Nodes of Design#121: Designing for Collision with James Song

Speaker A: Hi everyone. Welcome back to Notes of Design podcast and I'm your host, Tej. And today we have a very special guest joining us. Our show is all about exploring the intersection of design, technology and human connection. And today we are in for a treat. It's my pleasure to introduce James, a seasoned design executive with over 20 years of experience building teams, products and brands that sit at the nexus of digital innovation and tangible human experiences. James is currently the VP of Design at Tinder, where he leads the charge on brand, product and content design, as well as user research. His impressive career also includes being the head of Design for Meta AI Research where he helped develop the next generation experiences driven by breakthrough AI research. Prior to that, he was the Director of Product Design at Uber, responsible for platform services, micro mobility, design systems and user research, all aimed at building smarter cities and enhancing how we move. And before all of that, as a Creative Director at Frog Design, he led teams to drive human centered innovation at the intersection of design, technology and brand for both enterprises and early stage startups. Today we are excited to dive into a topic that resonate deeply with our community, that is Designing for Collision. This theme encapsulates how unexpected, sometimes even serendipitous interactions in our hyper connected worlds can spark creativity and lead to true innovative solutions. So whether you are a seasoned design professional, a beginner, or simply curious about how technology is reshaping human connections, stay tuned for this conversation. It offers a great insights, practical advices and a lot of inspiration. So, without further ado, please join me in welcoming James to Nodes of Design podcast. Hey everyone. Before we dive into today's episode, I wanted to quickly share some exciting news. My new book, Nodes of Wisdom Lessons from 100 Creative Visionaries is officially out. This book is accumulation of insights and experiences gathered from interviewing some of the most inspiring minds in various creative fields. I'm thrilled to share their wisdom with you all. You can find the links to purchase a book on Amazon in the episode description. Be sure to check it out and let me know what you think. Hi James. Welcome to Nerds of Design.

Speaker B: Hey, how are you? Thanks for having me.

Speaker A: All good, James. So how was your day so far, James?

Speaker B: It's going well. Uh, I'm here in San Francisco and uh, it's a little chilly outside, but Chile for San Francisco, so not, uh, too bad. I can't complain.

Speaker A: Thanks, James. So if you could give a brief about yourself to our listeners out there.

Speaker B: Yeah, um, I'm James. Uh, I'm originally from Atlanta, Georgia and uh, I grew up studying, um, Art actually and studying um, the creative side of things and didn't uh, have a ton of exposure to uh, a lot of the technology things. But we did get a uh, computer, a Macintosh, when I was uh, early, uh, early days. And it really kind of sparked my imagination and it really kind of unlocked a lot of things in me that there were new tools available to kind of express yourself and ah, to really translate kind of what you're thinking onto this new digital medium. And so ever since then I've been on a journey kind of exploring uh, the world of the digital and the physical and all the things that it means. And um, yeah, uh, I've been working in design ever since.

Speaker A: Thank you so much. So what was your journey into design? How did you start? What are your tips for the beginners on starting the design journey?

