Kate O'Neill: "Tech Humanism: The Future is Meaningful" | Talks at Google
Thanks. Again for coming and please join me as we give a warm welcome to Kate O'Neill. Thanks. Very much thank you Tim thank you. Everyone hello fellow, humans. We. Actually, I guess I should check, and make sure are there any robots, here, any. Robots raise your hand if, you're a robot in the audience, yeah. I, don't see any so I think we're safe to proceed but you know I asked this question every once in a while because I figured one of these days there's. Going to be kind of a little spindly mechanical, arm that comes up when I ask that question I'm. Not really sure what. I'm supposed to do at that moment if I'm supposed to invite the robot come to come up here and take my job because, that's kind of how we talk about robots. And automation and, AI and everything these days is like with, this fear, this dread, about what, it's going to mean for, human jobs for, humanity, for kind of existential. Reality. As we know it so. My. Premise has been to think about how we, can make technology, better. For, humanity, better for our future and of. Course better for serving business purposes, but. In doing so I think we have to start back from one, of the squares sort of one of the foundations, and that is to think about what it is that makes us human, what. Is it that makes humans human so, I'll ask you to indulge me and just think for a moment of a word or a characteristic. That, you feel like really captures, the. Human experience like what one characteristic. Is it, and I won't have you call it out or anything but just hold it in your head for a moment what. Do you feel like it is that really, makes humans. Human. And. So let me ask how, many of you by show of hands thought of something like creativity. Or problem-solving, or, innovation. Or something like that anyone, know, one okay a couple people in the room good. Okay so, that's a pretty common answer, how. About this, is a more common answer I think empathy. Or, love or compassion. Anyone. Yeah okay a few more hands those, are both great, I think create characteristics, and admirable, qualities, of humans, I didn't. Necessarily specify. That these needed to be uniquely, human attributes but if you think if we think about those they, don't feel like they are uniquely, human right like we've seen creativity. And problem-solving in, non-human animals. Like otters, Beng mollusks, on rocks to open them and ravens use tools and we've, seen compassion. And love from. Elephants. And dogs and other other, species, so we know that those are exhibited. By other animals and I, don't think it's too far-fetched to, imagine that in the not-too-distant future, we might see at least superficial, indications, of machines. Exhibiting, those, kinds of qualities in. Their behavior interactions. With humans. And maybe even eventually our machines, which, will be very interesting at, a surface level but, how, many of you when you think about what, that most human, of characteristics. Is thought. Of checking a box.
Anyone. By. Show of hands. Of. Course you didn't because it's absurd but this, is the sort of premise the problem, that we encounter, in technology, a lot of the time is that we, don't necessarily think through, this kind of foundational, experience and we are presenting absurdities. As if, they are sort of foundational, truths and. Besides, which if we were to try to claim, that this is a uniquely, human characteristic. We. Get beat out anyway. By. Machines, you can also do, this characteristic. So. I don't know how many of you have seen. This little hippie. Guy. But. He's kind of fun. So. I. Have. Come to be, known as as Tim mentioned the tech humanist and I take, this this. Sort of moniker. Pretty. Seriously because I feel like there is this this area, around. Which technology. Does have, the capacity to solve human problems, it also has the capacity to scale. Like. We are experiencing. Automation, and AI and all kinds of other emerging technologies, bringing, scale. To, the types of solutions we we create like, never before. And so I think it behooves, us to really think about what. The human experience, around that, scale is going to be and what the human experience around technology, is going to be and how we can make technology, better solve business. Problems and, solve, human, problems at. The same time so. As I talk about being a tech humanist and as I think about solving, those challenges, I'm excited that you, all are in this room and on the live stream and watching, on the video later I hope and, then I want to offer that perhaps, that. That is also you that you maybe also are a tech humanist, and I'd like to offer that term, to you so that when you see my book as, Tim mentioned just came out September, 24th, Tech, humanists, that, you will see that title and think I'm, describing, you as well, because, that is the truth I'd like to see us all sort of join hands in this movement, to create more. Human, technology, and more, wide-scale. Human, experiences. That are more, meaningful and more integrated, and more dimensional, with, the technology, we create so the, premise there is how, can we both. Make. Technology better for business to solve business challenges, and, make. It better for humans, and. I think that that, both and framing, is the key to the whole thing we need to understand, how to, accept. That these things do need to be integrated together and I. Would propose that, the, way to accomplish this at scale is, to. Focus on creating more meaningful. Human, experiences. At. Scale so how. Do we focus on getting that meaning, into. The human experiences, so the way that that looks in the, model that I proposed is this on one, hand how, can we think about scaling, business. Meaningfully. Through data, through strategic alignment, and automation how can we think about using the tools at, our disposal to, make business more effective, while. Also, creating. More meaningful, human experiences. And scaling. Those through data and automation. I've. Had the opportunity to test this idea with. A lot of different companies that have consulted, with spoken with advised worked, with on different projects over the years and I'm, excited to say that it works in almost every industry I've encountered. It. Sort, of provides, great, results, no matter who, you are or what you trying to accomplish, every. Company, is trying to achieve, profit. Right every company is trying to achieve, revenue. Based metrics, in in, what they're going. About even if you're a nonprofit organization, you, still have to be accountable, to some sort of profit and loss scenario there's, some sort of breakdown of the financials, that you need to be accountable for and, I'm happy to tell you that the. Work of creating meaningful experiences, actually does lead. To increased, employee, retention decreased, customer acquisition, costs increased loyalty, and all, kinds of other directional. Metrics that lead to more profit of. Course it's also the right thing to do it also creates a better experience for all of us and I want everybody to be motivated, by you, know kind of this this. Aesthetic of wanting, the world to be better and creating, more meaningful experiences, being its own end but, if we have to be motivated by profit we can be and and, that's all a good thing too so. Let's unpack this just a little bit what I mean when, I talk about creating. Meaningful human. Experiences, at scale what. Does that entail so first let's think about what. Meaningful, really is so. The, example, of the click, the box to confirm your humanity I mentioned. I think that that's an absurd example and, I had this kind of running. Hobby. Of. Appreciating. The tension, between meaning, and absurdity, in the world but, I feel like anywhere, there is a lack of meaning, it sort of opens up this void into which absurdity, can flow so.
