Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas - 224 | Edward Tufte on Data, Design, and Truth

Episode Date: January 23, 2023

So you have some information — how are you going to share it with and present it to the rest of the world? There has been a long history of organizing and displaying information without putting too much thought into it, but Edward Tufte has done an enormous amount to change that. Beginning with The Visual Display of Quantitative Information, and continuing to his new book Seeing With Fresh Eyes: Meaning, Space, Data, Truth, Tufte's works have shaped how we think about charts, graphs, and other forms of presenting data. We talk about information, design, and how thinking about data reflects how we think about the world. Support Mindscape on Patreon. Edward Tufte received his Ph.D. in political science from Yale University. He has been a professor of public affairs at Princeton and of political science, statistics, and computer science at Yale, where he is currently emeritus professor. He is the founder and owner of Graphics Press, and his books have sold nearly 2 million copies worldwide. He is an active artist and sculptor, as well as a touring lecturer. Web site Yale web page Amazon.com author page Wikipedia Twitter

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Formulation unique to Shell compared to minimum detergent gasoline with continuous use of Shell v. Power Nitroplus and gasoline direct injection engines. Actual effects and benefits may vary. See Shell.us slash more dash protection for more information. Hello, everyone. Welcome to the Mindscape Podcast. I'm your host, Sean Carroll. The world we live in today, I don't think anyone can argue, is suffused with numbers, with data, with information. Data and information come at us from all directions, right? Whether we're reading a newspaper or magazine, looking at something online, watching TV, scientific papers. And the thing about numbers and data is that they have this aura of objectivity, right? Like there's a number. You can't argue with it. It's giving you. It's giving you. It's you some information. It could be false, but as long as the information is reliable, it's telling you something objective about the world. But the reality is that the way that we present that information visually, whether it's in literal series of numbers or a chart or a graph or whatever,

matters. It affects how we process the information, what seems important to us, what is it that we notice, what is it that we care about. So sometimes you want to do your best. I hope that usually you want to do your best at conveying information clearly and vividly and concisely, sometimes maybe you want to fib a little bit, right, and hide the parts of the information that you're not that proud of. But one way or the other, it matters how it is presented. So the art and science of presenting information is very important in the modern world. And today's guest is The Guy.

When it comes to the display of quantitative information, Edward Tufti is the author of the classic book, namely the visual display of quantitative information. They're really pioneering texts that help people understand the importance of graphs and charts and how they are presented in the way to do it well. And since then, he has continued to try to educate as many people as possible

about thinking clearly and presenting those thoughts clearly in a visual form. He has a new book out called Seeing with Fresh Ones, meaning, space, data, and truth. And once again, it's an exploration not just of how to present information, but the meaningfulness of that information. One of the big things that Edward pushes is that the origins of quantitative information as a way of talking about things, you can trace back to, let's say, Galileo, for example. And it's not just a new way of presenting information, but a new way of thinking, a new way of arguing for a conclusion.

based on evidence rather than just words giving you an argument, a shift from rationalism to empiricism, if you like. And in the new book, we talks a lot about truth. There's a lot of physics diagrams in there, as well as a lot of works of art, which give you a different kind of truth. So it's a real pleasure to talk to someone who is truly a major transformative figure in their field and just listen to the wisdom that he has to offer.

So let's go. Welcome to the Mindscape Podcast. Welcome. Good. I do want to start with the sort of obvious caveat slash apology, which is that you're the world's expert in data visualization and we're doing an audio-only podcast. So I do understand that it would be even nicer if you could point to things, but we'll have people check out your books and so forth.

You have a new book out. Why don't we give you that chance to mention that? Okay. It's volume five in this series that started in 1983 with the visual display of quantitative information. And this is the fifth book. The title is quite immodest. Seeing with fresh eyes, meaning space, data, truth. And I can't think of a grander title, but I kind of set it as a goal as I was writing.

