Speaker 1: on it. Otherwise that's where you're gonna find me, is

518
00:29:41,120 --> 00:29:44,120
Speaker 1: behind a screen. I try to make rules for myself,

519
00:29:44,360 --> 00:29:46,320
Speaker 1: and they are hard for me to follow because I'm

520
00:29:46,360 --> 00:29:49,800
Speaker 1: pretty darn addicted to screens. It takes effort for me

521
00:29:49,880 --> 00:29:52,120
Speaker 1: to not whip out my phone as soon as I

522
00:29:52,120 --> 00:29:54,280
Speaker 1: sit down to eat, for example, or if I'm in

523
00:29:54,360 --> 00:29:57,240
Speaker 1: line anywhere, I want my phone out in my hand.

524
00:29:57,600 --> 00:30:00,200
Speaker 1: But even when I'm at home, I'm usually either are

525
00:30:00,200 --> 00:30:03,480
Speaker 1: playing a game or watching something online. I have numerous

526
00:30:03,520 --> 00:30:06,160
Speaker 1: tabs open all the time in my browsers. I play

527
00:30:06,240 --> 00:30:09,000
Speaker 1: some mobile games that are definitely built on top of

528
00:30:09,000 --> 00:30:12,000
Speaker 1: this understanding of human behavior, and I find myself growing

529
00:30:12,040 --> 00:30:15,800
Speaker 1: more disenchanted with it overall. And we're starting to see

530
00:30:15,800 --> 00:30:19,480
Speaker 1: a bit of backlash against this trend in broader culture.

531
00:30:19,840 --> 00:30:25,720
Speaker 1: This includes articles, books, public speaking engagements, politicians, activist organizations,

532
00:30:25,760 --> 00:30:28,520
Speaker 1: and more. There are lots of articles out there pointing

533
00:30:28,520 --> 00:30:31,280
Speaker 1: out our tendency to spend more time in front of screens.

534
00:30:31,640 --> 00:30:34,720
Speaker 1: A recent article in The Chicago Tribune cited a study

535
00:30:34,760 --> 00:30:38,600
Speaker 1: conducted by a nonprofit group called Common Sense Media that

536
00:30:38,720 --> 00:30:42,840
Speaker 1: found US teenagers are spending about nine hours each day

537
00:30:43,040 --> 00:30:46,440
Speaker 1: on some sort of digital media, and adults. Don't feel

538
00:30:46,440 --> 00:30:50,360
Speaker 1: good about yourselves because we're even more extreme eleven hours

539
00:30:50,440 --> 00:30:54,120
Speaker 1: per day devoted to screen time. Now, this prompts us

540
00:30:54,120 --> 00:30:56,680
Speaker 1: to ask the question, is that much time in front

541
00:30:56,680 --> 00:31:00,280
Speaker 1: of screens harmful to us? Should we be concerned that

542
00:31:00,320 --> 00:31:03,840
Speaker 1: we're dedicating so many waking hours to interacting with digital

543
00:31:03,880 --> 00:31:07,760
Speaker 1: media that it is encouraging this behavior and rewarding us

544
00:31:08,160 --> 00:31:12,040
Speaker 1: in psychological ways for engaging in it. Could we actually

545
00:31:12,080 --> 00:31:15,600
Speaker 1: be hurting ourselves and each other through these practices. Now,

546
00:31:15,640 --> 00:31:17,840
Speaker 1: as it turns out, there are a lot of people

547
00:31:17,880 --> 00:31:20,760
Speaker 1: who have stuff to say about this particular set of ideas,

548
00:31:21,040 --> 00:31:24,120
Speaker 1: and as you might imagine, the responses range from well,

549
00:31:24,120 --> 00:31:26,880
Speaker 1: of course, this is dangerous and harmful behavior and we

550
00:31:26,920 --> 00:31:29,520
Speaker 1: need to do something about it, to a more cautious

551
00:31:29,520 --> 00:31:32,880
Speaker 1: statement like, we honestly don't have enough empirical evidence to

552
00:31:32,880 --> 00:31:36,400
Speaker 1: support any sort of conclusion on the matter. So as

553
00:31:36,400 --> 00:31:39,040
Speaker 1: tempting as it is to come to one, the responsible

554
00:31:39,040 --> 00:31:41,440
Speaker 1: thing to say is we don't know enough yet. So

555
00:31:41,440 --> 00:31:44,240
Speaker 1: in our next section will dive into some of those arguments,

556
00:31:44,360 --> 00:31:46,760
Speaker 1: and some of them will appeal to common sense, But

557
00:31:46,800 --> 00:31:50,440
Speaker 1: it's good to remember that common sense isn't always right.