Where, We don't create enough meaning where, we don't describe. Enough meaning we, allow absurdity. To flourish, so. There's, enough opportunity. For that in technology, as it is and business, really I think, you all probably have this experience, I'm guessing, that, there, are areas where, let's. Say you talk about work things in ways, that you wouldn't talk about with. Your friends outside of work you use language or terminology that, your friends who don't work with you would. Would not understand, or. There, are things that you do at work that just don't. That are kind of like that's the way we've always done it but. Anytime you think to yourself this doesn't make sense that's. A really big clue because making things make sense is what meaning, so. We. Have an opportunity to step back and assess absurdity, and recognize. That that we can infuse meaning, into, those structures and create more opportunity, to avoid, meaning, to keep, away from meaning so the the reason that that works I believe is because humans. Crave meaning, more than any other characteristic so if you were to ask me what I think makes. Humans human this. Is what it is is that we seek meaning, in. All, areas of life we are compelled by meaning if you offer us a meaningful, answer. Or solution we. Are compelled by it how. Many of you are Douglas. Adams fans anyone, a few, okay so you already know where I'm gonna go with this in, life. And the Hitchhiker's, Guide to the galaxy series the answer to the great question of, life the universe and everything was. 42. Of course. So. Douglas Adams wrote or said in interviews that he chose 42, because it was not too high and not too low of a number and cuz it was just funny it is but. I don't know if you know this but in in on. Reddit you can find this and a few other places collected. Around the web there are, kind. Of collections, of alternate, explanations, for why 42, actually, kind of makes sense as the, explanation of meaning, in the world so. For example there, are 42, characters in the phrase it's the answer to life the universe and, everything. So. Right. You're, convinced now right no or also there's like 42 dots on a pair of dice so. That, answers everything, which, I thought was just kind of a throwaway explanation, but my husband said well life is kind of like a roll of the dice so, I thought well I really, I don't know, others. My, favorite. Of them is this. 42. Is apparently the Unicode character, communicate. Value for the asterisk, character, which, as you may, know is a, wild-card, symbol often, in computing which, means it can mean anything. Right. But. Okay so in me and it's obviously just a coincidence, because Douglas Adams didn't mean it that way but. That's, the important, point is that even, though Douglas Adam didn't mean it that way and it. Is just a coincidence it is an absurd and poetic, and beautiful coincidence but. We always make meaning the way we have always done and always will which, is by ascribing. Different, significance, to different events based on how and how much we value them, or in, other words by making it up as we go along. And. I think that's the encouraging, thing about this is that even. Though we talk about robots. And automation and, AI, and, in the broad mainstream. In a scary way what, this suggests is, that there, is this kind of open, interpretation. To the future we, get to make meaning. For the future as we go along we get to decide the future as we, go along, you get, to decide the future as you go along and that's, really incredible. Because, right now the, the possibility. Is the power of what's happening, within, technology and within the scale of emerging, technologies, means, that we have the capacity to create. The best futures, for the most people there's. Really this pop this potential, and I think even an ethical responsibility, to, think about how solutions, can scale to that. Sort of level. So. Let's go back to unpacking, create meaningful human experiences, at scale and what is it that human experiences. Really describes. We. Talk a lot in business about customer, experience user, experience, or depending. On your industry may be patient, or guest or visitor experience. Or student experience we. Don't often in, many. Industries talk about, human experience, in this integrated, way in this way that brings all of those roles together and appreciates, the fact that there is this kind of holistic.
Human. Experience, that that transcends. Any of those roles that, you are we, are all of those roles at any given point in time and so, even though you may be performing. As a customer, in a customer experience you, are still a human coming into that customer experience, the. Important thing about that is the, transcendent, empathy that can come from understanding, the, baggage, the context, that someone brings to that interaction. So. There's an opportunity to create these more dimensional, interactions. These more integrated interactions, and so to create more meaningful human, interactions, it turns out we, need to design more integrated. Human experiences. You. Think about how to blend, all of those roles and understandings, together and bring. An understanding, of where someone has been where are you meeting them in the world and how you can create these, kinds of senses of dimension, and. Holism, so. I promised. A Venn, diagram to a friend, earlier and I have it the. Best Venn diagram in the entire world, I'm. Sure you all have seen this if you haven't you'll, want to rush out and get this t-shirt right away, tensile. Graphics, makes this Venn diagram, but. The illustration. Here really I think gets at the point when. You think about what, is possible on one, side of an equation such, as the, best technology, - or the technology, to make business better and what's, possible in that other side of equation like what's, possible. To make technology. Better for humans it's. Only by really thinking about the intersection, of those things that. You really come at the, best, solutions. Like. Platypus. Keytar you don't get platypus, keytar until you're doing some serious both anding so that's. The, opportunity and really what we're talking about is augmenting. Human experience, with. Data and context, so the broader opportunity. In a technology sense, is to really think about where.