I had to talk about all this stuff with the title, and that's exactly what it's about. Yeah. It's redesigning everything. Sentences, paragraphs, Feynman diagrams, everything, sculpture, and that requires the scene with fresh eyes. I opened the book with a little, bit of free verse, which kind of describes it and also describes me. If it's all right,

please, we'd love it. This is a free verse. It's called the thinking eye to see the ordinary so intensely that the ordinary becomes extraordinary, becoming so focused, so specific about something, that it becomes something other than what it ordinarily is. Always. on, thinking eyes see intensely, actively, skeptically, scanned globally, focused locally, see at varying scales of space and time, approximating ways through multiplicity, detecting how things happen, move, act, interact, seeing with fresh eyes, vacation eyes. I love that. I love the vacation eyes. We have a lot, you know, the first five days, at a place. It just seems so

like a wonderful fresh eyes. Seeing with fresh eyes, vacation eyes, unhindered by self-confirming words, models, expectations. Not seeing something different is not seeing anything

at all. Grace Hopper saying, the most dangerous phrase in the language is, we've always done it this way. Staying in optical, experiences, forgetting the name of what one sees. This is a very important idea about seeing with your eyes, not seeing with words. Once you have the words, it's impossible to see around them. It's very important in sculpture, for example. If you walk out and see a big thing and people

say, oh, it looks like Stonehenge, or it looks like this, or it looks like it was somebody bought it for a million euros in Zurich the last week at an auction. You can't see it any other way. And so that's the seeing has got to be free of words because the words will dominate what you see. So staying in optical experience, forgetting the name of what one sees, laughing, playful eyes, shut up and look. If you see something, say nothing. De-familiarize, decontextualize, re-contextualize, reform. remodel. Thinking eyes are of this world, empirical, specific, practical, self-aware, asking, disbelieving, challenging, making the familiar, unfamiliar. How do U.I. They really know that? There's a little stack list in the middle. How do, in a sentence, then, vertical, U.I. They really know that.

How could you, I, they possibly ever know that? That is, how could you design a research? Could you even design a piece of research that would enable you to own it? Thinking eyes reason intensely about what they see. Reason about verbs, clinks, mechanisms, connections, dynamics. Reason about what things do, not what things are named. Reason across multiple time horizon. Now, then, forever. Name, rename, remodel. Thinking eyes, compare, model, choose, doubt, decide, compare again.

Thinking eyes act. Make something of seeing and reasoning. Discover, produce, construct, write a report, make an artwork, teach a class, have an insight, understand, explain, show, get on with it, To produce, construct, model, remodel, to act is essential. It is a difference between spectator and player, between consumer and producer, between art chat versus artwork, anecdote versus evidence, process versus outcome, retrospective versus prospective versus prospective, presentations pitching versus demonstrations comparing. Craig Venter saying, Good ideas are a dime a dozen for a smart person.

What distinguishes good from great is how an idea is executed, how it becomes reality. Thinking ideas, thinking eyes, identify, know, celebrate, excellence, forever, universal knowledge, gathering consequences, staying and playing in place, beyond memories and precision. Seeing, learning, doing, doubting are the meaning of intelligent life. I like that. I feel like I should applaud a little bit for the performance. Thank you. But, you know, I'll say that I love the word truth appearing in your subtitle, because that's

what hit me over and over again, sort of reading through all your books over the decades and thinking about what you're doing. There's the sort of down-to-earth operational side of making a beautiful chart. And then there's the much more profound question of discovering truth, presenting it, and conveying it. And that's really the motivating factor, yeah? It's what it's all about. It's in any good report or presentation, it's about the content and the credibility. It's not about whether you should do a certain motif or use a certain method. It's about the content. It's about the content and the truth of it, the credibility. And that's what's going on in information exchange. And this kind of stuff about the coding for visualization and all that. I regard that as plumbing.

Because it's plumbing, basically. And the reason we're having the reading that that research report or that we're having this meeting is to reason about content and assess the credibility of the material. That's the fundamental thing it's all about. And all the kinds of things I did early on, there was this concern with getting it right, getting it true. But it's really as I've become more general and applying to more and more things, truth comes right along with it.

And, you know, the plumbing may differ, but it's content, and then are they saying something true? I have a long chapter on medical research in the new book, and it's widely agreed by editors of the New England Journal of Medicine, by editors of the Lancet, and by the famous skeptic, John Ionidis at Stanford. that most published medical research findings are false. And the debate isn't over whether that statement is true or false. The debate over is the debate is over the word most. And so in a field, it appears to be at least 50% in published medical research. And this is by people who have been editors of journals. Yeah.

And it varies by fields. In some fields, I did the Ignoble Prize Awards this year. Love those, yeah. Yeah, and I did 24 jargon words about cognitively psychology. And then you have seven short words at the end. So I went through the jargon about parameters and blah, blah, blah, and so on. And then the punchline, the punchline. is that the first day in the class in cognitive psychology,

the professor says, half of the findings in our textbook are false. We just don't know which half. And so it's part of the failure to replicate, the replication process thing. Science has it easy. Brocket science compared to social science or even medical sciences is easy because you've got a guarantee of the truth. There is truth in the norms of nature. And that makes it easy.

