Tech Humanism: Shaping the Future of Connected Human Experiences
With heavy emphasis in business on artificial intelligence, automation of various kinds, and digital transformation, the future of human work — and even humanity itself — can feel uncertain. While we often talk about user experience, customer experience, patient experience, and so on, we rarely consider what a truly integrated human experience might look and feel like. Emerging technology offers tremendous opportunities to facilitate solving human problems at scale more efficiently while offering better human connectedness. In her keynote presentation, Kate O’Neill will offer her take on a global transformation of technology and beyond that keeps humans at the center.
Intended Audience
Technology and business leaders interested in finding and integrating human experience with the connected customer experience amidst the global technology business transformation.
Audience Takeaway
Walk away with a fresh perspective on integrating human experience with emerging technology.
Speaker
Kate O’Neill, CEO, KO Insights; author: A Future So Bright, Tech Humanist
[Kate O’Neill]
Hello humans. It’s really good to be here, well, not here with you, we’re not here together, but I think we all are trying to be as connected as possible through these virtual experiences that we’re having. So I’m really happy that we’re at least sharing that experience. And I’m really excited to be here talking with you about the future of experiences and how we’re gonna be thinking about data and technology shaping those experiences.
So let’s talk a little bit about the future because we’re living in a very weird moment right now. And I think it’s making us think in different ways about the future and change the way we’re thinking about the future. So, you know, one of the things that interests me, that fascinates me about the way we talk about the future, is that through English literature, the only lenses that we’ve ever been given to look at the future through, are this dichotomy of dystopia versus utopia.
And so, you know, what really happens there is that we end up seeing all of these sort of scientific breakthroughs and technological marvels as things that are going to either create the perfect world or they’re going to destroy us. And let’s be honest, nobody really thinks that they’re going to create the perfect world. Like that’s not even on the table. Utopia is not something anybody thinks is gonna happen. We’re not like, oh, everything’s gonna go perfectly, right, and we’re gonna be living in an ideal world. No one really thinks that.
So all we do is hear about things like, remember when you heard about Dolly the sheep being cloned, like, did you, in your mind, did you think that sounds awful? Like there’s potential ethical consequences of this like crazy. Like there’s probably going to be a lot of problems with this. And that’s true, but there’s also incredible opportunities that come with gene editing and CRISPR and so on. So what’s important for us I think to remember, as we go into thinking about the technology driven future, the data-driven future, is to remember that the future isn’t going to be either dystopia or utopia. And that’s a really important point because for a while now, my work has been predicated on this question of how can humanity prepare for what by all indications looks as if it’s going to be an increasingly data and tech driven future, and how can I help people prepare for that?
So you may be wondering, like, what does a tech driven future look like? What are we talking about when we talk about a tech driven future, what does it look like, what does it feel like? So when we think about like the future of work, is it this, is it people managing robots who are sneaking peaks at kitten videos throughout the day? Probably not. This is probably not the future of work as we’re going to experience it, but more likely a more vivid example that’s more in your world I would think is going to be something like this, right?
Many of you probably have, in fact comment Y for yes in the chat if you have one of these kinds of smart thermostats in your home. And how many of you have thought about whether this is a physical or a digital device, or whether this is an online or an offline experience that this device creates. And you may already be ahead of me. Like this is both at once, right?
And the really important thing about recognizing that is to recognize that the physical and the digital world do connect, but their connection points are through our human experience and interactions. The things that we do, the things that we experience, the ways that our data connects our experiences with the way we move through the world, the purchases we make, the connections we have with other people, those things all generate a data trail and they have a location attached to them in many cases. So that reality of the ether and the physical world are all being connected through human experiences. And that brings us to this really intrinsically important point that everything is connected because when you take it back to the smart thermostat, and you think about how your thermostat settings are being passed down to a central server somewhere, and they’re being intermingled with the data from other people’s settings, and that’s being optimized by some algorithm and then fed back into somebody else’s personal space, like changing my thermostat based on different settings. That’s a really important thing to recognize, like your data and my data are affecting the way that we each physically experience the world.
