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About
Currently serving as Head of Computational Design on AI Platform at Microsoft, John Maeda is a product experience leader across consumer and enterprise domains.
He is the first recipient of White House’s National Design Award for algorithmically generated visualizations informed by data + AI, a LinkedIn Top 10 US Influencer, and author of five books including How to Speak Machine and the tech bestseller Laws of Simplicity.
Recommended Reading
Temple Grandin: The World Needs All Kinds of Minds, Ted Talk.
How To Speak Machine, by John Maeda.
Laws of Simplicity, by John Maeda.
In this episode, John Maeda explains that software products are tools that help us achieve our broader goals – like caring for loved ones and strengthening our relationships – rather than the ultimate objective. So it’s no surprise that John frames artificial intelligence as a power tool that levels up our human potential to create an even better future.
John Maeda, VP of Engineering and the Head of Computational Design and AI Platforms at Microsoft, joined the Product Momentum team to record a live podcast episode on the heels of his conference-opening keynote at ITX’s Product + Design Conference, in late-June.
Humans Are ‘Wired for Creativity’
“I think creativity is the foundation of creating capital,” John says. “That capital is emotional capital or sometimes financial capital. But it is a thing that maybe we humans are wired to do.”
Risk-versed vs. Risk-averse
Creating does not come without risk, however. Because the act of creation is a choice, it requires a competitor’s mindset. Deep down, true competitors don’t play to win; they play to maybe win. Like product managers, designers, and engineers who devote their expertise to create things that do not yet exist, they understand the risks that come with innovation. And they approach their work from a risk-versed mindset — an approach that drives our pursuit of innovation while recognizing the inherent risks.
Within the context of AI, we enjoy a vast ocean of opportunity to tap into, John adds. But to take advantage of AI tools in this way, we need to understand the difference between risk-versed and risk-averse. “To pursue that blue zone of possibility, you need to be risk-versed,” John explains. “AI is understandable; It just takes your attention to go there.”
Understanding AI Requires “The Player’s Mindset’
“Going there” is to embrace the player’s mindset – not the victim’s. While some see AI and grumble, “It’s going to take my job” or “It’s going to be a competitive force against me,” others see the blue ocean of opportunity.
“Anyone who’s afraid of AI is afraid of it because they don’t understand it,” John says. “Positives and negatives are a part of every new technology; we tend to focus on the negatives so much that we forget that everything technological is not always bad. If we are to truly understand [AI], it’s important for us to continue to ask these questions.
Be sure to catch the entire episode with John Maeda to hear him discuss the following topics:
(04:02) Life is lived in 4 quarters: 0 to 25 years, 25 to 50, 50 to 75 years, and 75 to 100. Make the most of the 2nd quarter.
(06:43) I like to pursue things that I don’t know; when you have no reference for how things are done, you’re kind of free to make your own way.
(9:22) What mindset do you choose: will you be a victim of AI? Or invite AI to be your co-pilot?
(10:39) The potential of AI to augment human capabilities: what humans can do by themselves, what AI can do for humans, and the new possibilities that arise when humans leverage AI.
(11:42) To understand and embrace AI, we need to be risk-versed, not risk-averse.
(14:04) How powerful art is! Creativity is the foundation of creating capital – both emotional capital and financial capital.
(17:57) Powerful tools in the hands of the wrong people is a theme of every technology story.
(19:17) Everyone seems to be talking about AI. But why isn’t AI everywhere already?
(24:07) We’re in the Unknown / Unknown quadrant for how to manage AI.
You can also watch our episode with John Maeda on the Product Momentum YouTube channel!
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Paul Gebel [00:00:19] Hello and welcome to Product Momentum, where we hope to entertain, educate, and celebrate the amazing product people who are helping to shape our communities way ahead. My name is Paul Gebel and I’m the Director of Product Innovation at it, along with my co-host Sean Flaherty and our amazing production team and occasional guest host. We record and release a conversation with a product, thought leader, writer, speaker, or maker who has something to share with the community every two weeks.