558
00:31:51,120 --> 00:31:53,320
Speaker 1: Sometimes we'll draw a conclusion because we all see a

559
00:31:53,360 --> 00:31:58,080
Speaker 1: correlation that ends up being impossible to support upon further study. Remember,

560
00:31:58,480 --> 00:32:02,440
Speaker 1: correlation and causation are not the same thing. Sometimes the

561
00:32:02,520 --> 00:32:07,160
Speaker 1: correlation can indicate a causal sort of relationship between two things,

562
00:32:07,600 --> 00:32:09,920
Speaker 1: but it's not always the case. So when we come

563
00:32:09,960 --> 00:32:13,360
Speaker 1: back from this break, we'll look further into this issue

564
00:32:13,640 --> 00:32:24,440
Speaker 1: and we'll be right back. Okay, So it's pretty clear

565
00:32:24,560 --> 00:32:28,280
Speaker 1: people are spending more time with digital medium than ever before,

566
00:32:28,600 --> 00:32:31,760
Speaker 1: and if we're dedicating time to those screens, we might

567
00:32:31,840 --> 00:32:35,320
Speaker 1: also be taking time away from other tasks. So at

568
00:32:35,360 --> 00:32:39,080
Speaker 1: some level you could argue that spending time on digital

569
00:32:39,120 --> 00:32:42,160
Speaker 1: media can have a negative impact if we're neglecting real

570
00:32:42,200 --> 00:32:45,800
Speaker 1: world issues while we are engaged in the digital world.

571
00:32:46,280 --> 00:32:50,560
Speaker 1: But to make that argument convincingly, we need more data. Further,

572
00:32:51,120 --> 00:32:53,800
Speaker 1: there are many who might argue that because we're spending

573
00:32:53,840 --> 00:32:57,040
Speaker 1: so much time on digital media, we're hurting our own

574
00:32:57,080 --> 00:33:00,320
Speaker 1: ability to form meaningful connections with other people in the

575
00:33:00,320 --> 00:33:03,840
Speaker 1: real world. There's a growing concern that we're relying more

576
00:33:03,920 --> 00:33:08,080
Speaker 1: on online interactions than ones in a physical space, and

577
00:33:08,120 --> 00:33:11,440
Speaker 1: we're seeing it reflected in multiple behaviors, such as relying

578
00:33:11,480 --> 00:33:15,480
Speaker 1: more heavily on text and essueing phone calls. Most of

579
00:33:15,480 --> 00:33:18,400
Speaker 1: the people I know will not answer the phone, even

580
00:33:18,400 --> 00:33:20,520
Speaker 1: if they know who it's coming from. They would rather

581
00:33:20,600 --> 00:33:25,000
Speaker 1: just have a text. They actively avoid having to talk

582
00:33:25,040 --> 00:33:28,320
Speaker 1: on the phone. It's a social interaction that they don't

583
00:33:28,360 --> 00:33:31,960
Speaker 1: want to have. So we're choosing interactions that don't connect

584
00:33:32,040 --> 00:33:35,880
Speaker 1: us with each other in more traditional ways and arguably

585
00:33:35,920 --> 00:33:39,040
Speaker 1: more meaningful ways. But the jury is still out over

586
00:33:39,120 --> 00:33:44,080
Speaker 1: whether or not this constitutes actual harmful behavior. Is an

587
00:33:44,160 --> 00:33:49,520
Speaker 1: online relationship less meaningful or emotionally fulfilling as one done

588
00:33:49,560 --> 00:33:52,720
Speaker 1: in real space? Can we even draw any sort of

589
00:33:52,760 --> 00:33:56,040
Speaker 1: conclusion about that in general or does it depend upon

590
00:33:56,160 --> 00:33:59,520
Speaker 1: the actual situations and individuals involved On a case by

591
00:33:59,560 --> 00:34:02,600
Speaker 1: case Base says it may be that we cannot make

592
00:34:02,640 --> 00:34:07,800
Speaker 1: a generalization about the health of an online relationship versus

593
00:34:07,920 --> 00:34:13,759
Speaker 1: and a meat space relationship. Now, from an armchair psychology standpoint,

594
00:34:14,239 --> 00:34:17,080
Speaker 1: you could argue that the online world has deprived us

595
00:34:17,160 --> 00:34:19,800
Speaker 1: of a sense of intimacy that we tend to crave.