And not just that, you can think about finance, you could think about retail, healthcare, all these different facets of human experience have all kinds of ways in which our data is shaping not only our experiences, but other people’s experiences. So super important point for us to remember as we go forward and think about how do we optimize them, how do we build the most responsible experiences that connect your and my experiences and create the best futures for the most people? Well, I think we need to remember these three things, business data that we collect, you know, like purchases and transactions and so on, that is largely about and describing human experiences. And then also the analytics as we talk about it, you know, the data we collect in business, that is primarily about human experiences, that is people, is what people say, what they do, it’s what they come to your website wanting from you, it’s what they express an interest in, it’s the shoes that they’ve been following around the internet that have been following them around the internet for the last six months, that these kinds of things, these aspects of data are people.
And then the third point is that technology, as we understand it, most often advances to fulfill some kind of business objective. That’s a really important point. Like innovations may happen, you know, people may come up with ideas for technology in garages in isolation, but the way they’re brought to mass market usually is to fulfill some kind of business objective. So taken together those three points when we put them all together, that business data is about human experiences, that analytics are people and that technology advances to fulfill business objectives, this leads us to a really crisp, nice point. If we align business incentives to human outcomes and then use technology to amplify that alignment, then we can make sure that as business succeeds through technology, it is going to bring humanity with it. That we’re all going to be aligned, we’re all going to succeed through that approach.
And that’s where the tech humanist idea comes into play, that we need purposeful, meaningful human experiences at scale. I’m going to break into how we’re gonna get there and what we can do to get there, but first we need to recognize that what we’re building is always gonna be about the best futures or at least the least damaging futures for the most people. That’s what we’re trying to get to. It has to be the kind of, the common objectives whenever we’re trying to figure out, which is the right way to go in any scenario, which is going to lead to the best futures for the most people. So how do we do that? There are three aspects we need to consider. One is to build our best technology and I’ll unpack what I mean by best here. We need to grow our best businesses and I’ll unpack what I mean by that. And we need to become our best selves. And I think that’s actually a pretty good place to start.
So we can start with asking this question, what is it that makes us human? Like if we’re trying to figure out how to be our best selves, maybe we should understand what makes humanity, humanity. So when you think about that, if you try to just think of one word, just that one word that for you really epitomizes what it is to be human, what is that word? Go ahead and type one word into the chat and we’ll just share with each other.
What do we think of, when we think of like, what really makes us human? And if you’re anything like the audiences I’ve asked this question of before, the answers are going to fall into two, pretty much two buckets, right? There’s gonna be one set of answers that are going to be like creativity or problem solving or even innovation. And that’s a great set of answers, but there’s gonna be another set of answers, probably even more of them than the first set, which is gonna be about empathy and love and emotions and compassion and understanding and those kinds of things. And those are both really great sets of answers.
All of the answers you’ve shared, I’m sure are great, except for the one of you who gave some sort of devil answer, like that was not a good answer, but most of you gave great answers. But what I think the answer is, for me personally, it’s this 25 or 30 year obsession I’ve had. And I believe that is what actually motivates all of humanity.
Humans crave meaning. This, I believe is the fundamental attribute of humanity. We love meaning making and we love meaning seeking. We just can’t get enough of it. We crave meaning, we thrive on meaning, we seek meaning. We’re always looking for why and how, and we’re looking for the significance of things. And when I say meaning, by the way, I’m talking about multiple meanings of meaning, because why not, right? So I’m a linguist by education, so automatically, I think about the semantic level of what we’re trying to communicate when we talk to each other, what do our words mean, what are we trying to say? But then you can go all the way out to the most macro and sort of big picture views of meaning, too, and think about cosmic and existential meaning, like, what’s it all about and why are we here? But then there’s all kinds of stuff in the in-between too, that has to do with purpose or truth or patterns or significance, relevance.