You know there is truth. You don't even know other truth exists for the, you know, about a lot of personal people, people things or medical, medical things. And so Brockett science is easy. I say it all the time. I tell people that physics is the easiest science. That's why it's so intimidating because it's so easy we've learned so much about the physical world. Hey, everyone. It's Cal Penn. I'm the host of Earsay, the Audible and I Heart audiobook Club. This week on the podcast, I am sitting down with Ray Porter, the narrator of Andy Weir's audiobook Project Hail Mary, massive sci-fi adventure about survival and science.

and what happens when you wake up alone very far from Earth? I really had to make a decision because I caught myself getting that frog in my throat and starting to get teary as I'm narrating some of these sections. And it's like, okay, yo, yeah, yo, is this indulgent? And I really thought about it. I was like, no, at this point it would kind of be betraying the trust the author and the listener have in telling this story if I don't go through it. But there's places in this book that deeply emotionally affected me. and I left it on the mic. That's great.

Because it served the story. People will say like, oh my God, I cried at the end. It's like, yeah, dude, me too. Listen to EIRSA, the Audible and IHeart Audio Book Club. On the IHeart Radio app or wherever you get your podcasts. When people turn to telehealth or weight loss, they're looking for real support. That's why more people are choosing orderly meds.com. Orderly meds connects you with real doctors and access to proven GLP1 medications like semaglutide and terseptitide.

No guessing, just a more supportive experience. experience and all ship directly to your door in discrete packaging. Do your research, ask questions, then visit orderlymeds.com slash podcast for an exclusive offer. That's orderlymeds.com slash podcast. Individual results may vary on medical advice, eligibility required, C-Sight for details. It's extraordinary, and also the only thing that's universal. It's everywhere. That's, I mean, just out of this world. So let me give, let's make sure that the people, the, you know, the tiny percentage of listeners who aren't already familiar with your work, sort of get the thrust of it right from the start. I mean, you work at the intersection of data and design, and design is a tricky

thing. Do you have any training in design, or is this something that you just built up along the way? Or do you stumble into it, or was that a goal all along in your career? Like Paris, my mother was a professor of English, and did a scholarly work on the 17th century. But she also wrote a book, which I then published, I myself published, I published my mother's book, called Syntax's Style. It's called Artful Sentences, Syntax's Style. And so that was kind of the word part in my home. My father was a civil engineer, which is a very applied science. There you go.

Outdoors. And that helped me a lot of my sculpture, of course. And they both could really see well. I don't know where that came from, but they could really notice things and see well. And I was taught to see well, both in. reading things and reading poetry and looking at pictures and talking to my mother, but also being outdoors with my father. And so we'd take a vacation. We drive toward Hoover Dam in the middle of the Colorado River and study the dam because my father was a civil engineer. Or every time it

rained, we would go out driving to see the stormbrangis, fouleding up the wrong way. So it was Intense scene was just part of it. Interesting. And I married a famous graphic designer, Inga Druckery, who was Professor Yale and RISD, and the University of Arts in Philadelphia. And I learned a lot from her, and I found design very easy. And within, as soon as I did my book on visual display, I was teaching in the Yale Graduate School in design. Okay. So it was good enough.

Didn't need to have a degree. Because I had done the design for the books by working with a book designer. And the rest of the books I've designed entirely myself. And frankly, I found design very easy. I think it was because of my verbal skills. I think many designers are like violinists or there's a kind of innate quality of seeing and working with your hands and making things.

And it's not so much, it's kind of almost a physical performance, not so much an intellectual performance. there's a real difference there. It's a seeing performance, not a word performance. That's a better way to put it. And I'm not, I'm a B plus in a lot of different fields. I'm an A plus in visualization, but a lot of the subfields, like writing, design, statistical work, all this.

I could probably teach an introductory course, you know, at school. And I can use, but I have these tools where I can use, you know, all the time, that I can do everything myself within myself. Yeah. So the books I design myself, I publish them myself. I love the craft and the former craft of Doid books. Yeah. With the computer screen, it's not like that anymore.