Does Someone where are you meeting someone in the world what data do you have to understand and appreciate where. They come from what their preferences, are what their tastes are and. How can you create context. That addresses. The objectives, that you have as a business and the objectives, they have as a human and the, role that you're meeting them in and the, alignment of those objectives well how can we come at that in a way that that provides that and so, I actually kind of think of this in a way as being meaning, as a service, in a sense it's, an opportunity to think about offering. Up a meaningful. Construct. That aligns your, objective, and their objective, and providing. The the the, hooks in a sense to, be able to expand, upon that and I really mean any meaning, of meaning so, meaning as, we talked about it could be at any level we talked about meaning. As it relates to communication, so. I'm linguist by education, so I think about the, semantic, layer you know how we communicate. With one another what we convey across. Our communications. With one another but, it can be all the way through you know you probably spend a lot of your time if you do a lot of development. Or engineering, in patterns. And significance, that's probably a layer, that you spend a lot of time in but, it could be all the way out to sort of the existential and cosmic, layer what what is it all about Alfie. You know that sort of thing I, think. In a sense it's almost like API thinking, for everything you can really sort of think about how, one. Idea, integrates, with another and how what, is it what is meaningful on one side like the business side can. Be meaningful, on the human side of the equation how do you provide you, know sort of hooks and intelligence, across those, different parts of the experience, and make, sure that that meaning, is being transferred, through that layer. The. Integration. That most, brought me to this realization. Is thinking about how the design, of experiences, online now, regularly, intersects, with, the design of experiences, offline but, more and more as we think about physical. Experiences, they come with some sort of digital component, or some, sort of track ability, or traceability, with. That that physical experience or when we think about digital experiences, we have to think about the physical context, somebody might be in as they, encounter those, interactions, so.
I Wrote about this in my last book pixels in place, so. Thinking about things like the Internet of Things and wearables, and beacons and sensors and all kinds of connected. Smart, devices and how those bring, that sort of connective, layer between. Those two worlds but the important, point about. That is that just about everywhere, interesting. That. The physical world in digital world connect, that connection layer happens, through us through humans, through our human experience. It's our movements. It's our behavior, it's. Our patterns, it's what we want what we do what, we indicate that. Really creates, that connection so. Again. It comes back to sort of thinking about that integrated. Human experience, so. I proposed this model in pixels. And plays which. Is integrated human experience, design thinking. About how to blend. Those, online, in contexts. Thinking. About how to kind. Of come across all the different levels. And roles of humanity, that you might encounter, thinking. About how to think about experience. In an integrated way interactions. And transactions, across all the different touch points that you might have and, know. At the way end of defining, the, word design, which. Is the adaptive, execution, of strategic, intent so. You know you have an. Intention you have a purpose, to what you're trying to do with. Any given design, initiative. And you, know that you're going to probably, not get, it exactly, where you want it to be on the first go so. We need to build an adaptive, iterative, process, to this and, the, more we do this around a framework of creating, that meaningful, interaction, and that dimensional. Relationship, between, business. Entity. And human. That's consuming, that experience, the, more we stand a chance of conveying some sort of meaningful truth. So. The elements, of integrated. Human experience design as described. In pixels in place I'll go through it really quickly because what I want to get to is that with, tech humanists I've actually built out upon, this to, a more automated understanding, of experience, but. Within integrated. Human experience, design in pixels, in place, we. Look at integration. Of course that kind of comes along for the ride so we're already talking about all these layers that, are being integrated the, online and offline contexts. We're. Talking about dimensionality. So how, does something come to life across, different, sort, of touch points or, ways, in which you interact with people how. Does how, do the metaphors, and cognitive associations, come to life what sorts of intentional, things are you communicating through, all of the choices that you're making about. The language that you use the iconography, you, use and the, cognitive associa bringing, along with that cognitive, associations. You're. Bringing along with that intentionality. And purpose so how have you defined what it is you're trying to accomplish and that comes into play at a, more holistic macro. Level as well which we'll get to you in just a moment and, a value an emotional load like where are you meeting someone in the world how challenging.
Is That context. If you're designing for an encounter, at a hospital, for example it's going to be a very different type of value. Or emotional load then if you encounter, somebody at. A Children's. Museum where. They're having fun hopefully. Having fun. Alignment. Is of course that that sort of foundational. Principle. Of, understanding. What the business objective, is and understanding the human objective, and making sure that they are as tightly aligned as possible, and then. Adaptation, and iteration, being of course that. Process, of making sure that we. Are building upon what we've learned we're using experimentation. And and, that that mental model, of building, our, learnings, as we go, there's. Also this premise. That. Experience. Has sort. Of - in. A, sense two layers, to, it. If. You think about, human. Nature as this sort of ongoing. Truism. Like we all have throughout time needed. To drink water for example but. Then there's the shape of that experience and how it kind of gets packaged, up and dimensionalized. And so you can see this bottle of water is. An example of saying, well if. I were to put that water into sort of a heavy glass bottle and label, it with some sort of minimalistic, typeface, sort of brand and you, know create that whole aesthetic, it has this kind of hipster vibe to it maybe I feel like I'm being, a more aspirational, version, of myself because I'm drinking maybe, even the same water out of this cool bottle and I feel like a better version of Who I am, then. If I just drank it out of the tap water tap glass or whatever but. So there's this kind of ongoing way in which shapes. Evolve and, it's, important I think to recognize that as we create these integrated, experiences. That human. Experiences. Do evolve but the shapes will always, change more readily than the nature and it helps us get into contact and sort, of create this continuity. Across time with. The human nature that persists, throughout the experiences, that we're designing for and, yet. Be ready to adapt to the changing shape of experiences. So. With that that. Leaves us into this this opportunity, to think about how, machine. Led experiences. Can, actually be more meaningful the, more we're thinking about automated, experiences. And artificially. Intelligent experiences. How can we think about making sure that the humans that interact with those are having as much of a sense of meaning and significance and. And. Dimension, to those, so. What, I proposed in tech humanists is that. We don't just automate, the meaning well menial, we automate the meaningful I'll go through each one of these in detail of course that. We automate empathy that we use human data respectfully. And that we reinvest, the gains in efficiency that, we get in business from, automation, back, into humanity and human experiences, at least at some level and so, we'll talk about each one of these I'll. Start with this I think. A lot of times when we talk about automation, are. Based. Understanding. Is that we should automate, menial, meaningless. Things, so that humans, can do higher-order tasks. Which, is a nice, enough premise, until. You start thinking about that at scale and, start imagining a world in which all, kinds of functions have been automated, and most of our world is automated, and most of our interactions are with machines and they've. All been automated to be meaningless, so. I think it's a it's a gas and a both/and sort of scenario we do need to think about automating, the, menial, meaningless, functions. To free, ourselves up, to think about higher order things, well. We also need to think about what's working what, are human, interactions, that, convey some level of empathy and nuance that create create some sort of significance, and dimension and how, can we kind of work, to automate those as well how can we capture some of that significance.