Speaker B: Yeah, um, like I said, I'm originally from Atlanta and I didn't have a ton of exposure to uh, the outside world, I'll say. And um, I initially went to school for computer science because that was the thing that you did in Atlanta. There was a really, really great school there called Georgia Institute of Technology or Georgia Tech. And that was just kind of what you did. And so I was interested in computers and I think that was not going to be my life. Um, and then along the way I discovered uh, this, this little group at site, Georgia Tech called the Graphics Visualization Unit. And it was the first time I ever saw how people were using computers to draw on the screen. Um, and it really, really sparked my imagination and did a lot of exploration into kind of what was going on there and the different tools and mechanisms that they were using to kind of draw things on the screen. And then I didn't really want to get into the super technical side of things and I was studying computer science, but I discovered 3D animation along the way, funnily enough through, through Pixar movies and those types of things. And so I said, oh, that's what I want to do is creative but it's highly technical and it looks really real but you're telling human stories and uh, kind of resonating emotionally with people, uh was kind of my goal. And so I started going really, really deep in 3D animation. Uh, and then along the way in finishing school my parents were kind of like, just finish something. Just, just finish. Like you're kind of changing your mind all the time. Please just finish something. And so I was studying 3D animation and there weren't a uh, ton of schools around me, so I actually moved to San Francisco from Atlanta to try to study and finish my 3D animation studies. And in finishing my studies I actually discovered graphic design. I said, oh, this is actually what I'm more interested in. Uh, it was highly creative, highly technical. You know, the Adobe suite was very, very difficult to learn. And uh, all of the, all of the technical sides of things of graphic design were really, really interesting to me. And then the intellectual side of it was really, really interesting to me in terms of craft and philosophy and artistic vision and how do you marry that with the business side of things? And so I really discovered graphic design kind of by way of computer science and 3D animation. And so I started working as a graphic designer, uh, in the marketing side of things and businesses. And my first job was in a video game company, uh, designing, you know, marketing materials for a bunch of video games. And just learned a lot about the process and how I work with other people. And um, I started to ask, you know, higher order questions about why we were making the things that we were making because I wanted to really flex my graphic design skills, you know, and people like Paul Asher and Pentagram were really, really influential in my thinking of what graphic design was. And then I started to ask a lot of questions about why we were, you know, running the campaigns that we were running and the strategy was, and why this makes sense. And um, and then I moved into kind of what, what people would call brand experiences in that I was, I was, you know, a graphic designer who could code effectively. And that made me the web person. You know, I became the web person inside the company. And so I was designing all these, you know, 360 degree advertising campaigns and talking about a unified theme and a campaign vision. And we started building all of these digital branded experiences to tell stories around our products. Um, I went to the agency side, uh, and helped start like the digital arm of uh, an agency here in San Francisco. We worked with a lot of people like Levi's and Disney and Virginia, um, um, helping them think through their digital strategy on how to be present and how to engage digitally. And then I wanted to go, I wanted to learn from, from the best. You know, I, I felt like I didn't know everything about everything and I was being asked a lot of questions and I was just kind of, I felt like I was faking my way into things. And so I had the opportunity to go work at a place called Frog Design. And Frog Design really was kind of a graduate school for me. And for folks that don't know, Frog Design is kind of A design consultancy in the vein of ideo, um, and Smart Design in those folks. And it really was a masterclass in how to think critically about design and really showed me, uh, the impact that design could have at the business level, at the user level and the societal level. And so I had a lot of fun just kind of going into these really, really large multinationals, helping to consult with them on using design and design thinking to influence their global strategy and all the way down to, you know, how to make billions of dollars in new growth opportunities for the business, all the way through to how to translate that new strategy and vision into the lowest levels of the organization, how to help people make trade offs and things like that. So I did that for about three years and then I decided I wanted to go in house and really shift the things that I was kind of preaching to people. So I landed at Uber right before, uh, their, their ipo. This is right after, uh, Dara joined as the CEO. And it was a time of vast change there, but I really was interested in the idea of smart cities and how we, how we exist inside urban areas. So I spent a lot of time working with the team on our product strategy and the roadmap and how we can use design to kind of articulate a vision for the future of what, what Uber's role in the development of smarter cities and more equitable cities. And then the pandemic hit and uh, everything got turned upside down and I took some time off to kind of take care of my family and was doing some consulting. I worked with a nonprofit with my, uh, old chief product officer from Uber, helping to think about how we can have digital and physical experiences that will bridge the gap during time like Covid. So we built a lot of tools for universities, for example, that would allow them to have students come back on campus and continue to learn while also being safe and being considerate about all the different Covid restrictions that were happening across the country. After doing that for about a year, uh, I was, I was really kind of in a bad mental state and I was looking for the next big juicy topic to jump into. And I had the chance to join Meta AI Research, um, and head up their design team there. And so I joined and I spent about two years working with some of the best, uh, AI researchers, product designers, engineers, product managers to really look at, uh, the emergence of AI and AI research and what that could mean for people and what that means for future experiences, um, for Meta's products. And so spent a lot of time understanding the research side of AI and spent a lot of time understanding the product side of Meta and really thinking about how to bridge the two and continue to add user value across, uh, all of our different product surfaces in the most empathetic way. Now I oversee product and brand and UXR at Tinder, where we're really focused on fostering in real life, meaningful human connections. And, uh, AI is going to be, ah, a central part of kind of everything that we think about in the future. Um, and the advice I have for beginners starting, uh, their design journey is to really be curious about people in the world. You know, one of the most important experiences for me was while I was studying, uh, 3D animation in colleges. I took a lot of different types of classes. I took a music theory class, I took a, ah, sculpture class, I took a political class. Um, and it really is about developing, uh, a worldview about how things are interconnected and how we all relate to each other. And you're not going to get that just by taking a bunch of FIGMA classes or prototyping, um, courses and things like that. Right? You really got to be a, uh, unique. You really have to have a unique point of view about the world and expand your surface area in terms of the things that you're interested in and how you understand the mechanics of the world and how messy everything is, because it's not easy and it's not linear. Um, but that's the challenge ahead of us. And I look at the design practice as a whole, and it's maturing very, very rapidly. There's more and more designers starting every day. So I think the unique superpower that each designer will have will be their unique point of view, their background, their abilities, and their, uh, taste level. And that's really going to be what propels you in your own career. So my advice to people starting out is to just really expand your horizons and try to be as curious as you can about them.