All of these things are all pieces of the puzzle of what meaning is. But if you think about it on every single level that you could consider meaning, and try to understand what we mean by meaning, what it always is, is about what matters, meaning is about what matters. So you might be like, well, that’s kind of interesting Kate, but how does this get us closer to solving what humanity is gonna do to prepare for our increasingly tech-driven future? And I’ll thank you for reminding me of that, but I can tell you, it actually does matter because we need to be thinking about innovation too, in a human centric way, and the way we do that is to bring it back to the fundamentals of meaning. So innovation could be said to be about what is going to matter. So as we think about trying to create those best futures for the most people, we’re always trying to figure out what is going to matter in the long run, what is going to matter to the most people? How do we make sure that we’re solving for those kinds of challenges?
You know, I have a fun story from my early days at Netflix, about how one of the first projects I embarked on in my new role as content manager, the newly created content manager role, was that we had all these movies and they had single genre associations. So you might have a movie and it was a comedy, or you might have a movie and it was a romance, but you didn’t have any romantic comedies, and right away as a romcom fan, I could see that that was a flaw. Like we were going to need more flexibility. And so I worked with the database team and we redesigned the entire entity relationship structure so that it was a thing of beauty. It was like, you could frame that thing when we were done. It was beautiful. We’d really gotten to understand this kind of multiple relationship. You could create sub genres. You could create all kinds of nuances to this thing.
And now, as you may have experienced with Netflix in the last few years, there’s all kinds of like nuanced things, like political auteur cinema, or Oscar winning 20th century period pieces, I’m reading some of the things from this slide, which is actually from my own view of Netflix, but this was all built from artificial intelligence and machine learning, looking at patterns of viewer behavior and using other people’s viewer behavior to recognize patterns and find meaningful connections between what they liked and what I like. And then it’s built on this very flexible understanding of the relationships between movies and how movies are connected to one another. And that work wouldn’t have been possible without the work that we did 20 years ago to make the genre relationships more flexible.
And so I point out to you that what matters in the future, what is going to matter may not even be all that obvious, but you’re trying to always solve for it one eye on now, and one eye looking into the distant future to try to make it more possible to bring more meaning and more nuance into people’s understanding and relationship with one another and with themselves and with one another and with the brand and with the experience itself. And that is all about everything being connected once again. So that takes us a little bit into how we build our best businesses, because we talk a lot about digital transformation and what we really mean is data transformation. And we’ve already established that data is people, right?
Analytics are people. So again, everything is connected. All of these experiences that we’re talking about that are data-driven experiences. We’re really talking about people at the end of the day. So whenever throughout this conference, throughout every keynote you hear, and every presentation you hear, every time you’re having a conversation with someone, whenever you hear the word data, do me a favor and try to swap in the word people and see what it tells you, see what kind of insights that brings you. And also when you hear the word tech, try to swap in the word human experiences, with the phrase human experiences and see what that tells you. It’s not always gonna work. It’s not always gonna be a one-to-one substitution that makes any sense, but sometimes it really, really will. And sometimes it’ll really give you a clue about what matters and what is going to matter in what you’re looking at and what you’re designing for. ‚Cause I think one of the things that we need to remember is that emerging technology like artificial intelligence and all of the other like intelligent automation and all the other kinds of emerging technology that we’re generally considering right now brings with it incredible capacity and scale, like we have never experienced before. And so with that comes tremendous responsibility.
Our actions and decisions are going to have outsized consequences. And we need to be sure we’re thinking about that. We need to be prepared for the possibility that what we decide on is going to be brought to such a scale that it’s going to have such reach, that we need to have thought about what it means at that scale, what it means to affect so many people. And I have a vivid example for you. In fact, you may have experienced this yourself. So there’s this premise of this concept store, Amazon Go, maybe you’ve encountered it. So it’s, Amazon’s just walk out concept, right? It’s a grocery store, but what you do is you have an app on your phone that has a QR code, and you scan that through the gate as you walk in, just like that, right? And it’s a grocery store. And so you take things off the shelf and it’s just like any other grocery store where, you know, you have every access to everything, but here’s the thing. There’s cameras and sensors, and all kinds of like a constellation of technology that’s watching you, it’s surveillance technology that’s watching your every move so that it knows what you’ve taken off the shelf. And by the time you get done and walk back out through those gates, I guess it would be like back out through those gates if I’m gonna carry my little visual metaphor forward, you get rung up and it’s right in your phone and you never have to go through a cash register. You never have to stand in line. It’s all very simple and seamless.