In Those automation. So. In this way we're talking about using data and technology, to. Scale not just for efficiency but for meaning to, think about ways that we can actually create a sense of dimension in the world around us, one. Way that that works is I. Like to think about this model of this relationship, between metaphor, and metadata, and. I, think. The easiest way to explain, this is a is. A slide. I stole, from Brian, Chesky the, CEO of Airbnb when. He was demoing a couple of years ago the. New campaign, that they were launching, at the time which was they don't go there yeah, don't go there live their campaign, anybody familiar with that you guys run across that at all so, the idea was you know even if it's only for one night, go. To every place you visit as if you're a local you know treat that city like you're a local and, this. Slide was an illustration, of how you could experience a different, type. Of. Approach. On, TripAdvisor. Versus, with the Airbnb approach, of trusting the local, experts but. Note that I've said so this is obviously Paris, and note. That every, thing. On each list is different except for one which is the Luxembourg, garden which is my favorite place in Paris so Jamie, but. Each. Of the other things on the TripAdvisor, list, it's, really just a, brute. Popularity. Contest, right it's all just what are the most sort. Of bucket. List items, that someone would associate, with Paris and on. The Airbnb side, it's. Who has, the, most significant. Understanding of the city of Paris what did they recommend, as being, the places that you sort of must visit, and must experience in Paris and. What I think is interesting is when you think about the metaphor, that's, really underlying this it's clear. That the, TripAdvisor, metaphor, is much more about this kind of. Casual. Tourist experience, of the world this kind of conventional, understanding right, whereas, the earth E&B thing is that sort of don't go there live there this knowledge of the expertise, and then the metadata clearly, is it's like the same city these are all the same landmarks, they exist in either case but, it's one is being rated for popularity. And one is being ranked for, expertise. Or authority so. The way that these two sort. Of dimensions, interact with women it creates, this more a meaningful understanding, of. What. The company is trying to achieve and how it brings it to dimensional, life before, for the person that's interacting, with it because. That meaning, informs, the purpose that, the company is bringing to life in their experiences, and. The. Purpose of the company that they're trying to bring to life sort. Of fosters. The meaning that, the person is going to experience, when they interact with with the touch points that the company. Creates if they've done it well and the. Nice thing about this when you think about how, this really comes. To life in an automated machine. Led way is that. Humans. Really. I think when you think about what the research. Shows what, we most thrive on is a sense, of meaning and common goals and a sense of fulfilling something bigger than ourselves, whereas, machines thrive, on this sense of clear instruction, right and what. Leads to both of those things is purpose now I'm not talking about purchase purpose like in this kind of touchy-feely you. Know spiritual, sense necessarily I'm. Talking about purpose as a set, of, clear. Instructions, or as a sense of clarity about what.
It Is you're trying to achieve and what that does is leads to this ability, to kind of bring all your resources to bear in a very efficient, way and to, align all those resources to set priorities very effectively, and make, sure that everybody is kind of rowing in the same direction. My. Favorite example of this of companies. Setting a strategic, purpose and really using it to operationalize. Around is Disney. Theme parks, and. You, know from a digital transformation perspective. The my magic band program how. Many of you have been to, Disney World or one of the Disney theme parks since they've introduced this it. Is pretty magical, right, like so they have articulated, their purpose. Statement, as create. Magical, experiences, it's. Really just those three words create, magical. Experiences. And. So you think about cross the organization, just about anyone, in any function, can understand. How, they can solve problems relative. To their scope, of their work as it. Relates to creating, more magical, experiences, like a problem that's brought to them they can just go on I know how to solve this as long, as the company actually sort, of gets in line behind that and allows, them the autonomy to solve the problem the way they need to but. Think about that as it relates to digital transformation, and deploying a billion-dollar, program. Which, this was an, that investment, scale for. The company and you can do that with complete confidence knowing, that this. Magic band is going to allow people to be able to go around the park and use it as payment is it as access. Use. It as sort. Of preferences, and all kinds of information that's. Our tracking that certainly, gives, a lot of useful information to the company as they sort, of merchandize more effectively, and so on, but. That that that ability, to, translate. The. Purpose. Into a deployment, at a billion-dollar scale is very, clear from from that data. Program, so. We can design experiences. That are aligned with strategic purpose, so. That we can actually see that, understanding, of purpose scale to. Massive, levels and purpose. Is the shape meaning takes in business so. That's, how we get that meaning to be felt and understood at a human level by, the way I keep talking about scale so. I want to unpack that a little bit too so. When. We think about creating meaningful experiences, at scale. Normally. When we talk about scale, and like a start-up or a corporate business a corporate, growth, sort of scenario we. Are talking about like, removing hard, limits, so that growth opportunities, can flourish and usually. We're talking about that in terms of multiples, let's say right like 3x, or 4x or 5x or, 10x if, you're very very lucky. But. What happens when an ocean, meets nearly. Unlimited expansion possibility. When. Data can model it and software can accelerate it an automation, can amplify, it and culture. Can adapt it and that's, what really we're talking about with machine light experiences, and, that's why it's so important, that we think about, creating. These in a more meaningful way because. If we don't create the meaning into the system what. Are we doing we're allowing absurdity, to encroach right and we don't want absurdity, to scale. So. My favorite example of. Absurdity, at scale is one that I I don't mean to knock the the, program or the product because I think it's incredible, the, Amazon go store how many of you have experienced, it in person it's. Pretty cool right like the idea that you can actually just walk into a grocery store you. Scan your your, app as you go in and. Then. Just pick up whatever you need and walk, right out and there's, no you, know sort of checking, out process, it just kind of knows but through cameras and sensors and so on it knows what you've picked up, and what to associate, with your account and you're, good to go so, obviously. We, have to talk about catch. Your jobs and what that means for the future of human work as that, goes to scale, but. Let's leave that set aside for just another moment because right now what I'm focused on is something else what what. Happens when you open the app for the first time and. You. Get this onboarding, it, explains that as you pick things up off the shelf the, censors know you know what you've picked up and as you put it into your basket or in your bag that.
