Speaker 1: Sleepwalkers is a production of I Heart Radio and unusual productions.
Speaker 1: We can choose to have a poker face, but the
Speaker 1: point is that our bodies are still reacting and what's
Speaker 1: changed is the ability to see those signals. That's Poppy Crumb,
Speaker 1: chief scientists at Dolby Labs and a professor at Stanford University.
Speaker 1: Her work is at the forefront of neuroscience and data science,
Speaker 1: and it's bad news for the poker face pret Solo
Speaker 1: just want to an Academy award. And the filmmakers were
Speaker 1: at my company doing a screening and had we had
Speaker 1: captured carbon dioxide of the audience with her approval, of course,
Speaker 1: and I wasn't actually at the screening. I just saw
Speaker 1: the Ceoto capture and I knew exactly where the climbs were,
Speaker 1: where he abandoned his climbs. As the audience watched Annlex
Speaker 1: Honald attempted to climb El Capitan, their bodies responded to
Speaker 1: the suspense, their breathing change, and thanks to the carbon
Speaker 1: dioxide sensors in her theater, Poppy had a map of
Speaker 1: the audiences emotionally experience. It's this power of the audiences
Speaker 1: on that journey and experiencing it with the filmmakers, and
Speaker 1: it's pretty exciting to see that engagement in the theater
Speaker 1: and have that history. But our breath isn't our only
Speaker 1: tell There's an increasing number of ways machines are becoming
Speaker 1: able to read us, even how hard we're thinking. In
Speaker 1: thermal cameras, you can track, you can look at dynamics
Speaker 1: of blood flow to know stress levels and engagement. Just
Speaker 1: in the infrared signatures, you can understand cognitive load. You
Speaker 1: can then look at micro expressions of facial recognition to
Speaker 1: get past not just if I'm feigning emotion, but really
Speaker 1: the authenticity of what I'm experiencing. That gives us a
Speaker 1: lot of insight about how hard my brain is working
Speaker 1: and how engaged I am. We haven't changed this humans.
Speaker 1: What's changed this ubiquity of sensors and the capacity of sensors.
Speaker 1: The the cost just Fitteen years ago, the cost of
Speaker 1: a typical device would be about maybe. Now you're looking
Speaker 1: at those devices not even having to be close up
Speaker 1: for pennies dollars integrated into every pair of smart glasses.
Speaker 1: Going forward, we're on the cusp of two explosions. The
Speaker 1: power of machine learning to find patterns and make predictions,
Speaker 1: and simultaneously the miniaturization and affordability of cameras and other senses.
Speaker 1: Last episode we talked about facial recognition and surveillance by governments.
Speaker 1: But when machines contract how we're feeling, our most private
Speaker 1: selves become readable, and while that may sound frightening, it
Speaker 1: also holds enormous promise for many parts of life. From
Speaker 1: beginning to end this episode, we look at what's changing
Speaker 1: and what's possible. I'm as Veloshen. This is Sleepwalkers, my
Speaker 1: Ma Mama. So there are quite a lot of situations
Speaker 1: where personally, I don't actually want to be read. I'm
Speaker 1: not sure about you, like I want to hold them
Speaker 1: like they do in Texas play, Like when I'm playing Texas,
Speaker 1: hold them on people to know what I'm thinking, right,
Speaker 1: and not just at the poker table. In fact, our
Speaker 1: society kind of relies on the idea that we can
Speaker 1: look one way but feel another. Obviously, in plays like Hamlet,
Speaker 1: interiority is dramatized, but but more broadly, society is where
Speaker 1: people have no privacy tend to be a bit scary.
Speaker 1: It is scary because the last thing we have on
Speaker 1: earth is our privacy. You know, it's like people have
Speaker 1: this impulse to share everything on Instagram and give away
Speaker 1: their name to a company that wants to sell them jewelry,
Speaker 1: and it's just like, truly, our deep our secrets are
Speaker 1: the last thing we have, well the last thing we had.