Sean Flaherty [00:00:43] Paul, man, what a great episode.
Paul Gebel [00:00:45] That was. They say never meet your heroes, but I don’t know. That was a blast.
Sean Flaherty [00:00:49] Shivers up my spine.
Paul Gebel [00:00:50] Absolutely. Yeah. John unpacked a lot of life lessons, business lessons, and technology lessons. What was one that stood out to you is something that people should take away from this other.
Sean Flaherty [00:01:00] There were so many: Risk-versed, like, we have to really pay attention to the risks. The theme, the theme that really stuck with me throughout all of this stuff, from his keynote this morning to the talk today, was about how we should always keep our eye on that all-important ball of our family. Like, take care of your mom. Like, make sure that the relationships in your life are sound. You know, all of the technology is amazing. Like we center a lot of our discussions around it. But the real purpose of it is so that we can have better relationships.
Paul Gebel [00:01:27] Yeah. And there’s there’s kind of, an unhealthy imbalance that comes in when we are only playing to win. Players play to maybe win. Yeah. And that’s a really realistic human aspect of risk versed-ness. And being able to get comfortable with the fact that we’re in this to make the world a better place, to improve the lives of those around us, to remember to call your moms. But that’s why John Maeda wrote the books that he’s written, The Laws of Simplicity, Speaking Machine to take this world of knowledge that is floating around in this amazing brain of his and put it into the hands of folks who can do some good in the world with it, right?
Sean Flaherty [00:02:05] Yeah, absolutely. And it’s exciting to be in front of a live audience. Get to read this right after this talk. A lot of energy in the room.
Paul Gebel [00:02:12] There’s a lot of energy. I hope this comes through. I think if you’re if you’re a designer, a product manager, a human being, you’re going to get something out of it.
Sean Flaherty [00:02:19] You are. Let’s get after it.
Paul Gebel [00:02:20] Let’s get after it.
Paul Gebel [00:02:23] All right. We’re live. Okay. Welcome, everybody. We are just coming off a fantastic, opening talk with remarks by John Maeda. He’s been a powerhouse in the industry. He’s been an inspirational leader for me throughout my career. My introduction of John is going to double as my first question to you. You’re a guy who wrote a book, among other things, of the many things that you’ve been and done, what is the title that you’re most proud of? What’s the thing that you would prefer to be introduced as or remembered by? You spent a lot of time in your talk.
John Maeda [00:02:56] I’m my mother’s cook.
Paul Gebel [00:02:59] I love it, I love that of all the things I think that is, that’s one that I would hang on to too. You jumped on so many ideas in the talk that we’re just coming off of, one of the things, your mother’s short video included that really inspired me was the idea of, what people remember as they’re dying. And letting yourself be happy is not a topic that you would expect to start a product and design conference off with. But I think it’s a good moment of reflection just as we’re getting started in a day of very deep, very technical, very artistic ideas. Why did that make it into your talk? What is it about that that that landed in, and was important to carry on and pass on?
John Maeda [00:03:44] Well. You know, the thing that changed my life was something someone told me in my, 40s. It’s one of my mentors who’s also dead. All my mentors are dead. It’s unfortunate. Really good to remember that, you know.
Sean Flaherty [00:04:01] Yeah.