Speaker A: Thank you so much, James, for sharing such an inspirational journey and also those wonderful tips for our listeners out there. So let's begin our episode today on Designing for Collision. So could you please explain the idea behind Designing for Collision and how does it relate to the current age of connectivity?

Speaker B: Yeah. So like I said, I grew up in Atlanta and I didn't have a lot of exposure to the rest of the world. You know, um, I didn't meet anyone from Southeast Asia until I'd moved to California along with me in Atlanta. So I was really, um, insulated from the rest of the world. And so when the Internet took off, I was really just kind of using the Internet day in and day out to try to learn more about the world and what was going on and other people's experiences and things like that. And so if I zoom out and I look at kind of the first wave of the Internet and the companies that it's created and the products that it's created, Facebook, Google, Amazon, you know, all these large companies have really focused on connecting the world and all the world's information in kind of centralized forms. Right? Um, and the problem is that if you're not used to encountering people that are different from you, you can react in a negative way. You know, I see this in the rise of kind of global political polarization and in general kind of retreating inward and that people are building walls around themselves in their worldview. And again, it ties to kind of my work at Uber, where we were thinking about cities and the relationship of cities to people. Um, and cities are designed to kind of house lots of people in a small area, right? This leads to a lot of really amazing things like farmer's markets and impromptu communities and niche restaurants and grocery stores that you would, wouldn't normally come across. Um, some of the best healthcare lives in urban centers, right? And collisions between people who wouldn't normally meet, right? You're gonna run into somebody at the grocery store that you would normally encounter. And that has, uh, the potential for really meaningful connections, but it also leads to really bad things like violence and poverty and pollution and those types of things. So it's not a perfect solution by any means. If I contrast that with the idea of rural areas, they're much more defined by a sense of space and self sufficiency, efficiency, right? So you're largely living alone, um, and you form really deep bonds with a small set of people. And over those, over time, those bonds tend to harden and you create rules and mechanisms to protect the integrity of the community, because that's really your only link to the rest of the world. And so that often leads to a rise in kind of protectionism and kind, uh, of collectivism around, uh, this is my community. My community is the only thing I have to cling to. So I'm going to protect this community with whatever I need to do. So now if I think about the rise of the Internet and all of these connected platforms, right, These platforms have been incentivized to literally just connect the world, right? The same way the phone companies and telcos have been trying to, you know, put a phone in every house Right. So you can make any kind of connection that you need to. But now, increasingly, we're encountering people that are different from us. And it's going to be a, uh, big, big challenge for us in the future to think about how do we encounter different people in online spaces? Um, how do we give rise to the idea that people are living a different journey than us, they're coming from a different point of view and a different background, different, um, economic background and cultural background. Um, and we have to understand where they're coming from so that we can understand why, you know, they hold the worldview that they do and really recognize that we're all sharing the same space together. Um, and we have to do the hard work to kind of really align on these difficult issues that we're facing politically, economically, sociologically, you know. And the challenge for digital products, too, is going to be how do you create products that create the right incentive structure such that we can have these collisions in a meaningful way and build much more deeper empathy with each other. Right. And again, going back to the idea of cities, you know, the UN projects that by 2050, about 68% of the world will live in urban areas. Right. Like, mostly growing in Asia and Africa. Right. And so I worry that as we kind of move to urban centers and we kind of start to share the same space together, we're going to build more and more walls between each other because we don't know how to build empathy with each other. Right. If I'm seeing your comment on a Reddit post, um, and I really, really disagree with it, it's very different than when I run into you in a grocery store and we have a disagreement about that same topic. Right. Because I can feel your energy. I can understand where you're coming from. I can see that you've got two kids with you, and you've got different concerns on your mind than I do. Right. And so those are the types of physical cues that we have in the real world that really help build empathy with people, but those are missing in the digital space. And so I'm really interested in the idea of how do we design new digital services and products that really encourage that deeper sense of empathy, um, without that idea of physical presence or all the normal societal cues that we would have in a city. So I think that's the idea behind Designing for Collision. And it's a very, very difficult topic to, uh, solve for, but it's one that I've written, really focused on over the last five years and really, really interested in helping everybody build more meaningful connections.