Speaker 1: Right probably did a full ted talk on this, and
Speaker 1: the thing that I took away from it is will
Speaker 1: we live in a near future where a slasher film
Speaker 1: will be edited with people's biometric data in mind? Poppy
Speaker 1: suddenly sees that on the horizon, and she has a
Speaker 1: term for technology that starts to understand us. Empathetic technology
Speaker 1: is the idea that you know, it's it's not technology
Speaker 1: that empathizes with me or technology that is trying to
Speaker 1: emulate human empathy. It's technology that makes use of my
Speaker 1: internal experience to be able to integrate that as part
Speaker 1: of its interface. Today, it's impressive that Poppy can understand
Speaker 1: an audience's emotional journey watching Free Solo by tracking the
Speaker 1: levels of CEO two in their breath. But tomorrow it
Speaker 1: could lead to new kinds of art and entertainment that
Speaker 1: responds to us. Really great hip hop producer I was
Speaker 1: talking to wants to create music that is personalized, almost
Speaker 1: like a tailored suit for individuals. So you start to
Speaker 1: think about a very dynamic integration of the human experience.
Speaker 1: That experience becomes something that our technology can be aware
Speaker 1: of and optimized for. I want my technology to make
Speaker 1: the right di visions so that the experience I have
Speaker 1: with it is seamless. Seamless such a seductive word they
Speaker 1: named a food delivery service after it, but a dangerous
Speaker 1: word too, because for technology to read and respond to
Speaker 1: us in real time, it needs to make decisions about
Speaker 1: us on its own. You may remember last episode we
Speaker 1: spoke with Lisa talia Moretti about some of the risks
Speaker 1: of facial recognition technology, but that's not her only area
Speaker 1: of research, something that I was looking into really recently,
Speaker 1: as our relationship with technology is completely shifting. So we're
Speaker 1: moving from a relationship with technology where we are asking
Speaker 1: it to do something, you know, it's a pure sort
Speaker 1: of input output, And what now we're moving towards is
Speaker 1: a relationship with technology where we are trusting technology to
Speaker 1: make decisions on our behalf. Lisa teaches at Goldsmiths in
Speaker 1: London and Cardiff University. She told us about how her
Speaker 1: students have encountered chnology making its own decisions about their
Speaker 1: future prospects. One of the things that the students are
Speaker 1: starting to do is to game the algorithms that are
Speaker 1: being used to mind through candidates cvs. And so what
Speaker 1: they figured out is if they put right in white
Speaker 1: text anywhere on their CV UM Cambridge, Harvard, Oxford, they're
Speaker 1: more likely to get through to the interview process. Does
Speaker 1: students know that recruiting algorithms prioritize applications from certain schools,
Speaker 1: so they pepper their applications with words they know the
Speaker 1: algorithm will like, but written in white. So the human
Speaker 1: recruiters are not the wiser. They're marketing themselves straight to
Speaker 1: the AHI. They're gaming the algorithm system, which I think
Speaker 1: is pretty genius. There's also certain things where students or
Speaker 1: candidates who are having to conduct their first interview in
Speaker 1: some companies purely online and there's no person on the
Speaker 1: other side. You're essentially talking into your webcam, and there's
Speaker 1: algorithmic technology that is recording your voice, that's listening for intonation,
Speaker 1: that's listening for the types of words that you're saying,
Speaker 1: like if you use smart words or your language isn't
Speaker 1: perhaps at a level that they would think is appropriate
Speaker 1: for business. But do we want computers to deny opportunities
Speaker 1: to job applicants that may be qualified but not fully
Speaker 1: polished without human review. And the algorithms weren't only analyzing
Speaker 1: the student's words. They're also looking at your facial features,
Speaker 1: and so they can say if you're nervous or shy.
Speaker 1: And some of my students have said that if they
Speaker 1: very quickly use like hand gestures, they confuse the camera
Speaker 1: and the camera councy if they were nervous or shy
Speaker 1: for those particular moments. There's something quite hopeful about these
Speaker 1: students averting the algorithms designed to read them. It's not
Speaker 1: quite the Summer of six y eight, Cara, but the
Speaker 1: youth have still got something. Well, it's true that you
Speaker 1: and I both look very good in black leather and
Speaker 1: are considered cyberpunks. That's how we met that cyberpunk rally.
Speaker 1: I was reading about this Kickstarter campaign called reflectacles like specticles,
Speaker 1: but reflective, that's right, And that's because they reflect invisible
Speaker 1: and infrared light. When you look back into a camera
Speaker 1: that's watching you, which is like an ultimate that's like
Speaker 1: a techy middle finger, like I'm gonna look right back
Speaker 1: in this camera. It's just gonna like buzz light back
Speaker 1: at it completely. So you know, there are methods obviously
Speaker 1: for resistance, But what I'm worried about is that algorithms
Speaker 1: are very smart and they will wise up and be
Speaker 1: harder to trick. Right, and showing up for your job
Speaker 1: interview and reflecticles probably carried his own burden as well.