You'll Be charged for it so. It says don't, pick up anything for anyone else. Which. Is fine except, that you start thinking about I don't know about you but I get, asked all the time to help people in stories you seem pretty tall you probably could help ask for that you. Know you could ask and and now it's like okay well I can't really help that person to get the thing off the shelf because it might charge me for it and there's, a way to get it charged back and an Amazon, might fix this before it goes to scale but really like. 3,000. Amazon Go stores have been announced before 2021. So, if this. Doesn't get fixed and if it is if something that we all start adjusting our, behavior, and not. Helping, other people in, the Amazon go store well, that's the future of retail we're talking about 3000. Amazon go stores by 2021, is going. To mean that retail. Environments. Are going to be this cash earless environment, before, too long and, so we won't help each other in any stores and how. Long is it before we, don't help each other at all and I know that sounds like hyperbole, at some level but what I mean to suggest is the, the idea that experience, at scale, does change, culture, and, I think that's important to recognize because really. Experience, at scale is, culture. What, we sort of all collectively, agreed to do with. Each other and how we agree to interact with each other is culture. And are, all of the work that we do creating, human experiences, sets, that context. It creates that that, modality, so that. Understanding. Is super, super important, so I do have a slide here and if anybody needs these slides I'm happy. To share them but. But it's slide the masks questions and it's in the book as well if we were to try to. Deprogram. The, absurdity. Of not. Helping each other we, could ask some questions, to step back from that and think, like how do we not create. Experience. At scale that's going to be absurd. How do we make sure that the brand isn't going to be impacted if we create products, or solutions that might scale in ways that are unexpected, how do we how do we pivot to deal with that you know what does that look like so, there's some, questions, we can ask to anticipate, that but, primarily I think, the. Challenges, or the opportunity, is to think about, meaning. And to think about keeping absurdity. From scaling this, is a comic. That was drawn for me by my friend Rob Cottingham, to. Illustrate, the sort of opposite. Of tech humanism, I don't. Know if you can read it it says it's getting harder and harder to hold on to my humanity but Wow is it easy to track my Amazon deliveries. And. So of course that's absurd. But. It's the idea that we aren't, thinking about what. Do we really want meaningful, experiences, to look like what do we really want our future humanity to look like how, do we create technology.
Solutions. That amplify, our humanity, and don't, get in the way of humanity. That's. Really what we're talking, about. The. Second, premise. Of, machine. Led machine, meaningful, human experiences, is to, automate, empathy, which, again may sound like it's a contradiction. But. I think there's an opportunity to think about the ways that any, kind, of experience that we design creates. Some kind of connection and to. To. Create as meaningful a connection as possible so how many of you remember the Seinfeld episode, where, Kramer. Got a new phone number and it, was one digit off from Moviefone anybody, remember this, so. Anybody, remember Moviefone I, know. The app just sort of ended as of like a week ago but but. In the 80s. And 90s or whatever we all had to pick up the phone and actually call a service, to tell us what movies were playing and in. This episode kramer, had gotten a new phone number it was one digit ah from movie phone and, it's. Obviously, touch-tone, service so he couldn't understand, the touch tones that he decided that he was going to impersonate a movie phone but. He couldn't understand the touch tones so he ends up just saying why, don't you just tell me what movie you want to see and. I. Always, find this to be such a prescient. Example. Of how we think, about machine. Driven interactions, and how we think about what human. Interactions, look like the sort of relationship between those two so. I think of the movie phone Kramer model, as a, sort, of agile, deployment, of emerging, technology, that, you can think about the, the. Robotic. Interaction. And the human interaction, as being. Somehow interchangeable. With one another so that you can actually, use, human, interaction, to gather patterns, that, you will encode as. Chat. BOTS or other types of automation and not. To suggest that you would lie that, you would print present a human and. And have it be posing as Moviefone. Or or whatever, your equivalent is but. Rather that you would have some kind of agile, human, based interaction, that, gives you the insights, to be able to create scripts, and create patterns. That develop, that help you develop frameworks, for automation. And. Of, course you're starting with if-then, statements, but you're quickly trying to work beyond that if then to get to the nuance so, if them is easy to anticipate right and the kind of frequently. Asked questions, model of automation. If you're saying like if. You're automating, let's say a chat bot for a bank you know that a lot of your interactions. Are going to be about how to change your password for, example or how to set up a new account so if someone, wants to create a new account then here's the answer and here's the the sort of flow diagram, that you can block them through but. The nuance beyond that is I need, to change my password because. My, ex is stalking. Me and it's a dangerous situation and, there needs to be some human. Interaction. There needs to be some human nuance to, that experience, so that's, more where the empathy. Gets automated into the process, is finding, those, types of interactions and, finding, the opportunity, to build out the, relationship, between the, automated and the human and. Also when we're looking for patterns that we're not just looking for. Arbitrary, patterns, and encoding, those, arbitrariness. It also, sits in opposition to meaningfulness, in much the same way that absurdity, sits in opposition to meaningfulness so we want to make sure that we're finding meaningful patterns and automating. Those, because. In all of the, work that we do with. This we cannot leave meaning. Up to machines machines. Won't, do, meaning that's. Just not something that machines are really equipped for so, it has to be humans, that determine, what what is meaningful and I love, this example I know many of you probably work around, image, recognition or, AI and so you know this dilemma. Very very well it's I know a lot of algorithms, have advanced since this day but you know the, puppy versus, muffin, sort. Of problem. Is one of my faves and it always gets a chuckle I see, some smiles in the audience but, but it's true that subtle nuances, aren't really where AI steins in many cases, at this point at least not at a, meaningful, recognition, level, not. Being able to say that.