596
00:34:20,080 --> 00:34:24,680
Speaker 1: And I'm not speaking solely of romantic intimacy, though that

597
00:34:24,880 --> 00:34:28,600
Speaker 1: can play apart two. Rather, I'm talking about the intimate

598
00:34:28,640 --> 00:34:32,080
Speaker 1: connection between two people in a one on one interaction,

599
00:34:32,640 --> 00:34:36,480
Speaker 1: not a romantic intimacy, but just a human connection. It

600
00:34:36,600 --> 00:34:40,400
Speaker 1: is very tempting to argue that the rise and popularity

601
00:34:40,440 --> 00:34:43,600
Speaker 1: of things like a S m R style videos in

602
00:34:43,640 --> 00:34:46,759
Speaker 1: which a creator focuses their attention on the viewer in

603
00:34:46,840 --> 00:34:50,920
Speaker 1: some way in an effort to soothe, relax or tingle

604
00:34:51,239 --> 00:34:54,880
Speaker 1: that person, is evidence that we in general lack the

605
00:34:55,040 --> 00:34:57,640
Speaker 1: sort of connections in our day to day lives. We

606
00:34:58,320 --> 00:35:02,520
Speaker 1: crave that connection and that we're not getting and that

607
00:35:02,560 --> 00:35:06,120
Speaker 1: has given birth to an entire genre of videos that

608
00:35:06,160 --> 00:35:10,600
Speaker 1: have become incredibly popular over the last five years. If

609
00:35:10,600 --> 00:35:13,120
Speaker 1: you do a quick search on YouTube for the terms

610
00:35:13,320 --> 00:35:18,120
Speaker 1: personal attention, you're going to find thousands of videos catering

611
00:35:18,320 --> 00:35:21,600
Speaker 1: to that audience. These videos tend to feature one or

612
00:35:21,640 --> 00:35:25,560
Speaker 1: more creators speaking to the camera and microphones as they

613
00:35:25,600 --> 00:35:28,799
Speaker 1: serve as a stand in for the viewer, so they

614
00:35:28,800 --> 00:35:31,880
Speaker 1: are simulating the sort of interactions people would otherwise have

615
00:35:32,200 --> 00:35:36,160
Speaker 1: in real spaces. It's possible that the popularity of this

616
00:35:36,360 --> 00:35:39,959
Speaker 1: genre is in part due to a decline in such

617
00:35:40,080 --> 00:35:44,080
Speaker 1: meaningful interactions happening in the real world, but without an

618
00:35:44,120 --> 00:35:49,200
Speaker 1: actual study investigating the matter, it's not scientifically responsible to

619
00:35:49,280 --> 00:35:52,160
Speaker 1: make that claim. You could say, I suspect I have

620
00:35:52,200 --> 00:35:56,400
Speaker 1: a hypothesis that this is because of that, but until

621
00:35:56,480 --> 00:35:59,480
Speaker 1: I test it, I cannot really be certain. Also, these

622
00:35:59,520 --> 00:36:03,880
Speaker 1: sort of end up being very tricky to arrange because

623
00:36:04,600 --> 00:36:07,440
Speaker 1: there are a lot of potential variables that could affect

624
00:36:07,520 --> 00:36:12,080
Speaker 1: the outcome, and isolating all those variables is notoriously difficult

625
00:36:12,120 --> 00:36:14,880
Speaker 1: to do. In these sort of social uh survey and

626
00:36:15,000 --> 00:36:19,359
Speaker 1: social scientific studies, they're very very challenging. It's much more

627
00:36:19,440 --> 00:36:23,799
Speaker 1: challenging than say, taking a substance and saying is this flammable?