It’s actually a really nice experience, but here’s the thing, because of that limitation of what you take off the shelf is charged to your phone, when you start the app, it gives you this little onboarding and it says, don’t take anything off the shelf for anyone else.
But I would like for you right now in the chat to put a Y for yes if you have ever taken something off the shelf at a grocery store for someone else, or if someone has ever asked you, or if you’ve ever asked someone to take something off the shelf for you, put a Y for yes, I am pretty sure there’s a lot of Ys in the chat right now because I’ve asked that question everywhere. I’ve asked it in Australia, in India and China and Europe, Canada, U.S., I’ve asked it all over the place. And it is a nearly universal phenomenon. In fact, I was rewatching the movie Double Indemnity not that long ago, if you remember it, it was a wonderful movie, great film noir.
And there’s a moment when, as Barbara Stanwyck and Fred MacMurray are conspiring to cover up a murder, which I realize is a spoiler, but it’s an 80 year old movie people, so catch up, okay? A woman just comes up and asks Fred MacMurray if she will reach him, or sorry, if he will reach her a package of baby food that’s on a top shelf she can’t reach. So he does, as they’re conspiring to cover up a murder. And it’s a great little moment of humanity. It’s a kind of a funny moment in this film noir, but it’s also a great vivid illustration that this is not a new concept. It’s a concept that’s been around with us for a long, long time, and it’s very pervasive.
And so what I mean by talking about this is to point out that think about Amazon and the scale it has. It’s talked about rolling out Amazon Go to like 2000 different stores, you know, it was talking about pushing out that model to 2000 retail locations by the end of 2021. And now I actually believe it’s changing to where they’re going to start merging that in because of they acquired Whole Foods, right? So that’s 2,600, I think, stores or something like that. And starting to roll that out through Whole Foods, but think about it, this is Amazon. They have the scale to do whatever they wanna do. This is going to become the dominant model of retail.
And so what I think about with the thought experiment that leaves me with is how long will it take before we’re just conditioned to know that we don’t help each other, not only in Amazon Go stores, but maybe not in any other grocery store or any other retail store? And that may sound like hyperbole, but I actually think you could go further, let’s before we talk about the hyperbole, let’s just say like, how long do you think it would be before we were socialized just not to help each other at all? Does that sound like hyperbole, maybe, but here’s the important point to consider, is that when you think about experience and you take it to that level of scale, it really does change culture. Do you know why? Because experience at scale is culture.
So what we decide to create and what we decide to bring power to and amplify through data and technology, we need to be sure is the best of what humanity can do. And that’s why the consideration of trust and the future of trust is really important here, too. To know that in the latest Edelman Trust Barometer, there’s been an opportunity for companies to step out ahead. Corporations have had an opportunity to stand out as the most trustworthy entity of the four types that Edelman studies for this. So NGOs, media, and the government versus business, business is the leader here. So business can be thinking really progressively and thinking about how do we introduce more trust building components in our experiences?