The. Muffins, all have this certain meaningful, characteristic, and the human the puppies all have this certain meaningful characteristic, whereas. I believe, many of you are probably able to determine which one's a muffin and which one's a puppy pretty well here's some more by the way you. Know which ones a barn owl and which ones an apple you're, not having a trouble with that a bit which. One's a croissant. But. I think this one introduces, an idea that there, may be. There. May be opportunities for. Humans. To work, alongside, machines. In ways, that I add nuance, and, empathy, and understanding, to. The machine lad processes. Because. Humans generally do nuanced pretty well that's something that we are encoded, for we get meaning that's what we're about so. We're, able to add that into the value proposition, so when we think about the relationship between machines. And humans as we move into the, future. Of. Work, and the future of that sort of economy I think we're gonna add the most value by, being human and. Understanding, meaning and nuance and understanding, value and understanding, each other and adding. That layer to, those interactions. So. The third tenet, of the, machine led meaningful, experiences, is to use human data respectfully. It. Comes from this idea that when, we talk about digital transformation I, kind of feel like that's a little bit of a misnomer at some, level because we already, made a digital transformation, the moment we started spending all of our time in front of screens transacting. In front of in bits and bytes with each other so, that's kind of a done deal. And what's. Really more meaningful, than that is the, data transformation. The fact that all of this is happening with a data layer behind it that business, has all kinds of data visibility, and transparency through. The supply chain through, logistics, through operations, and everything, has this. Kind of clarity, and transparency about. What. Kind, of track ability is going on what's what's, measurable, and all that so. It's a really interesting, layer. To, work with but when, we talk about digital transformation including. Automation. And digitization all of that all, of the many nuances of that, fundamentally. What we're talking about is, agility. With data as companies, become more digitally. Ready and digitally transformed, they're becoming more agile, with data, based decisions, and, that. Data that. We're talking about is really. Our data it's human. Data for the most part business. Data is largely. About people. It's our purchases. It's our movements, through space it's our preferences, it's our you, know all of our tastes and indications that we've made and, really. What I'm saying is analytics, are people. Right, at, some level for the most part when, we are looking at graphs and reports and so on we're, generally, looking at the needs and interests and motivations of, real people. That, are they're buying from our companies and interacting, with them and driving. All of these decisions, for us and I. Think the flipside of appreciating. That and treating, that data with respect is, understanding. That what, we encode, into machines. Is really, about us that, we are putting ourselves and. Our, biases, into. Into, the encoding, into the algorithms, and everything that we create. So. The opportunity, I think. As we look at this tech humanists future is to. Encode the best of ourselves is, to think about how we, can create our most egalitarian, viewpoints. And our most evolved, understandings. Into. The data we model into the algorithms. We build and into. The automated experiences. That we design and create. So. We can use our data our human data to. Make more meaning, in the, world. And. We can recognize. That the, more we create relevance. In. Those in the alignment between business, objectives, and human objectives the. More we are creating a form of respect, but. That also that sort of caveat to that is that discretion, is a form of respect to that, we're also allowing people to say. Be forgotten, by. Us and allowing them to take their data with them and that we can not make people feel like we're creeping them out by knowing so much about them and, that.
We Protect, human data, excessively. That. We make sure we're being very very very careful, with, the data that we collect and use in business decisions, because we recognize that it is human data. The. Last point and it's a quick one because. This, may or may not be within scope for many of you but, that as we think about the. Gains, that we make in our businesses, through, automation and machine led experiences, that, we think about reinvesting, some of those gains into, how to create more meaningful human, experiences, at scale, and, I don't think it's really a mystery. Why that's so important, there, was a study done a couple of versions of a study done on what. Jobs are potentially, considered automatable and this is one, visualization. Of the data from that study that. Shows. The, the different, cities in the United States and how likely the jobs that are there are to be automated, over the coming years I zoomed. In on New York which, is where I'm from and you see 55%. Of jobs, are considered potentially, automatable, and you have to think about the socio-economic impact, that you have to think about the psychological. Impacts of that that, humans have had a very, deeply. Connected experience. To work that, we've derived a lot of our sense of meaning and identity from work we say who we are in terms of what we do and we. Have names like butcher a baker Tanner carpenter, and so on that, derive from ancestral. Jobs that have been carried down through our three generations of our family and. That's true across cultures. So, it's a really important, thing to understand, that jobs. Are kind of going to change there's going to be job displacement augmentation. And replacement, by, automation, and we don't yet know what that means for human meaning and, we don't yet know what means economically, we, don't yet know what that means you know sort of socio-politically. And so, there's a huge opportunity for us to take the, gains that we make in automation and have this, ethical contribution. Back into society back to humanity and say like what can we do to, foster a sense, of meaning and a sense of community and a sense of connectedness and, a sense of more humanity, with, that with those games. So. I think we can also think about repurposing. Human skills and qualities into higher value roles so as we automate that, one, of my the executives, was in a strategic, workshop I led ran. On the utilities company in South America, and he found through, our work, an. Opportunity. To automate a customer, service function, that. Was their, most heavily, accessed customer support question. And function and once, he saw, that opportunity, he saw that there was a way to take the humans.