Speaker 1: It is how I got this job, though, But we
Speaker 1: should also ask ourselves why these companies are using AI
Speaker 1: to filter candidates and conduct interviews, And of course it's
Speaker 1: really about saving money and saving resources, which brings out
Speaker 1: the big question of the series. Who benefits from this
Speaker 1: new technology Amazon and Facebook and Google. When we come back,
Speaker 1: we look at the economics of giving up our data
Speaker 1: and what we get in return. Sensors and AI to
Speaker 1: analyze our response to movies or decide if we're a
Speaker 1: good fit for a job. May sound like the stuff
Speaker 1: of dystopian science fiction, and that's because it is set
Speaker 1: up a progner and Tilmon Rope. I'm placing you under
Speaker 1: arrest for the future murder, Sarah Marks, you have a
Speaker 1: man his head. Yeah, oh, gosh, Well, it's interesting you
Speaker 1: mentioned Minority Report because, um to this day, so many
Speaker 1: years later, decades later, I'll be in some meeting in
Speaker 1: Silicon Valley and We'll be looking at some gadget and
Speaker 1: so I say, Wow, this gadget is great. It's like
Speaker 1: from Minority Report. It's so cool, And I'm like, that
Speaker 1: was supposed to be cautionary. That was a description of
Speaker 1: the bad world. That was what we want to avo wide. Oh,
Speaker 1: for God's sake, that's Jaron Lania. He's a research scientist
Speaker 1: at Microsoft and in the eighties he coined the term
Speaker 1: virtual reality after helping invent the field. Jaren's thought a
Speaker 1: lot about what our relationships with technology mean for us,
Speaker 1: So when Steven Spielberg was making Minority Report, he called
Speaker 1: on Jarren to act as a technology consultant. Mostly, what
Speaker 1: I've taken from Minority Report is that just trying to
Speaker 1: do cautionary portrayals of technology actually backfires, because there's some
Speaker 1: way that it's a little bit like when you show
Speaker 1: the Life of Billionaires, people don't get angry about like
Speaker 1: why do those people monopol or where they own whole
Speaker 1: islands or something. Instead they say, oh, I identify with
Speaker 1: that person. Maybe I could own a whole island someday.
Speaker 1: And despite our fascination with dystopian fiction, we also have
Speaker 1: a tendency to fantasize about ourselves as the beneficiaries, not
Speaker 1: the victims, of the systems we create, and we tend
Speaker 1: to ascribe those systems their own will, even though we've
Speaker 1: made them. Early in the history of capitalism, Adam Smith
Speaker 1: suggested that capitalism or markets were an invisible hand, as
Speaker 1: sort of a life form. And in the same way
Speaker 1: that you can interpret a market as being this living
Speaker 1: thing just because it's a little beyond our understanding, it's
Speaker 1: a little too complicated to fully predict and fully understand,
Speaker 1: and and that's actually its power. In the same way,
Speaker 1: big computational systems can be a little out of control,
Speaker 1: not entirely, but even if they're only a little bit,
Speaker 1: you can interpret that as being the new invisible hand,
Speaker 1: which we call artificial intelligence. Invoking an external force like
Speaker 1: the invisible hand, or an algorithm that automatically reads resumes
Speaker 1: or makes parole recommendations obsculls real human decisions. We have
Speaker 1: to remember that our creations reflect us. If you use
Speaker 1: that to abdicate your responsibility. If you use it just
Speaker 1: to cower and fear, then you're not being a good
Speaker 1: computer scientist. That is not the responsible way to do things.
Speaker 1: Just as if an economist says, well, the invisible hand
Speaker 1: says all these people should starve, that's not a responsible economist.
Speaker 1: The responsible economist fixes the problem in a sense. I
Speaker 1: think it's very hard to be effective if you believe
Speaker 1: in some kind of magical agency in your own inventions.
Speaker 1: I think you make yourself into an idiot. And and
Speaker 1: so I'm really concerned that not only economists but computer
Speaker 1: scientists make that error all the time. It's almost like
Speaker 1: a new form of mythology. I've been calling it alchemy lately.