Speaker A: Thank you, Jim. So in your perspective, what role does deeper empathy play in the design process, especially in an era where digital connections are omnipresent?

Speaker B: So in a typical design process, designers work closely with research insights to really empathize with users and try to design the best products for them. Right. But the problem is, you know, our organizational structures and our business incentives and our metrics tend to focus on a very specific problem set for my user and they often don't see the larger picture. Uh, at Uber, we encountered this a lot where, uh, we dealt with a large amount of these types of collisions where you're literally getting into the backseat of the car with someone you've never met before. M so we did a lot of work to try to make sure that for both drivers and for riders, there's a really clear set of rules and uh, a really robust set of tools to help try to keep everybody safe and respectful. And you know, we still had a lot of, uh, safety incidents on the platform. But the good news is that, uh, these incidents were very, very small amount of these types of collisions, by and large people are having a great experience with Uber across the world, but there's, you know, always the outliers and a very, very small amount of horrible things were happening on the platform like murder and rape and things like that. And so there' work to be done to raise the bar on how we engage with each other, um, in the physical space coming from a digital starting point. Right. And so when I think about the role of designers, um, we have to be deeply, deeply empathetic about our users and really trying to understand where they're coming from and really do the hard work of trying to level set expectations around, um, how we engage with each other and what the rules for engagement are. Right. And that's going to require us to go really deep and ask the hard questions about what we value as a society. And it's probably going to change depending on your location in the world. You know, uh, we're seeing Generation Z, for example, is growing up with the Internet. Uh, they're growing up with smartphones in their houses all the time. And they're one of the most empathetic generations we've ever seen. Right. They understand the plight of underrepresented people, they understand and empathize with each other. We're seeing more and more the rise of multinationalism in terms of like mixed race couples and children. And so there's a deep, deep sense of empathy. But it's coming at the cost of their own mental health. And so we have to understand that empathy for people isn't kind of an add on, that you can just add to your users. There really does come in a trade off and we've got to be very deliberate and clear about what those trade offs are and what we're willing to accept in exchange for this empathy. Because it's not a, uh, it's not an ad, an add on to the value that you're creating for users. There is a real trade off here in terms of people's mental health. So, uh, my ask of designers is to really think about how we engage with insights and what are the types of research that we're going to be conducting, what are the questions that we're asking of our users and how do we design products that really create that sense of community and empathy while also recognizing the impact that empathy and increased mental load is going to have on our users.

Speaker A: Thank you so much, James. So moving on to empathetic AI, how do you define it and what significance does it hold in enhancing human centric design?