That Were working in that job and create oversight. Positions, for them so that they could continue training the algorithms, that were going to create, that automation, so, obviously a very straightforward kind, of replacement. It, may not be a one-for-one we may see job loss anyway but, some of that the investment, is going to offer, up human, human, higher higher value, human roles so. Here are those, four. Tenets again and. I, think the, summary of this really, comes back to as you think about the work you're trying to do and how to create, these more meaningful, experiences, through, automation, and through artificial, intelligence, and so on it. Really comes down to this question and what is it that you are trying to do at, scale, so that's the purpose statement how, can, you articulate what it is your company is trying to do your team is trying to do you are trying to do at, scale, and for, me the, answer to that question is create. More meaningful human, experiences. It's just as simple as that but the way that I can do that is by speaking with groups like yourself, working, with executives working with leaders and being, able to help them hone, in on that purpose and really, get clearer on how to create those more meaningful experiences, that do align. The business objectives, with the human objectives that, do bring the business results and that, create a better future for Humanity. So. Because business, will have to scale through digitization automation. Business won't be successful. Turn without it it's table stakes but. Humanity. Won't be successful without, meaning, so. In for, that I thank all of you for, the work that you do thank you very much. Thanks. Kate we. Have a Dory there are no questions on it right now so we can ask a few local questions and if anything shows up then we'll we'll. Get those included, too but, I see a hand right here and can we get the. Mic test test okay. Hi. Thank you for the talk first off so. For the rhetorical, question you asked the very beginning of the talk I know a lot of people if not most people I know would answer a soul what, makes humans, human is, a soul so. What, advice would you give about, how to automate, religion. It's. A very interesting question I actually. Have, talked. With a few people about the work that they're doing around automation. And creating. Experiences. For people at scale around religion, and, I don't feel, like. I'm. In a really good position to be an expert on that it's. Not the work that I do but. I do think that religion. Is fundamentally, offering, meaning right so really we're talking about the same principles, we're talking about being able to offer people a lens into, what is meaningful and then, helping to scale that so, if if, there, is a solution that someone is trying to build that is some, sort of technology, product, for. Creating. Like a religious, experience, or a religious outlet for people or community, and, I think it really comes down to the same principles, it's, just like religion, is the industry, in that sense and we're trying to offer meaning. Through, those experiences I, would be probably, my best take, on that but I think it's a it's a more interesting question than that at some fundamental layer, and it sounds like a discussion over beers or something like that so. Do, we have another another, question yeah, -, you're Matt, hi. Thanks for the talk I was really struck by your. Point. About shared, experiences, forming, culture and. Obviously. We. In the technology, world have a lot of we, increasingly. Kind of shape shared, experience. So, in. The Amazon go expand, Amazon, go point, about like people not helping each other that's something.
We Can all probably agree as a net negative and even, Amazon I'm sure would agree but. There's, a lot of cases where we have, the. Potential to shape culture where the answer really isn't clear what is the right thing to do filter, bubbles being like one controversial, idea, whether they're a good thing or a bad thing. So. I'm wondering what's. Your take on how, we should approach these problems like what principle. Should we use in deciding how, to shape culture or what processes. Or institutions maybe, we need to make these decisions, yeah. Thank you it's a really good and big question, I'd. Like to, cop. Out and say that the entire book tech humanists sort of addresses, it but at, some level. What. It comes down to is, trying to understand, that that sort of strategic, purpose that, alignment between business. Objective, and human objective, and. I think if you're looking at a, filter. Bubble type of example, for example an. Example of something where a like, a social platform or, or. An, online community, is, fostered. Or or a media company is fostering. Through, algorithmic. Content, filtering and so on this, sense of disparity. Between people's. Collective understanding, of what is truth I. Think, you can probably come. To some understanding at some, level, of view. Of that that the, business objective, which may be advertising, or something. Along those lines and the, human objective, aren't aligned, there, so. I do think, that there there is still a useful. Framework, there, but. I do offer some additional ones in in, tech humanist as well, it. Is a really good and important, question. And it's an important point, for us all I think to consider in the work that we're doing because. There's so many net, positives. And net goods that come out, of let's, say with social. Media and the connectedness, we have with each other and. The way we're able to maintain really, chips with, such ease. Versus. You know twenty years ago but. Of course it does come with these these sort of associated. Difficulties. And and the challenges, of making sure that we're all sort of speaking the same language which, at, the moment I believe we're not we were having that question before that discussion, beforehand. So. I'm going to leave it at that I think there's a lot in the book which I'll just keep pointing back to that that. Does unpack, that a little further but I genuinely, think, that that framework of understanding what, it is the business is trying to accomplish and, what it, is that's good for Humanity how. Those things can be in line and it doesn't it doesn't have to come down to a humanitarian purpose. It just has to mean that we're not accelerating.