Speaker 1: But yeah, sure, it's certainly easier to say, oh, we
Speaker 1: should respect this amazing autonomous living thing that has arisen
Speaker 1: in our own inventions. It's much easier to say that
Speaker 1: when it's benefiting you and you're getting very rich. Jarn
Speaker 1: puts his finger on a central irony in our relationship
Speaker 1: with technology. When our creations benefit us, we're quick to
Speaker 1: forget who pays the price. People who translate between natural languages,
Speaker 1: such as between English and Spanish, have seen their career
Speaker 1: prospects on the whole decrease tenfold since the arrival of
Speaker 1: Autumn Addic Translation, which is offered for free but companies
Speaker 1: like Google and Microsoft. Now, the thing is, you might say, well,
Speaker 1: this is very sad, but it always happens. People are made,
Speaker 1: people's jobs become obsolete when new technologies come along. The
Speaker 1: buggy whip goes away and the motor car comes. All right,
Speaker 1: but the problem is that every single day, those of
Speaker 1: us who help run these free services have to scrape
Speaker 1: or steal tens of millions of example phrases from all
Speaker 1: over the world from people who don't know it's being
Speaker 1: done to them. And the reason why every single day
Speaker 1: there's new pop culture and slang in public events and
Speaker 1: memes and on and on and so you need to
Speaker 1: constantly get new phrase examples to feed into the translation engines.
Speaker 1: So it's a weird thing. We're telling the people you
Speaker 1: don't get a job anymore because you're not needed. Oh,
Speaker 1: by the way, you're needed. We need to steal with you.
Speaker 1: Oh but by the way, we won't even tell you.
Speaker 1: And it's all based on this lie that we don't
Speaker 1: need people. Um, and that lie is based on this
Speaker 1: need to pretend the AI is this free standing thing,
Speaker 1: whereas we could instead think of it it's just the
Speaker 1: way that's African channel value between people in a new
Speaker 1: and better way. The free availability of real time translation
Speaker 1: opens up a world of possibilities for travelers, for language learners,
Speaker 1: for long distance lovers. But these technologies have invisible costs,
Speaker 1: like the translators losing their jobs to a tool that
Speaker 1: was trained on their work. And this kind of unpaid
Speaker 1: labor is actually something all of us participating every day
Speaker 1: without even realizing. Here's Lisa again. The way that these
Speaker 1: voice activated assistance are being trained is through huge amounts
Speaker 1: of data. A bit of an unknown secret by many
Speaker 1: people who have an Alexa is that every single time
Speaker 1: you are talking to that device, it's being recorded and
Speaker 1: being stored and going back to the cloud to train
Speaker 1: all of the other echoes around the world. So the
Speaker 1: users of echo devices are providing free labor on behalf
Speaker 1: of these massive organizations in order to train the system.
Speaker 1: It's not the first thing we think that after purchasing
Speaker 1: an Alexa and using it to buy stuff online, every
Speaker 1: time we interact with it, we're also helping Amazon improve
Speaker 1: and make more money, but framing our data in terms
Speaker 1: of labor helps us think about technology in new ways,
Speaker 1: and our Alexa use reminds Jarren of another science fiction movie.
Speaker 1: The reason. One that's really gotten to me is that
Speaker 1: probably the most famous cautionary tale about computers was in
Speaker 1: two thousand one Stanley Kubrick and Arthur C. Clark's movie
Speaker 1: And There's this computer called how that's this round thing
Speaker 1: that sits on the wall and just looks at you
Speaker 1: and talks to you, I'm sorry, I'm afraid I can't
Speaker 1: do that, and it ends up going berserk and killing
Speaker 1: people and just and they have to the program it.
Speaker 1: And the hot new gadge for the last few years
Speaker 1: has been this round thing that sits there and looks
Speaker 1: at you and you talk to I'm afraid I can't
Speaker 1: do these smart speakers and so on, and it's like,
Speaker 1: no matter how many cautions we put forward, people just
Speaker 1: follow right into it. It's it's astonishing to me. Of course,
Speaker 1: Alectra is powered by artificial intelligence. It takes a machine
Speaker 1: learning to understand what you say to it. But maybe
Speaker 1: the bigger breakthrough has been our decision to let listening
Speaker 1: devices into our homes. Yeah, I think that's true. I
Speaker 1: didn't grow up talking to something in my house. It's
Speaker 1: interesting when you read those articles like deep inside North Korea.