Speaker B: Um, I'm, you know, I'll caveat this by saying I'm all in on AI, right. I think it's an incredibly transform, transformative technology and I think it's going to be as fundamental for the world as the shift to mobile. Right. And so when I think about empathetic AI, um, I think it's a way of thinking about AI in a way that's deferential to the human experience and human agency. Right. AI models are trained on billions and billions of parameters and data points and they give the appearance of understanding exactly what's happening in all of that data. But the reality is that they're kind of giving, uh, a, sometimes an incomplete picture of what's happening in the data. Right. If you go to any generative AI tool, for example, right. I'm going to make an image with Dall E3 or I'm going to make an image with Mig Journey or something. And you ask it for something like a football player or cowboy, it will give you a fairly stereotypical review of what it thinks that thing is. Right. Um, because if you think about what an AI is trying to do, it's really just trying to do the most accurate thing possible. And accuracy to an AI model means it's represented the most in the data set and the models are tuned towards that specific result. Right. So if I go and ask stable diffusion for an image of a cowboy, it's going to give me a Picture of a white man with a mustache and a cowboy hat in a, in a desert. Right. Um, and I think that the idea of empathetic AI is really thinking about the edge cases and understanding what representation means to our ideas of empathy and our ideas of a cowboy or football player. And how do we create these deliberate moments of collision such that we can kind of start to change our perception of what's not just the median representation in the data, but what the edge cases also indicate. Right. Um, and so I want to make sure that empathetic AI is a way of not bypassing the nuance and complexity that lies in the data by just providing a simple answer. Right. If you ask an AI to summarize a book, for example, it will give you a couple of paragraphs about what that book is about.

Speaker A: About.

Speaker B: But you're going to miss a lot of the key points, you're going to miss a lot of the nuance, and some of those examples in that book may resonate with you more deeply than others. And you're going to miss that, and you're going to miss that deeper connection with that content because you're effectively designing for the median. Right. Because of the data set. So empathetic AI is an approach to surfacing the median of, uh, the data set while also highlighting the edge cases. This is a lot to glean from the edges of an answer.

Speaker A: Thank you so much, James.

Speaker B: It's capable of and what it's great at and what it's not great at. Right. The space is maturing so, so quickly that we're making leaps and bounds, progress every day, but we're still kind of exploring the edges of what this thing can do. And I think there's not a lot of examples of using it to kind of make things better for people. Right. We're kind of exploring the expansive nature of it, but not really understanding the implications of these things as they're, as they're being developed. I think it's going to be really important to, uh, keep a focus on responsible AI and the open source movement in particular. Um, we have to understand the different complexities of all these AI models and really understand how they work and develop them in such a way that we're able to kind of trace the work and interrogate it openly kind of as an industry. Um, and one of the interesting examples I have is that meta AI where we were looking at the rise of global polarization, um, on our platforms. We found that on Facebook and Instagram, for example, people were curating their own feeds based on, you know, what they're interested in has actually increased the amount of protectionism that we saw, uh, of a particular worldview. Right. I'm able to kind of pick and choose who shows up in my feed. And if somebody posted something inflammatory, for example, something that I disagreed with, we tried an experiment where we tried showing them an opposing point of view, just to get them to consider the alternate point of view. And what we found is that it actually polarized people more. Right. If I'm on my Facebook feed and I'm posting things about a particular political point of view that I have or something, and then right next to that political point of view, uh, we showed somebody with an opposing point of view, uh, it actually made me put up my guard a lot more, and it actually made me react more negatively to that person. And the collision between these two people by just putting this content next to each other just didn't work. It just didn't work. There's still a lot to unpack there and why it didn't work. You know, the existing expectations of somebody coming onto Facebook or Instagram, the specific moment that we showed this opposing point of view, the format of this content, the content itself, et cetera. But if there's a gentler, more human way to understand where someone is coming from and why, I think that's the chance to use empathetic AI to really break down these. These walls between us. One of my favorite examples of getting at this idea of designing for collision is actually an Apple's Fitness plus product. I use it to try to do yoga, and I'm not the best yoga practitioner by any means. Um, but I was dipping my toe into the waters and truly trying to understand how it worked and how to approach it. Um, and all the trainers there are wildly different. Right. They're not typical what you would think of as yoga trainers. Right. If I put yoga. Yoga trainer as a prompt into, you know, uh, a generative AI model, it might give me a very stereotypical view of what a yoga trainer might look like. But Apple's Fitness plus products goes out of their way to actually show you a wide range of yoga trainers and approaches and body shapes and abilities. Um, and it really changed my perception of who yoga is for, uh, what attitudes you need and the actual physical requirements for being able to practice. So that's a very, very small example, but it's one that I'm hoping we can see more of where we start to use AI to kind of not just build these walls, uh, between us, but to really Use them to break down the idea that we're all different from each other and there's nothing to offer each other. Because I don't think that's true. We're going to share an increasingly small space online and it's really important that we design these collisions intentionally and use AI to kind of try to build empathy, um, at the right moment of interaction with the right products, with the right type of content and format, etc.