John Maeda [00:04:02] He said that I had just gotten the job as president, of the university, and they called me up, this mentor of mine, and he said, “Hey, John, you got the job kind of early. You should get there when you’re in your 50s. It’s kind of early.” I said, well, his name was Mitz. He was just a character. He was in his 70s at the time. And they said to me, “You know what, John? Life is lived in four quarters. Four quarters of age, 0 to 25 years. 25 to 50. 50 to 75 years. 75 to 100. And he said, “John, don’t forget that most people don’t make it to the fourth quarter.” So, I was thinking there was four. Then he said there’s only three. So that’s kind of a bummer. And he said., “Don’t forget, you just finished your first quarter. That’s all gone.” So, it’s like seeing four light bulbs you’re given. One went out, poof, the other went out. Poof. And he had two light bulbs left. And he said, “Don’t forget in your third quarter. Your body starts to deteriorate.” And I was like, okay, that’s like a shaky light bulb, the third quarter. So, he said “Make the most of the second quarter.” Now that was the best advice to get. You know, so, I think in your third quarter, like I’m in my third quarter, I think about things like death and what occurs and things like that. So that’s why I like to remind ourselves that some of us are lucky to live long lives, some are less lucky to live short lives. And if you do live life and you think about that is the goal. It makes it makes you more aware. It may make you create a better product, design better, make a better business. That’s where I stand.
Paul Gebel [00:05:50] Amazing.
Sean Flaherty [00:05:51] Happiness is important, right? And I’m very impressed with the dedication that you’ve had for your family. And, where you’re where you’ve gone. When I look at your life because I’ve been following you since the beginning of the internet. Laws of Simplicity was like a earth-shattering book at the time. This is the guy that actually sat down to codify design. Yeah, it was a brilliant, guiding principles for how we’re going to put things together in the world. And, you know, when you, when you build software, you’re building things that don’t exist. Like, everything we do is vaporware, like, until it’s not. But you’ve crafted a life that’s been really interesting and kind of like if you look back at it and say, hey, how did I get here from there? Like, I’m curious what your theme is like. What is the theme that kind of runs through the decisions that you make about where you go?
John Maeda [00:06:43] Oh. Well, it’s actually quite easy, because I come from a – I’m a first generation and go to college person. Is anyone else like that in this room? Oh, yeah. Yeah. So, it’s a really good experience to have. Not saying those who didn’t have experience. You’re bad people, but, it’s very useful because you didn’t know what you could become, which is a terrible handicap. And for some it, it stays as a handicap but for a small few it, it seems to be a blessing, because you, you don’t know what you’re doing and therefore you don’t have, a guide. You know, your grandfather did this and this and this. You know, my grandfather was a carpenter, which is all good. All good, you know? But I didn’t have a guide. And so, after I had, done a few things, I kept losing reference.
You have to realize that when I got to MIT, which was my parent’s dream, for one of us to go to college for me and my siblings, I got there. Well, first off, we didn’t know what the M stood for until it was too late. It was Massachusetts, I was like, well, where is that place? I was like growing up in Seattle. So I was like, whoa, that’s far. And I got to the East Coast, you know, my first, my first week, there’s all these, like, like upper-class people studying for this test. I was like, what is this test? Well, it’s called GREs. And so what is that? I thought we did the S.A.T. already. What’s that one? And then I was learning about something called graduate school. So I called up my parents. I said there’s something called graduate school. And my dad said, you better go to that. But at some point, you have no reference to what you can do and you’re kind of free. And so, I like to, pursue, things that I don’t know. And sometimes I have the luxury of surviving entry into that outer space, and I fail a lot.
You know, people tell me, oh, my gosh, you’ve been so successful. I was like, oh, you’ve never seen how many times I’ve failed. But, I liked it when Mandela, the great Mandela passed away. There were all these quotes, like, in every newspaper. Wow. What a life, you know? And my favorite one was, ‘Don’t judge me by my successes, Judge me by how many times I fell down and pick myself up again.’ Yeah, I love that.
Paul Gebel [00:09:22] That’s a really great segue into the way that you kicked off your talk in the context of a victim versus a player, right? And for those who weren’t able, to join the adventure we just shared in the auditorium a few moments ago, the very, very brief version was that a player is, a it’s a choice. It’s a mindset that you choose to engage in. And the way that you phrased it was that players don’t play to win, they play to maybe win. And that is exactly what you were just jumping into. I think, the, the ideas of AI right now, take a turn into the more technical, out of philosophy mountain, to talk about where we are in, the AI context, the AI business landscape, the AI, engineering, and design landscape. There’s so much that we can be afraid of that we can, contextualize ourselves as victims around. It’s going to take my job. It’s going to be, a competitive force against me, or it’s going to enable us to get into that blue space that you talked about in your talk. Can you can you unpack just for those who are listening for the first time, what were those three sort of concentric squares of the spaces that we can play with AI in, in maybe, a way, to give us a snapshot to jump off of.