Speaker 1: You know, the thing that journalists always writes, there's a
Speaker 1: speaker in every house which projects the chairman's voice into
Speaker 1: the homes. As always the shocking detail. And of course
Speaker 1: now we will have Alexas in our houses, you know.
Speaker 1: I think it's interesting that Amazon was being delivered to
Speaker 1: us the boxes on our door step. That was the
Speaker 1: farthest they were going to get right, And now with
Speaker 1: Echo and Dot, these are devices that are inside of
Speaker 1: our homes, that are on our countertops. We're at this
Speaker 1: place where Alexa is now a part of the family.
Speaker 1: And now we have this first generation of children growing
Speaker 1: up with Alexas and other smart devices at home, interacting
Speaker 1: with them, seeing their parents talk to them all the time,
Speaker 1: and they're already used to this responsive technology. The giving
Speaker 1: away our data piece is disconcerting, but there's another piece
Speaker 1: of our shifting relationship with technology, which is why I
Speaker 1: dragged Julian into New Jersey to one of the smartest
Speaker 1: homes I know. And no I'm not talking about i Q.
Speaker 1: Let me ask you a question. What does your little
Speaker 1: brother look like a little guy? So what would you say?
Speaker 1: What does Alexe look like? But where does she live in?
Speaker 1: They really so every time you talk to Alexei, you're
Speaker 1: talking to space, despite having an Alexa who lives in space.
Speaker 1: My friend and her husband live in the suburbs with
Speaker 1: their sons, who are almost two and five. When they
Speaker 1: recently moved to New Jersey to fit their expanding family,
Speaker 1: they did not scrimp on smart home devices. Yeah, we've
Speaker 1: got two little kids. We both work. It doesn't bother
Speaker 1: me that they know our habits make it easier for us,
Speaker 1: like to get stuff done. Like I'm cool with Amazon
Speaker 1: just sending me diapers because it knows what I need
Speaker 1: diapers for parents like my friends, devices like the Amazon Alexa,
Speaker 1: Google Home and their marriad counterparts are genuinely helpful, which
Speaker 1: is probably why over a hundred and eighteen million American
Speaker 1: households have a smart speaker. That's half of the US.
Speaker 1: And when you've got something so involved in your home
Speaker 1: life that it helps with diapers and groceries, it's bound
Speaker 1: to affect some other areas as well. Your dad said,
Speaker 1: they're too There's there are three women in the house Google,
Speaker 1: who I don't know, who's the third woman in the house?
Speaker 1: And even bedtime is different. Hey, Google, tell me a story. Sure,
Speaker 1: here's one from Nickelodeon. It was a sunny day and
Speaker 1: Mr Porter was visiting farmer. He'll have I'll Google reading
Speaker 1: a story when he's in bed and we don't want
Speaker 1: to read any more books. You for your Google go
Speaker 1: off when you as if closed the door. Yeah. To
Speaker 1: be clear, Google Home has not replaced real life bedtime stories,
Speaker 1: but it has enabled my friend's kid to get more
Speaker 1: out of bedtime. He can keep asking for stories long
Speaker 1: after his parents need to stop reading. But focusing on
Speaker 1: the privacy component of these devices doesn't capture the full picture.
Speaker 1: Not only can the rhythms of family life change in
Speaker 1: response to a digital assistant, but so can kids expectations.
Speaker 1: And that's true for all of us, even those of
Speaker 1: us already passed early childhood development. We should think about
Speaker 1: how we're affected long term by our expectation of seamless delivery.
Speaker 1: You've got a good rapport with those kids, Kara. Neither
Speaker 1: of us have our own kids, but our editor among
Speaker 1: us does. I was curious for his take on next
Speaker 1: to joining the family So I'd gone out to this
Speaker 1: wedding a couple of years ago in Seattle, and it
Speaker 1: was in this fancy hotel and there was an Alexa
Speaker 1: there in the room, and Azzie and I went out
Speaker 1: for dinner or something, and we left the kids with
Speaker 1: a sitter, and the kids were mesmerized because they never
Speaker 1: encountered one of these devices before, so they were watching
Speaker 1: the babysitter interact with it, calling up music and whatever else.