Something, That, is not ultimately, good for Humanity that that. I think is where the alignment comes, back to. Right. There's a question on the dory and it's sort of similar to a question that I had so I'm gonna try to merge them together. The. Question is on the dory, search. Like this scale. Tends, to force humans, to reduce their variety to, adapt, to machines, instead. Of the other way around so. Further. What, about ways to reduce scale, that are compatible with business. You. Mentioned. Distributism. Decentralization. Or, something. Else and, I'll. Add that I think that a lot of this technological change, is really. Coercive, meaning. Either, you get with it or you get left out particularly, around the job changes, that you talked about and, like. How, much is our responsibility, to bring people along like. To offer the lifeboat and, how much do people really need to get in the boat. Yeah. I think that's a that's a really. Difficult. Thing, to be able to break down and one one side or the other right like I think that the change is coming no matter what. What. We find though is the. Change is going, to be, disproportionately. Felt. So. Jobs. That are most likely to be automated, our jobs, like truck driver cashier. These. Types of things and what. We know is. Statistically, those jobs are disproportionately. Held by people of color, so. That that. Not. Fair, not equal, distribution. Is happening, so, we I think we do have an obligation if, we're trying to create the best futures, for the most people which, is what I would say is one of the underpinning, ideas. Or underlying ideas, of tech humanists that, we have to be thinking about how, to create, a more equitable distribution of. Opportunity. And how. To make sure that the the impact. Of automation, is not going to, destroy. One set of humans, potential. And while it increases, the potential, for enrichment of another. So, that, that, inequity is going to become even, more extreme, than, we've already experienced. So, I think it's it's an it's in our best interest as, humans to think about how to sort, of shift that and how to how to level that out not that people can't become wealthy, but, that we don't and create this even. More extreme distribution. Than we already have so, I think to some extent it's it's a imperative. For anyone who's creating, experiences which, is pretty much everyone that works, in technology, that works, around. Most. Fields that I've worked around healthcare, entertainment. And so on to, think about that the, change, that's coming and how to make sure that it is, that. We are creating as much opportunity there as possible but. Yes I think there's also there's. Also this kind of new, emerging, space around, opportunities. To retrain. People and, repurpose, you know get people to understand the new skills that they that they might have. I've. Shared some really great stats in tech humanists about. Programs. That were taking, let's, say prisoners, who were who. Would come out of. Sort. Of prison, programs and been able to retrain. Them into. Into. Communities, the jobs that they could keep and there was a point. One percent recidivism, within. This program so. I I urge, you to look into that example, there's. Just so many ways that I think an ecosystem, of answers, is really what's going on here we have to own the, responsibility as. Content, creators and experience creators and we, also have to recognize that, you know this is going to be a broadly, distributed Bradley, felt thing that. Is going to have inequitable, and equitability, inequity. So. To bring back a word that Paul put in his question. Decentralization. How, does maybe, decentralization. Help, with this by spreading. Power around, or control, around maybe, you just talk about decentralization, for a bit well. I I, mean the idea of spreading power runs kind of spreading control around is interesting. Certainly. We, have, seen, you. Know through user generated, content user. Communities. And you. Know platforms. Like meetup for example we were talking about earlier as one. Way that there's sort of tools that we can put in the hands of people that allow people to kind, of create communities, amongst themselves create, more human connection, those. Are going to be I think increasingly important. And the, technologies. Are there to sort of foster that and allow discovery within those communities allow. People, to sort of find, you know find each other and and connect. More deeply but. I think you know we we just have to be thinking mindfully.
About The the challenge, of not. You. Know amplifying. Those, sort, of net negatives, as your question was alluding to earlier with, the filter. Bubble and so on so. I'd. Love to hear more specifically. What about decentralization. Might. Be the what's sort, of nagging. On the person's, mind that sounds asking the question or on your mind. There. So. Whoever, is asking that feel free to ask a secondary call yeah and. If there's any other or, maybe for the sake of time we look for one more question in the room before we wrap up anything, else. Yes. So. I have a kind. Of a thought about some of this stuff in. Terms of you. Know do, you ever take your your, work and look at it as a lens, of looking at humanity, through the lens of what technology is revealing, about people. Yeah. I I have, looked at that but I'm very curious as to what is occurring. To you as you think about that well. I mean I used to do a lot of community management and so. I came out. You, know beyond the BBS's back in the late. 80s early 90s and, so it's this kind of thing. Where I realized, that a lot of what happened, online, was just, what. Happened offline but at a different scale and at. Different localities, yeah. And that, was sort of a, ha. Moment for me when I was a part of these little communities back. In the BBS days so. It's, it's just kind of like as technology. Has become more and more prevalent, in our lives it's. Something that I kind of look at almost flip, flip, the the conversation a little bit in my own head of like Oh what does it mean what does it say about people. Given. How we're using yeah. Yeah. That's what I mean it does kind of a little bit of that points back to the decentralization, discussion, as well but I like the the aspect you brought up, one. Of the. Aspects. Of this that I have looked at is that it turned it seems to me that our, digital. Selves. That sort of aggregate, set, of characteristics. That gets collected, through. Our movements, through our connections, through. Our interactions, in social. Spheres, that digital. Self is really our aspirational. Self most, mostly, that we are saying who, we most want to be and it. Seems ironic to, me that that. Digital, self is the self the, version of ourselves that is most, commodified.
By Business and most capitalized. Upon and, manipulated. By business. I think in our physical, manifestations. We, are much less prone to that kind of manipulation. And over. Capitalization. Yet. This digital, self which is our aspirational, self is prone, to that so I think this is the opportunity for us to kind of merge that understanding, and say well it is a human, that we're looking at in that digital you. Know sort of collected. Aggregate. Data, points, and so, we need to be respectful about that too so, I think that flipped version, is to say you know there's this way that we are interacting with each other in a way that represents who, we most want to be and who we most feel we are so. It's all the more reason why we need to be respectful, with the data that we collect and monetize, and you, within business to inform, our intelligent. Decisions, and our systems, so. I'd say that that's. Exciting to me Thank, You Kate and thanks, Google, for being, great audience for Kate and, I guess we owe us. All a round of applause so thanks. And. Kate especially. You.