John Maeda [00:10:39] Right. What? That’s, that framing is from Professor Brynjolfsson. He was at MIT. Now he’s at Stanford. He’s, like, the real expert on productivity and AI. There are three zones. The first one is the yellow zone. The things that, you, we humans can do in that set of things. There is a set. It’s marked in my diagram as black. The things that AI could do for you instead. And then if you zoom out, there’s a big, bluer ocean that this yellow block is sitting in. Of all the things you can now do because you have AI to tap into. And the reason why I I’m not surprised that most people are afraid of it is because they don’t understand it. And I want to reiterate that, like 99% of computer science people do not understand or have used it in their actual work because they’re too busy pushing regular code, not because it’s bad, it’s because they’re just busy.
And so anyone who’s afraid of it is afraid of AI because they don’t understand it. That’s why in. The space of when I was in the security industry, and especially with supply chain during the pandemic, one of the supply chain experts talked about how you have to be risk versed, not risk averse. So to go after that blue zone of possibility. You need to be, risk versed. And the way to be risk versed is you understand? That’s why we went through in the talk kind of briefly, AI is understandable. It just takes your attention to go there. That’s why I wrote How to Speak Machine. To lay the foundations. To enable people to understand what I now understand much better. Because if I didn’t write that book, I don’t think I could, blah blah blah like this.
Sean Flaherty [00:12:34] I’m going to tie a couple of these themes together, thoughts floating around my mind here. So we play to play, players play to play. But really, the human condition, what makes us happy is to create. And I loved how you answered my question about the theme of your life. So when I asked it, I said, you know, when we sign up to build software, we’re building vaporware. We’re creating something that doesn’t exist yet. And your answer was really kind of profound. Like, we have this potential and it’s a choice. It’s a choice. We have this potential and we can create whatever we want to the future. It’s our job to think of it that way so we can step into it. And I think AI is, it’s been, at least for me, it’s been a power tool. You mentioned a couple of ways in which you used it. Even this morning, writing your blog post, like, has the potential to help you create an even better future and to create a more profound next thing. Yeah, because we can. It gets rid of some of the cognitive load so we can actually do more with our creative energy. That’s what I see.
John Maeda [00:13:38] No, thank you for that framing. Actually I’ve been. I mean, try to understand this thing of what you’re saying. We love to create. And I was like, oh, yeah. So like, we love to create. Is that true or not? Some people can create. Some people prefer to boss others around.
Sean Flaherty [00:13:59] You mentioned bosses a lot today. Yeah. There’s a theme there as well.
John Maeda [00:14:04] You know if you’re not independent you always have a boss. Right. And even if you’re a CEO you have a board. So I say it not in a pejorative way, I love bosses, I love good bosses. But, the idea of creating is, you know, we think that artists love to create, designers love to create. Programmers love to create. You know, I mean, I’m sure I understand this phrase because, you know, one thing I love, when I used to advocate for the arts, when I was running the RISD, I was able to kind of think about, you know, what that is and what that means. And, one thing I used to say in that era was how how powerful art is. And anyone who is a parent knows this is when your kid just you can’t stand them, right? Sometimes. I mean, of course we love them and all, but some like.
Sean Flaherty [00:14:57] Oh, Paul’s dad’s over there.