Speaker 1: But then she also ordered food, so they were just
Speaker 1: floored by this. Then the next week, we were back
Speaker 1: at home and I was watching my four year old
Speaker 1: just like stomping around the house, and she started barking
Speaker 1: Alexa pizza, and it was just so confusing. She immediately
Speaker 1: knew that there was this thing you could just bark
Speaker 1: at it and and get food, and she wanted results.
Speaker 1: But I have a conflicted feeling about all of this
Speaker 1: because I had grown up in the States, very middle class,
Speaker 1: and every couple of years we go to India and
Speaker 1: visit my relatives who were a little wealthier. And we
Speaker 1: went to a party once with one of my cousins
Speaker 1: and I saw this kid who was super wealthy, and
Speaker 1: he was yelling at his chauffeur. He was yelling at
Speaker 1: his mom, he was barking at the maid that they had,
Speaker 1: and it was just so gross. And when you see
Speaker 1: this sort of entitlement in front of you and expressed
Speaker 1: in this way, you don't want your kids growing up
Speaker 1: with that, right, and you want everyone to be treated
Speaker 1: as humans. And and so for my daughter to be
Speaker 1: stomping around barking what she wanted, you know, I don't
Speaker 1: want that to be her way of speech. This kind
Speaker 1: of reminds me of the movie Invasion of the Body Snatchers,
Speaker 1: except the Monash version, which is that you know, he
Speaker 1: went out to dinner with his wife. He comes back,
Speaker 1: his daughter is like Alexa pizza, and he's like, what
Speaker 1: has Alexa done with my chid? You know, she was
Speaker 1: like the sweet little girl, and now she's like a
Speaker 1: child that's aware of an Alexa based on one encounter. Right.
Speaker 1: I feel like if an alien came down from space
Speaker 1: and came into my apartment and saw me cooking dinner
Speaker 1: and then saw me go, Alexa turn on Paul Simon radio,
Speaker 1: the alien would be like, is she yelling at a
Speaker 1: woman who's going to go turn on the music? Um?
Speaker 1: I think right, now we are all, you know, Mangesh's
Speaker 1: daughter included, participating in this life altering moment of self
Speaker 1: delusion where we're sort of collectively accepting smart devices in
Speaker 1: our homes. We're not just accepting them, we're treating them
Speaker 1: as human right, And I think this is the slippery
Speaker 1: ish slope of using voice assistance. More and more we're
Speaker 1: speaking to voice activated devices as though there are family members,
Speaker 1: and there have got to be some long term implications,
Speaker 1: both emotional and psychological, of blurring the line. I agree,
Speaker 1: and we're going to hear more from Jared about that
Speaker 1: after the break, But we'll also speak to Poppy Crumb again,
Speaker 1: who believes that we've barely scratched the surface of how
Speaker 1: these devices can change how we live for the better children.
Speaker 1: Interacting with Alexa and Siri and other digital assistance is
Speaker 1: particularly striking because of the developmental implications, But interacting with
Speaker 1: machines who understand and respond to us can his questions
Speaker 1: about who and what gets to be treated as a person. Here, Jarren,
Speaker 1: I think the problem isn't the math or the computer
Speaker 1: science algorithms. I think the problem is our framework for
Speaker 1: thinking about them tends to be machine centric. Instead of
Speaker 1: human centric, and it tends to create dangerous for the
Speaker 1: whole and and to create a lot of confusion, And
Speaker 1: a lot of it is because of this ideology of
Speaker 1: thinking of the machine as being alive. And when we
Speaker 1: remember that our AI inventions aren'to live and simply reflect
Speaker 1: the inputs we give them, we can do a better
Speaker 1: job at harnessing their power for good. You may remember
Speaker 1: kai Fu Lee from the last episode. Before running Google China,
Speaker 1: Kaifu worked at Apple, where he helped develop Siri. AI
Speaker 1: is programmed by people. It is up to us to
Speaker 1: remove the factors that we don't think it's appropriate to
Speaker 1: be considered in the decision from an AI. So if
Speaker 1: we want to eliminate sexual orientation from a long decision engine,
Speaker 1: we can do that, or if one to eliminate it
Speaker 1: from a job application, we can do that. It's actually
Speaker 1: better than people. You can't force people to completely ignore
Speaker 1: these sort of things from their decision. They can try,
Speaker 1: but our brains are not separable in that way. Engines
Speaker 1: actually are being able to program a way out of
Speaker 1: our messier human biases is a big deal, but it's
Speaker 1: only made possible when we acknowledge that we control what
Speaker 1: an algorithm learns from. So if we get it right,
Speaker 1: just how good could our relationship with technology get? His
Speaker 1: Poppy crume again. I had a relative who you know,
Speaker 1: was at the end of life, and I was with
Speaker 1: him for the last few weeks in the hospital. He
Speaker 1: hadn't been speaking for a couple of days. I had
Speaker 1: taken on Amazon Alexa. I was using it simply to
Speaker 1: play music. I was playing classical music. And all of
Speaker 1: a sudden, he says, Alexa, play al Green and I was,
Speaker 1: And you know, and Poppy had always interacted with our
Speaker 1: uncle through classical music. It was their thing. And here
Speaker 1: he was, at the end of his life, requesting R
Speaker 1: and B an interest she didn't even know he had.