And so it just somehow came in this odd package of genetics and school and never specializing. That's actually that was the key thing. I got a bachelor's and master's degree of statistics from Stanford, PhD in political science at Yale. I was a good political scientist. I was a full professor by age 31 at Princeton in political science, but it was quantitative. I was thinking over to graphics, you know, more and more upset in the politics department, you know, while I'm supposed to be doing this and what's the book with graphics stuff.

And I think I always mourned to be a professor, you know, from about age 12 on, but I have yet to discover a professor of what. Right. I taught in the Yale Law School. I taught in design. I had tenure in public affairs at Princeton. I had appointments and statistics. And maybe it's because I have a short attention span.

But I love going into a discipline and looting it, not getting a, you know, a degree. in it, but rather looting what was useful for me. And I get in a completely different posture when I talk to people on other fields who were, and I've always been attracted by excellence. I hang around excellent professors when I was a student, regardless of what they were excellent at, and seeing how they think and just being with them most happy. and it's the only time I really shot up

is when, you know, in this environment where there's all this stuff to be learned. And I just say, interesting. And oh, that's interesting. And maybe say, you know, guide them slightly ever, maybe say, why is that once or twice every few minutes? But I just love that kind of discussion where I have no responsibility except to listen.

and guide it just enough to do it. And it's, I think, when I'm happiest. I'm a stranger in all these contacts, but I'm so taken by it. And because I did the data stuff, I could play in just about everybody's backyard. So let me, if it's okay, get down to some nitty-gritty,

because I do want to make sure that every listener to the podcast comes away making slightly better charts than they did coming in. I mean, we live in a world where there's graphics and data visualization all over the place. This is probably an unfair question, but what do you think is the biggest flaw or the most common mistake in how people make charts and present their data these days? Multiplicity. Okay. They try five times, five different.

graphics, or maybe 10, they have a programmer that does us something special, and they cherry pick the results. And my first piece of advice to any researcher is use utterly conventional graphics that are in the very best graphics in your field. And you specify those graphics in advance. You can't search through, you can't cherry pick. Things are so bad that in medical research, in clinical trials, RCTs, randomized trials, they have to specify their graphics before they see the data.

Wow. Because everybody was cheating. Jerry picking. Because most everybody is doctor confirmation bias. Sure. All researchers have a little bit of confirmation bias in them. Of course they do. The real giveaway is that a study is cheated is that they'll have an unusual custom graphic.

Hmm, interesting. Not a conventional graphic. And they're so proud of it that the title of work paper is ending metastasizing in cancer by the use of artificial deep intelligence 6.C.2. So they're pitching their finding and their contribution that they've also made to graphical things. That is the sign of a fraud and somebody who's cheating. If they have any kind of decent substance finding, it doesn't matter the plumbing. They're trying to say, well, I brought this thing into the field.

I used to referee all kinds of papers. People would say graphics for sociologists, graphics for psychology, you know, and they would, you know, think, what bullshit? You know, it's, it's, it's, the principles of graphics are the, are in, are, are, don't come from the feel. They come from the problem, the data problem to be done. Right. And so you do whatever it takes in any field. You know, what graphics did you use in psychology? Whatever it takes is the answer.

No, not that we have some kind of special things. So the giveaway is an unusual charting method, often custom. So are you thinking about something like, you know, pie charts versus histograms versus line charts? Is that the difference of choices that we're thinking of here? No, we're thinking of scientists, more scientific, serious things. Okay, but what are the kinds of choices that you're saying people make to sort of cheat a little bit? Oh, they take, they put things on, they put a Y on a logarithmic scale. Ah, okay, yeah.

That's the, and they're good reasons usually for it, but not always. if there's a doubt, they should show both. That's how you get around it. Your findings survive both transformations. The conventionality is also good because the person has come there to learn about that the cancer metastasizing can be stopped. They haven't come to learn about your graphic. Right.

and you want to minimize, you want them to, to your readers to see the data instantly, not decode a graphic, not have little color codes like R does endlessly. Python is better on that. And so use conventional things. Just as you use, there's all kinds of conventions about the language that you use in published papers. They're conventional things. Get all that out of the way. And that now allows cross-researched comparisons.

And people who are shopping around for something new are thinking they're making a contribution. Look, Don Canoves did it 25 years ago, okay? That's true of everything, by the way. Yeah. He did my spark lines, which I was so proud of. He did something called Skyline, Skylines, like little things post for, you know, silhouette skylines,

in an inline graphic. And it really was 25 years before my sparkline. But it's true everybody, once they hear that, they'll say, yeah, that's right. I mean, maybe tell people what a sparkline is, for those who haven't heard of it. It's an inline graphic, so it's like a word in line, and it has a resolution of typography, which is an intense resolution of letters. So it's very high data and it's embedded in the text itself and shows lots of it. And it's perfectly readable.