John Maeda [00:14:58] Oh, sorry. Oh, different for you, of course, sir. But, it’s like, you realize that when they make a picture for you at school and they give it to you, it’s like the best money ever. It’s like, you know, it’s just Dad I’m sure you have a few of those like dad. Oh okay. You’re okay kid. Somehow they made art. And they’re giving (of) art, change the relationship. So I think creativity is, is the foundation of creating capital. That capital is emotional capital or sometimes financial capital. But it is a thing that maybe we humans are wired to do if you are not the boss, because you have to create value unless.
Sean Flaherty [00:15:51] You’re a good boss.
John Maeda [00:15:52] Of course. I love good bosses.
Paul Gebel [00:15:54] Yeah, yeah, you did have at least two admonitions that I picked up on one being from your Professor Weizenbaum about powerful tools in the hands of wrong people. Which I’d be curious for your thoughts is how this relates. And the second was, why isn’t AI everywhere already? There’s a bit of a paradox where everyone’s talking about it. We’re talking about it right now, and yet nobody’s actually figured out what it means to use it. Where are these productivity gains? Where is the speed? Why isn’t the roadmap moving left and everyone is expecting it to happen? Kind of. There’s a state of anticipation right now. And yet it’s an already but not yet situation. So, I’m curious, you know, the those two ideas of powerful tools in the hands of, I’ll say, wrong people. You can correct me – bad bosses – and the idea of why isn’t it everywhere, even though it already seems to be everywhere? These two ideas seem to be warnings of sorts, and I’m wondering if you can help us unpack that just a little bit more.
John Maeda [00:16:55] What is my thing about bosses? You’re right. Now something has over time. I’ve just met so many people with bosses that I think I never thought of as a construct. I think when I was a, MIT professor, you’re like a Jedi. So you’re, like, super powerful. I think after I left that, I became aware that, I don’t have a Kevlar vest anymore. So, I’m just a regular person, and regular people have bosses, and it’s good. You know, I like the phrase you don’t choose a job, you choose a boss. One of my favorites, favorite ones. What was your question?
Paul Gebel [00:17:33] There were two ideas that you shared that that are resonating with me, that seem like they should mean something, that I want to try to give folks a way to apply the ideas of powerful tools in the hands of the wrong people or bad bosses. Yeah, or the idea that AI seems to be everywhere, and yet we’re not necessarily – or maybe it’s limited to the business world, but these two ideas seem to be something we can unpack.
John Maeda [00:17:57] You said about bosses. That’s why I treat the bosses well. Powerful tools in the hands of the wrong people.
Paul Gebel [00:18:03] Yeah.
John Maeda [00:18:04] In general is a theme of every technology story.
Paul Gebel [00:18:08] Yeah.
John Maeda [00:18:09] If you’ve seen Oppenheimer, you know the story. The story is if you create something extremely powerful, it’s really amazing. But then now when it’s available, who gets to have it? And I think some people forget the, there’s this famous prize called the Nobel Peace Prize that many of the younger generation probably don’t know that Alfred Nobel invented dynamite. And dynamite was when the cause of the most deaths in any war. But also was good because it saved miners lives for not having to, crawl into rocks and sort of use their hands and picks, so positives. And negatives and so every technology, that’s what the science, technology society, field exists. It’s very important to ask these questions, as always, positives and negatives. We tend to focus on the negatives so much that we forget that everything technological is good. It’s actually not always bad.
Who likes to, drive to somewhere to see their parents? Well, some of you don’t like your parents, but you know what I mean. It’s pretty useful to have that car technology, with us. Your second question was about AI. So, why haven’t people? Why is this AI not so common? It’s because it’s still scarce. It is actually the best variants of this. It’s like the vaccine, I guess. I know some people have the vaccine, some people don’t. Vaccines- touchy topic, I forgot. It is, it is something that is scarce. It’s like platinum, still. So if you don’t know what it is or haven’t, you’ve only touched a version of it. That’s probably copper, not the platinum version. Because it’s still very scarce. And that scarcity is beginning to diminish. And so that’s when you’ll see more impact of it in everyday life.