Speaker 1: He wanted to hear Algreen and sly in the family stone,
Speaker 1: and I was like, nowhere near that. But the empowerment
Speaker 1: the device allowed at a very vulnerable and sensitive and
Speaker 1: important time, he smiled the end of life. And it's
Speaker 1: the access to memories, the access to that internal richness,
Speaker 1: the things that might bring someone the most comfort are
Speaker 1: we all don't know. Amazon's Alexa really opened up great
Speaker 1: opportunities for what our relationship with our technology can be suddenly,
Speaker 1: Alexa isn't just something that dims your lights or tells
Speaker 1: you if his reigning as you rush out of the door,
Speaker 1: but actually a device that can change profoundly how you
Speaker 1: live and die. And Poppy noticed other ways, and Alexa
Speaker 1: could have up her uncle beyond playing al Green. I
Speaker 1: sat in a hospital room where I saw errors be made.
Speaker 1: I saw information be captured, incorrectly written on the board
Speaker 1: one way, shared to a different nurse, another, shared to
Speaker 1: a different doctor, another And I said, all of these
Speaker 1: different things happened that with the right coordination of that
Speaker 1: same device that just allowed my uncle to hear al
Speaker 1: Green on Q it could have also been a huge
Speaker 1: part of improving not just his mental wellness but his
Speaker 1: physical wellness. Because we're humans, we make errors, we make mistakes,
Speaker 1: We're not good at integrating information all the time, and
Speaker 1: our fallacy comes in places that technology can solve. I
Speaker 1: don't want to discount hospital stuff. They work very hard,
Speaker 1: uh and and everything, but people are sometimes you haven't
Speaker 1: had enough sleep, or they don't know someone else. You know.
Speaker 1: People try to help at different points in time and
Speaker 1: end up sometimes introducing error and mistakes. Technology that's actually
Speaker 1: capturing or registering information for a user. There's obvious ways
Speaker 1: that it can help improve the interaction to Poppy. The
Speaker 1: true power of Alexa is not to respond to specific
Speaker 1: requests like a super assistant. It's to monitor us constantly,
Speaker 1: detecting patterns that we can't more like a parent. And
Speaker 1: as of now, as far as we know, that's not
Speaker 1: what it does. What Alexa does right now is not
Speaker 1: what would actually benefit us most from a healthcare perspective.
Speaker 1: Right Alexa is listening for a wake word. It's listening
Speaker 1: for a particular que It's not holding that longitudinal data
Speaker 1: to learn our behaviors and and such right now. Not
Speaker 1: because of technological barrier, No, because of I think social
Speaker 1: and privacy barriers, and those barriers tend to erode in
Speaker 1: response to new technology. Twenty years ago, we would never
Speaker 1: have believed we would summon strangers from the Internet and
Speaker 1: climb in their cars either, you know. So we evolve
Speaker 1: when the capacity, when the convenience is introduced, and the capability. Clearly,
Speaker 1: technological innovation is only part of the equation. Becoming comfortable
Speaker 1: with new uses for those technologies opens up new worlds
Speaker 1: of possibilities and everything from how we listen to music,
Speaker 1: to how we take care of each other. So let's
Speaker 1: say we accept this new bargain and open ourselves up
Speaker 1: to constant monitoring what might the future look like. Companies
Speaker 1: are looking at these things as ways of knowing not
Speaker 1: just someone is taking their medicine for an aging population
Speaker 1: or someone who's healing, but to know if actually they're depressed,
Speaker 1: are they under mental stress as well? And that becomes
Speaker 1: a great opportunity for autonomous living for elders, where the
Speaker 1: caretaker knows a lot more about how well the individual
Speaker 1: is healing and is doing at a particular point in time.