Speaker A: Thank you, James. So what ethical consideration should be taken into account when designing for empathetic AI systems?

Speaker B: Um, I think it's really, really important that we think about the open source versus closed source debate. You know, it's a pretty, it's a pretty hot topic right now. Um, I think AI architecture is going to be a highly, highly competitive space. And there's a lot of concern in the AI, uh, research community, for example, that closed AI systems, uh, just aren't as transparent with their ethics. Right. Companies are increasingly viewing AI as the magic button to solve all of the problems and to unlock exponential growth for their shareholders. But organizationally it's really important that we absorb all the accountability that comes from deploying these really, really complex systems. Right. With most AI systems it's impossible to backtrack and understand why a system produces specific output. When I was at Meta, um, we had an incident where an AI model was, uh, auto tagging videos and actually tag auto tagged a video of a black man with the tag gorilla. And it was just a horrible, horrible outcome and it was lived in production and so we had to backtrack. But we really were trying to understand why it caused that outcome and we just couldn't do it because the AI is making so many decisions along the way that we just can't pull on that thread, um, enough to understand why I made that decision. You know, the weights and the tuning of these models are getting a lot better, but it's far, far from a deterministic system. So it's really incumbent on the creators of these models and how we architect the stack of our AI tools to really think about how we are building these things and how we build accountability into these, uh, AI systems. And how do we continually invest in responsible AI and improve the bar for what we expect from these AI systems. The other major, major ethical consideration is diversity. Right. Large, large language models are trained on terabytes of data that are largely scraped from the web. But the content of the web has mostly been created by, uh, first world countries. For example, like one of the favorite, my favorite projects that I worked on at Meta AI was a project called no Language Left behind. And it really broke new ground in how we can use relatively low amounts of data to translate the web into smaller languages. Right. Um, this approach really, really bodes well for the data race that people are trying to just gather more and more data to feed these systems, because it's not really about getting all of the Internet into your model. It's really a race to include as many types of people as possible. Right. So with that no Language Left behind project, we took, uh, a small amount of data in a very, very specific language like Tamil, for example, and we were able to develop a model that is capable of translating Tamil into, uh, a rural Vietnamese dialect. You know, and this is an area, these are languages that don't have a ton of data to train these models on. But the model itself was able to kind of make these inferences and it used a lot of reinforcement learning and manual kind of translation. But we were able to develop a system that was scalable and now it's deployed across all of Wikipedia, for example. So I'm really interested in the idea of using not just what's out there, but being intentional about what the goal for these AI systems are and how to build responsibility into these AI systems to make sure that everybody is represented, make sure everybody has access to those right tools, make sure that our data sets. The data that's available to us isn't the only consideration that goes into training these models.

Speaker A: Thank you so much, James. So what are the main challenges in fostering empathy through design in the digital age? And conversely, what are the opportunities does it present?

Speaker B: So I think about, uh, the design of businesses a lot, and the design of businesses today are really incentivized towards the personalization of digital tools. Right, right. YouTube will show you whatever things you're interested in. Right. TikTok has built a juggernaut by inferring your interests by using the smallest behavioral signals. Right. This inherently lets people build their own Internet comprised of everything that they think that they like. Right. Which amplifies the lack of empathy. And tech companies in particular have taken the mantra of, uh, focusing on a user to mean give them whatever they want. Right. And I think the opportunity here for designers in particular is to consider a way of how we make money as companies and organizations by leaning into this shared space of the Internet and to create more societal awareness and global awareness, not just hyper personalized rabbit holes of everything we already think. Right. And so I think about the opportunity for designers in particular and designing New business models. And we have to move to a more collectivist approach to business design and moving from human centered design to more society centric design.