Sean Flaherty [00:20:05] Yeah. You said something in the talk about how AI has this because we’re gullible. And Daniel Kahneman proved this whole, you know, relationship between negative and positive. Like, we’ve we’re wired for that negativity, right? And the gullibility of humans. You talked about specifically. The quote was around, short exposures from the stuff can induce delusional thinking and like, that’s the bad tool. Yeah.
John Maeda [00:20:33] Why are we gullible? Why did economists say we’re gullible? You remember?
Sean Flaherty [00:20:36] It’s miswiring in the brain. We have a fast brain and a slow brain. That’s the fast brain is working. We make there’s these cognitive disconnects because we’re the brain’s trying for efficiency, and it makes mistakes. That’s the word gullible. It’s going too fast.
John Maeda [00:20:50] Well, I mean, you know, in the world of, large language models, slow thinking and fast thinking is used as well. When it’s hallucinating, it’s because it’s doing fast thinking. You give it no context, the best way. And you’re already seeing it. And some of the, technology you’re using with ChatGPT, etc. is, it’s called thinking out loud. What happens is, if you before the LLM produces an output, if you get to the LLM, think out the steps before you give you the answer. And it just thinks out loud. Now, given the answer like a human or like an intern, it’s able to produce the next token better. Not because it’s sentient. It’s because, the way these systems work is that, they take a stream of text. And if you start with a very little text and try to predict the next token, we do all get it wrong. Like if the phrase were like, I’m John. I like, I don’t know, you’re going to guess. Ice cream, puppies, wood or whatever. But if I gave you a longer sentence. I really like the forest. I’m John. I like wood or green or whatever. So the more context you give a, predictor, it can predict the next token better. So when you think out loud, you’re producing a stream of text of thinking out loud. Now solve the problem. The next prediction will be more correct. So this is like system two, deep thinking versus system one. No thinking.
Sean Flaherty [00:22:34] Interesting.
Paul Gebel [00:22:35] We have a couple questions from the audience. I want to make sure we get in here since we have just a few moments left. This one so fast. The first going back to the very beginning. Someone in the audience wanted to know what is your favorite meal to cook for your mother?
John Maeda [00:22:49] She’s so picky. And, you know, your tastebuds change at that age. Anyone who’s been a caregiver raise your hand. You know that their taste buds change. Like. Well, I thought you like this. No, it tastes terrible. I said, oh, no, I got to get a different kind of shopping now. She liked mushrooms. Now she doesn’t like it. So I can’t tell you, I don’t know. That’s stressful for me every day.
Paul Gebel [00:23:12] Okay, fair. We’ll back off that one. I have one more question on my own, and then I’m going to close with another, audience question. Your allusion, I think two three body problem about hydrating and desiccating. I don’t know if that was intentional or not. About the engineer, the creator, the designer, using this tool. You mentioned it yourself in the blog post that you wrote in 30 seconds, and you’re able to put something out in your own voice, and it’s in the world now elsewhere. And there is a there is a feeling now that we can create so much. There’s a saturation, but users can only consume, you know, what the bandwidth can endure. So is there a decision that we need to force into our workflows that triggers a “this is fine for AI, but humans are the limiting factor.” And how we can be more contextually aware of the audience for whom we’re creating, if that makes sense.
John Maeda [00:24:07] Yeah. I mean, I just I mean, I think what’s so exciting is that we really are in the unknown, unknown quadrant for how to manage this. Like, I love. I love high school students who are trying to figure this out where I don’t mean anything against teachers. The teachers are so busy right now. Doing their regular stuff. The teachers are too busy to cope with this new technology in their classrooms. So, I have a lot of empathy for them, it is a quantum leap. Suddenly you don’t just have a calculator that can do math faster. You have a calculator that can do every possible homework faster. What do you do when a teacher clearly doesn’t understand that this is the now? This isn’t the future. It’s occurred. Yeah. And then it gets worse in college because the professors are the same way. Like, at least 99% are going to be way behind.