Speaker 1: There's this real irony in all of these situations that
Speaker 1: where through more tracking of my information comes freedom and
Speaker 1: you gain autonomy through the amalgamated data. There is an
Speaker 1: angel belief that more privacy we have, the more freedom
Speaker 1: we have. But Poppy says it's time to rethink that relationship.
Speaker 1: If you look at an elder who might otherwise be
Speaker 1: in a care home but instead gains ten years of
Speaker 1: autonomous living because you now have more ubiquitous understanding of
Speaker 1: our mental and physical wellness, you have people having a
Speaker 1: lot more freedom with simply having a richer understanding of
Speaker 1: their internal experience and their personal data. Crucially, if we
Speaker 1: do feel comfortable trading our privacy for more agency, we
Speaker 1: need to be very sure we can trust the people
Speaker 1: who get to see our data, because they're not just
Speaker 1: seeing us naked, they're seeing under the hood. The physiological
Speaker 1: tells that betray our private emotions. For me, everything is
Speaker 1: about transparency. No one should be tracked when they don't
Speaker 1: know they're being tracked. How our technology interacts with us,
Speaker 1: whether we share information or not, our technology can't know.
Speaker 1: I think that's the real issue. We have to recognize
Speaker 1: that this sort of cognitive sovereignty or agency that we
Speaker 1: believe in is a thing of the past. It means
Speaker 1: we have to redefine what that future looks like. It's
Speaker 1: a future we can all participate in building, and it's
Speaker 1: one way better off building as citizens with a collective
Speaker 1: voice and long term objectives, rather than as lone consumers
Speaker 1: in search of the best deal, whatever the cost to
Speaker 1: us in society. As Poppy says, there's a difference between
Speaker 1: an Alexa waking up to respond to commands like play
Speaker 1: our green and an Alexa that is always on building
Speaker 1: a model of our behavior that knows us better that
Speaker 1: we know ourselves, but the crux of that difference is
Speaker 1: more cultural and political than technological. Are we willing to
Speaker 1: give up our poker faces and allow ourselves to be
Speaker 1: read by sensors and algorithms in return for longer, safer,
Speaker 1: happier lives like Poppy's uncle? Or knowing the history of
Speaker 1: governments who have monitored and categorized citizens, Should we be
Speaker 1: doing everything we can to hit pause? Will our technology
Speaker 1: become a safety net or a spider's web? Next episode,
Speaker 1: we travel to Facebook's headquarters and investigate some of the
Speaker 1: more dangerous corners of the Internet, and, knowing that AI
Speaker 1: can both learn about us and imitate us, we take
Speaker 1: a hard look at deep fakes and examine a world
Speaker 1: where it's increasingly difficult to tell truth from fiction. I'm
Speaker 1: az veloshen see you next time. Sleepwalkers is a production
Speaker 1: of I Heart Radio and Unusual Productions. For the latest
Speaker 1: AI news, live interviews, and behind the scenes footage, find
Speaker 1: us on Instagram, at Sleepwalker's podcast, or at Sleepwalker's podcast
Speaker 1: dot com. Special thanks to Briany Cole. We had a
Speaker 1: conversation with Briany that made this episode possible, and Brian
Speaker 1: is the host of a fascinating podcast called Future of
Speaker 1: Sex that's all about using technology to make our lives better.
Speaker 1: Sleepwalkers is hosted by me Ozveloshin and co hosted by
Speaker 1: me Kara Price, with produced by Julian Weller with help
Speaker 1: from Jacopo Penzo and Taylor Chikoin mixing by Tristan McNeil
Speaker 1: and Julian Weller. Our story editor is Matthew Riddle recording
Speaker 1: assistance this episode from Tofarel and Phil Bodger. Sleepwalkers is
Speaker 1: executive produced by me Ozveloshin and Mangesh Had to Get Up.
Speaker 1: For more podcasts from my Heart Radio, visit the I
Speaker 1: Heart Radio app, Apple Podcasts, or wherever you listen to
Speaker 1: your favorite shows. Alexa Pizza