Speaker A: Thank you, Jim. So how do you envision the evolution of empathetic AI in the near future and what impact might it have on the design practices?

Speaker B: I'm really hopeful for the future. I hope that more and more AI practitioners and engineers and researchers incorporate more of the edge cases and the nuance in their training data into the outputs. For example, if I ask for an image of a, ah, cowboy of a generative AI model, right, we might show a white cowboy, but we could also show a disabled black cowboy and we could also show a female cowboy alongside those results. Um, we can still defer to our users to define what it is that they're actually looking for, but at the very least we're introducing the idea that cowboys are much more than the stereotypical image that we have in our head. And product designers in particular need to learn more and get more insights from the edge cases, as they often hold the most interesting insights to design from. One of my favorite examples is a practice called the universal design, where you look at the edge cases and you look at how those human truths actually apply to the rest of the world. My favorite example of this is curb cuts in cities where, um, there was a University of California, Berkeley professor who was in a wheelchair and just couldn't use the sidewalks in California. And what they ended up do, what they ended up doing was being very antagonistic about it and protesting a lot. And there's even rumors that they, they dug up the sidewalks and built their own wheelchair ramps for this professor in protest of the inaccessibility of these public infrastructure. And what it did was it actually unlocked a lot of value for everyone else. Right? It was initially intended for access for wheelchair users, but now bicyclists can use it and people with baby strollers can use it. People with limited mobility can use it. Older people can now use it to get around much easier. And so that's the idea of universal design and thinking holistically about the edge cases. To really design something that's equitable for the rest of the population. Um, we have to design for edges because we're all humans at the end of the day. And you can't just design for the median average in the center of this data set. You've got to really look at the edges and really look at how the things that we can learn from these edge cases can really inform the way that we design these products. And services in a way that increases our empathy and improves access and responsibility for the rest of the m. So it means much more empathy for our users and a less dogmatic view of traditional engagement metrics in product. Right. AI is going to give us the power to understand both explicit and implicit inputs, uh, to craft a m more nuanced view of where someone is and why they're behaving in a certain way so we can really meet them where they are with our products and not just drive them down a particular conversion funnel or engagement funnel. There's real value in relationship building with your users and moving away from a purely transactional relationship with our products.

Speaker A: Thank you so much, James, for sharing all these wonderful insights with us. So could you tell us, like or share with us, how does your day look like?

Speaker B: My day is very much filled with meetings, I have to say. Uh, I do a lot of one on ones. I do a lot of product and design review sessions. I participate in workshops and design critiques. Um, I meet with my designers and my cross functional partners, and I try to structure my days around supporting my scene, seeing as much of the actual work as possible, and making sure that we're working on the right things at any given moment.

Speaker A: So, James, uh, what is a key message or thought that you would like to leave our listeners with regarding the intersection of design, empathy and technology?

Speaker B: I think the main message I have for the audience is to recognize that we're all occupying the same bit of land together. There was a campaign back in the 70s by a guy named Stuart Brand, uh, who petitioned NASA to release, uh, the very first image of the entire planet taken from, you know, the space missions. And what it did was it actually created a really deep sense of awe and wonder and empathy with the entire globe. Right. Seeing that one blue planet floating out there in space really created a shared sense of responsibility and empathy for everything that happens on our planet. Right. We're all on this one blue marvel floating through space, and it really created inspiration and imagination for the entire population at the moment. Right. Um, it actually galvanized the environmental movement to really think about the protection of our planet and the protection of these green spaces that we occupy. So I'd like to leave the designers with the idea that we have a responsibility to society and the people that we serve to really try to break down these walls between each other and really try to understand that we're occupying the same bit of land and the same bit of mental space together. And we have to create stronger shared values as a globe and really try to work towards making lives better for everyone. There's a lot of really, really difficult questions ahead and a lot of misaligned values. But I'm really hopeful that a unique approach to design and AI can really help us build stronger bonds between us.

Speaker A: Thank you, James, for all these wonderful insights. We'll conclude the show by your three favorite book recommendations. Also, people who inspire you the most on the space.