628
00:36:23,880 --> 00:36:26,960
Speaker 1: That's pretty easy claim to test. These sort of claims

629
00:36:27,120 --> 00:36:30,360
Speaker 1: much trickier. Now. We might also draw the conclusion that

630
00:36:30,440 --> 00:36:33,640
Speaker 1: all this technology is hurting our ability to focus on

631
00:36:33,719 --> 00:36:37,359
Speaker 1: specific tasks and interactions. When our world is filled with

632
00:36:37,360 --> 00:36:41,480
Speaker 1: notifications and demands for our attention, are we giving anything

633
00:36:41,640 --> 00:36:44,840
Speaker 1: our full focus at any given time or are we scattered?

634
00:36:45,400 --> 00:36:47,960
Speaker 1: There are a lot of articles suggesting that that's the case,

635
00:36:48,000 --> 00:36:51,480
Speaker 1: that we're not capable of really focusing on things anymore,

636
00:36:51,800 --> 00:36:55,360
Speaker 1: though again, few studies really back up this claim, And

637
00:36:55,400 --> 00:36:57,239
Speaker 1: I should also point out that this doesn't mean the

638
00:36:57,280 --> 00:37:00,880
Speaker 1: claim is false, That just because it's not yet supported

639
00:37:00,880 --> 00:37:04,440
Speaker 1: by scientific research doesn't mean it's wrong. It just means

640
00:37:04,520 --> 00:37:07,759
Speaker 1: we can't be certain. You can make a claim and

641
00:37:07,840 --> 00:37:10,359
Speaker 1: not have evidence, and you can end up being right,

642
00:37:11,120 --> 00:37:13,600
Speaker 1: but you have to have the evidence to prove whether

643
00:37:13,680 --> 00:37:16,680
Speaker 1: or not you're right. People who follow me outside of

644
00:37:16,680 --> 00:37:18,799
Speaker 1: tech stuff might know that I used to do a

645
00:37:18,840 --> 00:37:22,799
Speaker 1: show called Podcast Without Pretense with my co hosts Eric

646
00:37:22,880 --> 00:37:26,320
Speaker 1: Sandean and I as actar, and the show gradually evolved

647
00:37:26,320 --> 00:37:30,520
Speaker 1: into a sort of jokey experiment. Each week, one of

648
00:37:30,600 --> 00:37:34,000
Speaker 1: us would pick a movie, usually a really poorly reviewed

649
00:37:34,239 --> 00:37:37,840
Speaker 1: film that we could watch on a streaming service like Netflix,

650
00:37:38,280 --> 00:37:41,239
Speaker 1: and then we would set time aside to watch the movie.

651
00:37:41,280 --> 00:37:43,799
Speaker 1: Each of us would make time in the week to

652
00:37:43,880 --> 00:37:46,920
Speaker 1: try and watch the movie, and the rule was you

653
00:37:47,040 --> 00:37:50,440
Speaker 1: could not have any distractions present while you tried to

654
00:37:50,440 --> 00:37:54,800
Speaker 1: watch the film. No second screens, no smartphones out, no laptops,

655
00:37:54,880 --> 00:37:58,080
Speaker 1: nothing like that. It was just you and the movie.

656
00:37:58,480 --> 00:38:00,920
Speaker 1: And then we'd each write down how long into the

657
00:38:00,960 --> 00:38:04,600
Speaker 1: film we lasted before we either grabbed a second screen

658
00:38:04,960 --> 00:38:07,200
Speaker 1: because we didn't want to pay full attention to the

659
00:38:07,200 --> 00:38:10,680
Speaker 1: film anymore, or we just gave up entirely and turned

660
00:38:10,680 --> 00:38:13,759
Speaker 1: the film off, which happened more rarely than you would think.

661
00:38:13,840 --> 00:38:15,560
Speaker 1: Usually we would just give up and grab a second

662
00:38:15,560 --> 00:38:18,560
Speaker 1: screen and keep on going. Now, this was in reaction

663
00:38:18,880 --> 00:38:22,319
Speaker 1: to that same feeling that our dependence on technology meant

664
00:38:22,320 --> 00:38:24,760
Speaker 1: that when we do something like try and watch a show,

665
00:38:25,400 --> 00:38:28,160
Speaker 1: we'd have another screen open at the same time, and

666
00:38:28,200 --> 00:38:32,160
Speaker 1: it would leave us feeling like we hadn't really watched anything,

667
00:38:32,360 --> 00:38:34,520
Speaker 1: that we were just sort of there while it was happening.