And so, the students are smart because they’re afraid. Will I be able to get a meaningful job if I’m slowed down in school through that 12 plus six, four years, will I be relevant. So, I guess I kind of feel like we need to be aware that if we are in an advanced part of our careers, we need to actually facilitate, running at speed and enabling other parts, other sectors to catch up much quicker because that divide is going to be increasingly felt. And people can argue that’s bad or that’s wrong or that’s whatever. But this occurred when electricity came on the scenes. I heard a story once about how there was once, the greatest country on earth, and happened to be named Great Britain. It was the 1800s. You asked the one country that could produce the things, manufacture the things that fast, or ship it anywhere in the world, any size. It was Great Britain. It was because its factories were all powered by this amazing technology called steam power. And it was the most amazing technology ever. And then in the late 1800s, this like startup technology called electricity sort of appeared. And what are the steam powered people say? Never going to take off. And the United States didn’t have the same kind of factory infrastructure, on steam. So, we invest in electricity. And that achieved outsized gains. Interesting. So, it’s a question of, do we want to choose to be disrupted or not? Is it a techno-centric view of the world? I think it’s more of an economic advantage view of the world that it’s good to consider as a player with a conscience mind you.
Sean Flaherty [00:26:59] One more question from the audience.
Paul Gebel [00:27:00] We have one last, and I’m going to paraphrase it slightly. The way that they worded it was, what’s the most important thing you’d like us to learn today? Since I’m sure there are too many to list, I’ll ask an alternate version. What’s the thing that you hope to inspire us with as we leave the room for the rest of the day?
John Maeda [00:27:17] Oh, I didn’t come to inspire anyone. Okay. Okay. No, I’m just randomly here in Rochester. I thought it was, and I. What is his name? Ralph. Ralph? The CEO? I mean. I came to see Ralph clearly. I mean, I didn’t know Ralph and I had dinner with Ralph, and I was moved. It’s this guy, Greg. Ralph and Greg. I mean, Ralph and Greg. They’re like, they’re like Oreos or something. I don’t know, but, they’re really good together. And I kind of felt like I loved seeing friends, longtime friends that choose to stay friends and support each other. So, I think, you know, I hope in life you’re lucky to have a friend like that. I think that’s important. Some people get to have it, some people don’t. Be nice if we all have that. Yeah, I have some of that. And I want more of that. Yeah.
Sean Flaherty [00:28:19] And take care of your mom. Take care of your mom.
John Maeda [00:28:21] Mom part: you know, I know it’s finite. This will end. Yeah. And when it ends, I’ll be sad. Kind of happy, but kind of sad. More sad. Living it.
Sean Flaherty [00:28:32] Well, John, it’s, been a pleasure. Thank you for joining.
John Maeda [00:28:36] Likewise, thanks for the conversation.
Sean Flaherty [00:28:38] And, one last quick question. Yeah. What are you reading? What inspires you these days?
John Maeda [00:28:42] Reading? Well, I had the most inspiring conversation with, this person over here, the designer over here, I read, we did a lot together. Right? We read online. Temple Grandin. We talked about empathy, cattle slaughter, all kind of stuff. Right. That was a good book to read. I was reading her book from her brain. It’s a good book.
Sean Flaherty [00:29:03] Outstanding. Thank you. John.
Paul Gebel [00:29:05] Thanks for joining us today. Thanks very much for listening in. Okay. Enjoy the rest of the day.
Paul Gebel [00:29:09] Okay. Well, that’s it for today. In line with our goals of transparency and listening. We really want to hear from you. Sean and I are committed to reading every piece of feedback that we get. So please leave a comment or a rating wherever you’re listening to this podcast. Not only does it help us continue to improve, but it also helps the show climb up the rankings so that we can help other listeners move, touch, and inspire the world just like you’re doing. Thanks, everyone. We’ll see you next episode.