How do we create these trusted relationships with customers, with people in the world and think about things like social platforms and algorithms and filter bubbles and false news and the world we’re living in that feels like it’s really hard to understand what’s true and what’s not, and who we can trust and who we can’t. It’s really important for us to make sure that we’re thinking about that attribute and making experiences and interactions that are worthy of people’s trust. That’s what it means to think about experiences at scale changing culture and thinking about trust and making sure that we’re bringing the best of humanity into light, because we cannot give absurdity a chance to scale. It will take every opportunity it can get, which is what I think about when I think about this Bill Gates quote about automation, where he said that automation applied to an efficient operation will magnify the efficiency, but automation applied to an inefficient operation, magnifies the inefficiency. But I think you could change that quote just a little bit to where you’re talking about automation applied to a meaningful experience, amplifies the meaning, and automation applied to an absurd experience will magnify the absurdity, and that’s not what we want. We want the good stuff. We cannot leave meaning up to machines to determine, we cannot let absurdities scale. If we meaning up to machines, if we say, hey, AI, figure out what the most relevant thing in this situation is, we will probably let that lead to our worst tech, not our best tech.
If we think about, you know, the way that AI processes nuances, that’s not really what AI is so good at yet. Yet, maybe it’ll get better, but you may have seen these images before. It’s a classic image recognition dilemma of muffin versus puppy. It’s mostly been solved, many image recognition algorithms now can process the difference between a blueberry muffin and a Chihuahua puppy, and here’s some other examples for your amusement, but the point is we can tell these things apart when AI couldn’t, because we have sense memory. We have the ability to remember times when we have petted nice fluffy puppies. And when we have, you know, eaten roasted marshmallows and hopefully not eaten puppies and petted marshmallows, that doesn’t make any sense. But what we need to remember is that sense memory, the emotional recognition that we have, the things that we recognize when we see these things and know what they feel like, what they taste like, what they smell like, that’s all part of meaning because senses help us make meaning. And that’s an advantage that we have as humans over machines today. That is how we lead into our best technology is by understanding what empowers us as humans.
The meaning that we understand, the sense that we understand, the way that we understand the world and the way we build around it. So what if we took that understanding and used data and technology to transform everything around us, the experiences around us so that it helped humanity actually thrive, what would that look like? Well, I think it would look a little like this. If you’re not familiar with it, this is the United Nations‘ sustainable development goals diagram, it’s 17 goals. And they’re things like no poverty, gender equality, you know, quality education and on and on to things like quality of life on land and life below sea. So it’s a lot of different kinds of things, but what’s interesting about it is that just about every company out there can figure out one of these 17 that it most aligns with and figure out how to build its strategy in alignment with one of those goals, if not multiple of those goals and try to help really scale the best of what makes humanity thrive.
And what’s even more cool is that if you think about how AI addresses these goals, there is examples currently in play. These are proof of concept headlines that I’ve gathered together and showing in the slide where actual AI demonstrations are in effect to show how AI could be brought to bear on things like detecting cancer or combating human trafficking, or really important things that we can actually use AI to help humanity thrive and help solve human problems at scale. That’s what we should be doing with the power and capacity of emerging technology, solving human problems at scale. And we’re gonna have to do it in alignment with what makes business thrive, absolutely, but make sure that we are looking for that alignment and bringing that power to the human problem, the equation, because everything is connected. And that’s the message we have to take away from this.
We also need to remember that in order to solve human problems at scale, and in order to create the best futures for the most people, we do need diverse perspectives. We need people leading projects, we need people participating in projects who represent a wide range of experiences and perspectives to make sure we have created the most inclusive and the best experiences for people. So we also need to remember to use human data respectfully, protect human data excessively, and we need to remember to use that data to make meaning.
Remember this, if you remember nothing else about this conversation, machines are what we encode of ourselves. They’re the biases and values we encode. So why would we not encode our best selves? Our most enlightened selves, our most egalitarian viewpoints, our most evolved understandings of the world around us and each other. Why would we not do that? Of course we wanna do that. So let’s do that. Let’s make sure that when we ask ourselves, what is it that we’re trying to do at scale with our businesses, with our design work, with technology, that we think about helping humanity prepare for that tech-driven future, and that we create more meaningful human experiences for all of us, because remember that tech driven future is not going to be dystopia or utopia, it will be what we make of it. And I’m so grateful that you’re helping to make it the best futures for the most people.
And for that, I thank you very much for your work and your contribution. Thank you for having me here today.