668
00:38:34,920 --> 00:38:37,200
Speaker 1: So this was sort of us testing our ability to

669
00:38:37,239 --> 00:38:40,440
Speaker 1: focus on a topic even if that topic didn't deserve

670
00:38:40,520 --> 00:38:44,080
Speaker 1: our attention, and dedicate all of our attention to it,

671
00:38:44,640 --> 00:38:49,839
Speaker 1: and it wasn't easy, even when the films weren't absolutely awful. Similarly,

672
00:38:50,239 --> 00:38:53,719
Speaker 1: claims that screen time is harmful in of itself, while

673
00:38:53,760 --> 00:38:56,480
Speaker 1: appealing on a common sense level, haven't had a lot

674
00:38:56,480 --> 00:38:59,680
Speaker 1: of critical scientific study. It's a challenging thing to explore.

675
00:39:00,000 --> 00:39:02,440
Speaker 1: You might see a rise in screen time and a

676
00:39:02,480 --> 00:39:06,120
Speaker 1: similar trend in people seeking help to treat depression, so

677
00:39:06,200 --> 00:39:10,720
Speaker 1: that is attempting connection there. But does that mean people

678
00:39:10,760 --> 00:39:14,040
Speaker 1: are becoming more depressed as they spend more time interacting

679
00:39:14,040 --> 00:39:17,720
Speaker 1: with screens or could it mean that depressed people seek

680
00:39:17,760 --> 00:39:21,000
Speaker 1: out screens as a means to help alleviate their depression.

681
00:39:21,640 --> 00:39:24,840
Speaker 1: One does not necessarily cause the other, and it could

682
00:39:24,840 --> 00:39:27,719
Speaker 1: be that both trends have no meaningful connection at all.

683
00:39:27,760 --> 00:39:30,400
Speaker 1: They're both on the rise, but maybe they both stem

684
00:39:30,480 --> 00:39:35,200
Speaker 1: from a common source that doesn't have a connection between

685
00:39:35,239 --> 00:39:38,600
Speaker 1: the two. Now, I say all this to remind myself

686
00:39:38,680 --> 00:39:41,160
Speaker 1: just as much to remind all you that these are

687
00:39:41,200 --> 00:39:44,879
Speaker 1: complicated issues. I have my own opinions, which typically lean

688
00:39:44,960 --> 00:39:47,800
Speaker 1: toward the idea that more screen time and less interaction

689
00:39:47,800 --> 00:39:51,720
Speaker 1: in real space is probably not the most psychologically healthy

690
00:39:51,800 --> 00:39:54,840
Speaker 1: behavior we could engage in. But I also must admit

691
00:39:55,200 --> 00:39:58,239
Speaker 1: that I don't have any scholarly evidence to support this,

692
00:39:58,600 --> 00:40:00,960
Speaker 1: and that most of my conclusions are really drawn from

693
00:40:00,960 --> 00:40:04,439
Speaker 1: my own personal experience, and as any good scientist will

694
00:40:04,440 --> 00:40:09,680
Speaker 1: tell you, anecdotal evidence isn't really evidence at all. At

695
00:40:09,719 --> 00:40:13,440
Speaker 1: the same time, for my own mental health, I feel

696
00:40:13,440 --> 00:40:15,920
Speaker 1: the need to do something, and so I've been trying

697
00:40:15,960 --> 00:40:18,560
Speaker 1: to sort of wean myself off of my dependence of

698
00:40:18,640 --> 00:40:21,560
Speaker 1: social media and screens to see if that has a

699
00:40:21,560 --> 00:40:24,400
Speaker 1: positive impact on my life. I'm not the only one

700
00:40:24,520 --> 00:40:27,920
Speaker 1: drawing these sort of tentative conclusions, and some people are

701
00:40:28,160 --> 00:40:31,200
Speaker 1: far less cautious in connecting the dots than I am,

702
00:40:31,239 --> 00:40:33,960
Speaker 1: but they also are more educated in the field than

703
00:40:34,000 --> 00:40:36,400
Speaker 1: I am, So it's not meant to be a dig So,

704
00:40:36,440 --> 00:40:39,800
Speaker 1: for example, the Chicago Tribune piece that I mentioned earlier

705
00:40:39,800 --> 00:40:43,480
Speaker 1: in this episode, the author, Drene Dodge and McGee is

706
00:40:43,560 --> 00:40:46,399
Speaker 1: a psychologist and a researcher, and she believes that there

707
00:40:46,560 --> 00:40:50,920
Speaker 1: is a connection between an increase independence upon technology and

708
00:40:50,960 --> 00:40:54,200
Speaker 1: the rise of depression among certain populations in the United States.