Speaker B: Um, this is a really difficult question, but I've got three pretty different book recommendations that I hope are expansive for, for the audience here. The first one is a book called Exhalation by an author called Ted Chang. It's just a phenomenally creative book that explores the human condition in a way that was completely new to me. It's typically, I guess it would be considered a sci fi book, but it's not a typical sci fi book. It's a collection of short stories that explore our potential futures and a relationship with technology, um, in incredibly different ways and in a way that really expanded my view of humans and machines and our relationships not just with each other, but with our planet and the things that we build. So that's my first recommendation is Exhalation by Ted Chiang. The second recommendation I have is a little more direct in the AI space. And it's a book called the Alignment Problem by Brian Christian. Um, it's probably the best book that dives into all of the things we've been talking about today about the challenges of aligning AI systems with human values. It highlights a lot of the details of the complexity of aligning AI systems with human values, like biases and unintended consequences and how we actually tell machines what we care about. Because what we care about changes depending on who you are, where you are in your life, how you're feeling that day, what type of breakfast you had that morning, the, et cetera. So I really encourage everybody to go read the Alignment Problem because it's, it highlights a lot of the challenges we're going to face as a, uh, as a population. The last recommendation I have for books is a book called the City is Not a Computer by Shannon Mattern. And I've been talking a lot about cities and digital urbanism. And this is kind of a different take on the space. But I think there's a lot of parallels between the idea of a city and the idea of digital empathy with AI. Um, and this book really challenges the idea of kind of a linear, data driven approach to understanding societal dynamics in cities. And it kind of argues against the oversimplification of urban dynamics when lots of people live in the same space and need access to shared resources and knowledge and utilities and societal norms. So a really interesting study on the dynamics of what happens in a city and all the complexities that we need to consider when designing smarter cities. And I think there's a lot of parallels to the digital products and ecosystems that designers are working on tonight. In terms of people that inspired me the most in the space, I had the great fortune of working alongside one of the godfathers of AI at Meta, uh, uh, Yann LeCun. And he's just one of my favorite leaders in AI. He's focused on the intersection of AI research and societal impact and the way that we conduct ourselves as a technology industry. And he's incredibly insightful in everything that he works on and touches, and he's really pointing the way forward for all of the AI, uh, industry. So I really, really was inspired by working alongside him and seeing how he operates. The second person that I really look to as a, as a inspiration in the industry is a woman called Fei Fei Li. She started what's called the Human Centered AI Lab at Stanford and has been working on human centered AI for decades. She's a really strong advocate for considering the societal and ethical considerations of AI and what are the technical research breakthroughs that are going to enable forward progress for our society. You know, AI is influencing the humanities and policy, medicine, science and creativity. And I really feel like Fei Fei Li and her work at the Stanford Lab has really been at the forefront of exploring these intersections with the human centered.

Speaker A: Thank you so much, James, for sharing such, uh, wonderful inspirations with us. I have one last question. Like, this is like a bonus one that I wanted to ask. Uh, considering a conversation. So how do you still keep up learning all the new things as you grow in your land?

Speaker B: I'm a very curious person and I love learning everything about everything. And it's a fault of mine, I have to say, and that I get really distracted at times with all the things that I'm interested in. But I am just voracious about the types of things that I try to consume and the types of viewpoints I try to consider. One of my favorite exercises in design is really going to user interviews and just listening to other people and hearing their experience and what they're struggling with and what they're going through and what they're delighted about, both in my day job and kind of in everyday life, you know. And so I listen to a lot of podcasts. I try to speak to as many people as I can and I try to get as many different types of viewpoints as I can, uh, with my limited mental capacity, I have to say. And again, as I mentioned with Gen Z, it takes a toll on you to try to consider, uh, all the different viewpoints in terms of what everybody else is going through, all the different existential problems that we're dealing with as a society. But that curiosity is deep inside of me and I have to try to do better. And, uh, I always have to try to keep growing myself because that's the only way we move forward as a society. And it's my favorite way of expanding my own horizons and how I think, what I think about and my point of view on the way I think should things should be.

Speaker A: Thank you so much, James, for sharing it and thank you so much for all the wonderful insights that you have shared today. We're looking forward to host you again in our upcoming episode. Thank you so much for your time.

Speaker B: Thank you very much for having me. It's been a pleasure.