709
00:40:54,640 --> 00:40:58,279
Speaker 1: She connects increased usage with declining mental health, and she

710
00:40:58,400 --> 00:41:00,960
Speaker 1: may be right, but I still worry that without some

711
00:41:01,040 --> 00:41:03,840
Speaker 1: carefully designed studies, we can't be sure that that's the

712
00:41:03,880 --> 00:41:07,040
Speaker 1: actual flow of behavior. That is, that people begin to

713
00:41:07,080 --> 00:41:10,480
Speaker 1: experience a decline and mental health as they use more

714
00:41:10,520 --> 00:41:13,960
Speaker 1: and more technology, instead of people are using more and

715
00:41:14,000 --> 00:41:17,799
Speaker 1: more technology as a result of them already dealing with

716
00:41:17,840 --> 00:41:21,360
Speaker 1: a decline in mental health. Like, without establishing the actual

717
00:41:21,440 --> 00:41:24,959
Speaker 1: causal relationship there, I don't think you can make any

718
00:41:25,160 --> 00:41:29,839
Speaker 1: real conclusions. Now, another factor we should take into consideration

719
00:41:30,200 --> 00:41:33,560
Speaker 1: is what is the actual behavior being reinforced through these

720
00:41:33,640 --> 00:41:36,840
Speaker 1: various technologies and services if the purpose is to capture

721
00:41:36,840 --> 00:41:41,440
Speaker 1: eyeballs for the purposes of generating revenue, And nearly every

722
00:41:41,480 --> 00:41:44,719
Speaker 1: case does boil down to that if you go far enough,

723
00:41:45,320 --> 00:41:46,719
Speaker 1: the best you might be able to say is that

724
00:41:46,760 --> 00:41:50,960
Speaker 1: it's not necessarily doing direct harm to someone. If the

725
00:41:51,000 --> 00:41:53,640
Speaker 1: design is meant to convince someone to pour money into

726
00:41:53,640 --> 00:41:56,360
Speaker 1: a service, you could argue that the service can be

727
00:41:56,440 --> 00:42:00,480
Speaker 1: financially harmful to those who are vulnerable to the reinforcement cycle.

728
00:42:01,000 --> 00:42:03,600
Speaker 1: And while social networks can help people connect with one

729
00:42:03,640 --> 00:42:06,640
Speaker 1: another and stay in touch, if the algorithm that populates

730
00:42:06,640 --> 00:42:09,719
Speaker 1: a news feed is selecting which posts you see and

731
00:42:09,800 --> 00:42:12,359
Speaker 1: which ones you don't in an effort to convince you

732
00:42:12,400 --> 00:42:15,560
Speaker 1: to spend more time on that platform, you're not really

733
00:42:15,719 --> 00:42:18,840
Speaker 1: engaging with those friends and loved ones. Instead, you're seeing

734
00:42:18,840 --> 00:42:22,520
Speaker 1: a curated list that isn't meant to create meaningful connections,

735
00:42:22,760 --> 00:42:25,839
Speaker 1: but rather keep you on the platform longer so that

736
00:42:25,880 --> 00:42:29,280
Speaker 1: the platform can serve you more ads. If you're lucky,

737
00:42:29,719 --> 00:42:33,120
Speaker 1: just like with a slot machine player, than some percentage

738
00:42:33,120 --> 00:42:36,120
Speaker 1: of those posts you are seeing are actually meaningful and

739
00:42:36,160 --> 00:42:39,879
Speaker 1: do help you create those close connections, but otherwise you're

740
00:42:39,920 --> 00:42:43,040
Speaker 1: being fed stuff with the intent of keeping you there.

741
00:42:43,520 --> 00:42:46,520
Speaker 1: From a business standpoint, I can totally understand that design

742
00:42:46,960 --> 00:42:50,160
Speaker 1: businesses generate revenue, and generally speaking, you want as much

743
00:42:50,239 --> 00:42:52,880
Speaker 1: revenue as you can earn. You want that revenue to

744
00:42:52,920 --> 00:42:55,880
Speaker 1: grow year over year. To return money on the investment

745
00:42:55,920 --> 00:42:58,880
Speaker 1: for building the business in the first place. Publicly traded

746
00:42:58,960 --> 00:43:01,799
Speaker 1: companies face growth targets each year with the goal of

747
00:43:01,840 --> 00:43:05,359
Speaker 1: creating a return for shareholders, But that just means that

748
00:43:05,400 --> 00:43:07,560
Speaker 1: the business has to find ways to make more money,

749
00:43:08,040 --> 00:43:10,919
Speaker 1: not to make money in a responsible or a compassionate way.

750
00:43:11,160 --> 00:43:14,359
Speaker 1: As long as the business isn't outright violating any regulations

751
00:43:14,440 --> 00:43:17,319
Speaker 1: or laws, it's pretty much fair game. And this has

752
00:43:17,320 --> 00:43:20,440
Speaker 1: created the environment we see today and has enabled companies

753
00:43:20,480 --> 00:43:23,839
Speaker 1: to create services that incentivize us to use them more

754
00:43:23,840 --> 00:43:26,279
Speaker 1: and more. They can serve up ads, and in the

755
00:43:26,280 --> 00:43:28,719
Speaker 1: case of companies like Facebook or Google, they can use

756
00:43:28,760 --> 00:43:32,680
Speaker 1: the collected data that we generate to great advantage. So

757
00:43:32,920 --> 00:43:36,320
Speaker 1: even if the use of these strategies isn't directly causing

758
00:43:36,400 --> 00:43:39,440
Speaker 1: us harm, it is certainly an attempt to manipulate us

759
00:43:39,440 --> 00:43:43,360
Speaker 1: into being ever more dependent upon those services, and it

760
00:43:43,480 --> 00:43:46,560
Speaker 1: totally works, just as it worked in those rats in

761
00:43:46,600 --> 00:43:50,160
Speaker 1: Skinner's experimental box. Now there are people out there who

762
00:43:50,200 --> 00:43:53,960
Speaker 1: are dedicated to breaking this dependence on technology. In some cases,

763
00:43:54,160 --> 00:43:57,200
Speaker 1: it all starts with more tech. There's an app called Moment,

764
00:43:57,360 --> 00:43:59,719
Speaker 1: for example, and it tracks how much you use your

765
00:43:59,719 --> 00:44:02,399
Speaker 1: phone in her tablet and includes a breakdown of which

766
00:44:02,400 --> 00:44:05,080
Speaker 1: apps you use most frequently and for the longest amount

767
00:44:05,080 --> 00:44:09,040
Speaker 1: of time. Sometimes just getting quantifiable data can help you

768
00:44:09,160 --> 00:44:12,160
Speaker 1: get some perspective. For some people, the results might not

769
00:44:12,239 --> 00:44:14,920
Speaker 1: be a surprise or even alarming, but for others it

770
00:44:14,960 --> 00:44:17,719
Speaker 1: could serve as an incentive to try and reduce the

771
00:44:17,719 --> 00:44:20,960
Speaker 1: amount of time spent on devices. There are books and

772
00:44:21,200 --> 00:44:24,800
Speaker 1: camps dedicated to helping people break free of technology dependence,

773
00:44:25,520 --> 00:44:27,440
Speaker 1: and I think that can be well intentioned. But I

774
00:44:27,480 --> 00:44:29,719
Speaker 1: also want to point out that the world we live

775
00:44:29,760 --> 00:44:33,759
Speaker 1: in skews pretty darn heavily in favor of people who

776
00:44:33,760 --> 00:44:37,880
Speaker 1: are making use of technology or communication systems. Means of

777
00:44:37,920 --> 00:44:44,040
Speaker 1: finding work, uh commerce systems and more grow increasingly tech dependent.

778
00:44:44,680 --> 00:44:47,719
Speaker 1: I think it's not realistic to truly shed your use

779
00:44:47,760 --> 00:44:50,680
Speaker 1: of technology, to go off the grid entirely and be

780
00:44:51,520 --> 00:44:57,200
Speaker 1: meaningfully interacting with society at large. I suppose it's possible,

781
00:44:57,239 --> 00:45:01,560
Speaker 1: but it's really really hard to do. I do think, however,

782
00:45:01,600 --> 00:45:03,960
Speaker 1: you can make some choices to reduce your dependence on

783
00:45:04,000 --> 00:45:07,600
Speaker 1: technology if that's your goal. Now. For me, I plan

784
00:45:07,680 --> 00:45:11,440
Speaker 1: on stepping back a significant amount later this year. En

785
00:45:11,880 --> 00:45:15,040
Speaker 1: I'm likely deactivating my Facebook account in June of two

786
00:45:15,040 --> 00:45:18,400
Speaker 1: thousand nineteen. And this is a choice I'm making for myself.

787
00:45:18,719 --> 00:45:22,400
Speaker 1: I'm not urging anyone to do Likewise, I don't pretend

788
00:45:22,440 --> 00:45:24,799
Speaker 1: that I have the answer for everyone out there. Heck,

789
00:45:24,880 --> 00:45:27,080
Speaker 1: I'm not even certain that cutting back on screen time

790
00:45:27,080 --> 00:45:30,120
Speaker 1: and social platforms will have any meaningful positive effect in

791
00:45:30,160 --> 00:45:32,520
Speaker 1: my day to day life, but something I'm going to

792
00:45:32,600 --> 00:45:35,319
Speaker 1: try in an effort to be more engaged with the

793
00:45:35,360 --> 00:45:38,680
Speaker 1: people around me and my real world community. So we'll

794
00:45:38,719 --> 00:45:42,000
Speaker 1: see if it makes an impact in the meantime. If

795
00:45:42,040 --> 00:45:45,080
Speaker 1: you guys have any suggestions for future topics of tech stuff,

796
00:45:45,160 --> 00:45:47,919
Speaker 1: or you have any questions or comments for me reach out.

797
00:45:48,200 --> 00:45:50,759
Speaker 1: You can do so through email. The address is tech

798
00:45:50,840 --> 00:45:54,400
Speaker 1: stuff at how stuff Works dot com, or on Facebook

799
00:45:54,480 --> 00:45:56,359
Speaker 1: or Twitter. The handle for both of those is text

800
00:45:56,360 --> 00:45:58,879
Speaker 1: stuff HSW. I'm eager to hear what you guys think

801
00:45:58,920 --> 00:46:01,960
Speaker 1: about this stuff. Also, remember you can pop on over

802
00:46:01,960 --> 00:46:05,360
Speaker 1: to our website, tech Stuff Podcast dot com. I promise

803
00:46:05,440 --> 00:46:07,840
Speaker 1: I don't use any of those tricks to try and

804
00:46:07,920 --> 00:46:10,200
Speaker 1: keep you on that site forever, but you can search

805
00:46:10,280 --> 00:46:13,000
Speaker 1: the archive and look at all the past episodes we

806
00:46:13,040 --> 00:46:14,759
Speaker 1: have up there in case you want to see if

807
00:46:14,760 --> 00:46:18,520
Speaker 1: there's something specific in our library. And you can also

808
00:46:18,560 --> 00:46:20,560
Speaker 1: pop on over to our merchandise store if you want

809
00:46:20,600 --> 00:46:23,200
Speaker 1: to get a tech Stuff T shirt or a hat

810
00:46:23,480 --> 00:46:25,640
Speaker 1: or a coffee mug or something like that. And remember

811
00:46:25,640 --> 00:46:27,320
Speaker 1: every purchase you make goes to help the show. We

812
00:46:27,440 --> 00:46:31,399
Speaker 1: greatly appreciate it, and I'll talk to you again really soon.

813
00:46:36,160 --> 00:46:38,359
Speaker 1: Hext Stuff is a production of I Heart Radio's How

814
00:46:38,400 --> 00:46:41,799
Speaker 1: Stuff Works. For more podcasts from my heart Radio, visit

815
00:46:41,840 --> 00:46:44,920
Speaker 1: the i heart Radio app, Apple Podcasts, or wherever you

816
00:46:45,000 --> 00:46:46,320
Speaker 1: listen to your favorite shows.