And it's the highest, if you can operate at a graphic at the resolution of typography, you're in the big leaks. And so that's the metaphor. Instead of a word, it's a graphic. It's words like sized. It's built right in. and you have a bunch of these, and now you have what's called a table of lines like that, with consisting of words and numbers, and also maybe little tiny images. I first got the idea from Galileo, a lot of ideas,

where when he discovered the rings of Saturn. And he says Saturn looks like this, and there's this little charming picture, little drawing, line drawing, that the printer has. had to pack through out of the lead, make a special Saturn letter there. And you can see how it was kind of done roughly. And it says Galway. So Saturn looks like this. And two lines later, he says on a cloudy night, it looks like that. So comparison of a clear and a cloudy. And you could, you know, there was a difference. And it's right there in front of you. And it's perfect. You don't need it. He gets working at, you know, he can barely see him himself.

And I'd, that's showing up and kind of seek quietly. I think all five of my books. I have Galileo Satchel. Yeah. Because it is so wonderful. He is such a visual person and just seeing. And he is the person who saw more than seeing. He said, we now have the evidence of the eye, not the evidence.

of the church sitting around in armchairs, parsing Aristotle and parsing the Bible about astronomy. And Galileo knows exactly what's happening. He says, we now have the evidence of the eye. We have visible certainty. And ding, ding, all about truth. And empiricism, right? I mean, I noticed that connection also. Yes, it's seen, the evidence of the eye, not the evidence of words and of church. and all the rest. And he's very blunt about it. I've almost quoted

that what he said. And that's been the spirit of since book two, Galileo showed up in the second book. And Galileo's side term gets in every book. It's about the, it's about empirical evidence of

his eyes. And he is just a piece of, he's just beyond everybody. He's a a mutation with mutation is so incredible. He was pretty good. I do admit that. And I mean, there's a flip side, right?

I mean, there are graphic choices that, as you alluded to, kind of make things worse, kind of hide what you care about. And one of the other things, again, going back to the truth issue that I noticed in reading the books is this idea that good graphic design just flows naturally from clear things. about what are the causal relationships, what are the variables that matter? Like if you really think super duper clearly, maybe your graphics will pop out the right way. Is that an exaggeration or do you think that's more or less right? This is from the Green Book with a dog on the cover.

Beautiful evidence. And I wrote exactly about that. The purpose of an evidence presentation is to assist thinking. That's the key thing. Thus, presentations should be constructed to assist with the fundamental intellectual tasks of reasoning about evidence, describing the data, making multivariate comparisons, understanding causality, integrating a diversity of evidence, and documenting the analysis. Those are the principles of seeing evidence, but they are also, right now just turned into principles of analytical design.

The point of a display is to assist the viewers that reasoning about it. I can tell you what reasoning about data is. I turn them into design principles. So your design principles are, you know, show the data, show multivariateness, show mechanism causality, show an integration of different kinds of evidence, and provide documentation. This is a very powerful idea. that people don't think about, don't realize.

They talk about, you know, why we should use this method, whether we should use bullets, things, and stuff. No, you go deep down, you're trying to support the thinking of the viewer and understanding the data. And I can tell you what data thinking is and turn them into principles. This is a big idea because it's making now a more of a science of this. These are principles of scientific inquiry as well, too. when you're showing that.

And so the principles, this is the grand principle of analytical design, the principles of analytical design are designed from the principles of analytical thinking. And people don't act like that. They say, oh, hey, we can do donut graphics. We can do donut graphics now. Well, how does that help the thinking of the view? Does it testify to causality? Does it make comparisons?

Does it tell the truth? And so it makes it a completely different thing. Rather than, oh, the new has donut graphics in it. It gets to be the field now, unfortunately, of data visualization is becoming more about itself than about helping people understand data. It's like the economics department is about economics, not about the economy. that these things become about themselves. And this is what's happening in the packages,

and they're comparing each other, and they make, you know, they often, you know, get the lowest common denominator, so everybody has a donut. And I think that's a sin. Here, my advice for everybody, the 200th publication of logistic regression is that every major graphic should have a package insert with it,

like drugs to, pharmaceutical drugs, and that they have warnings. For example, never make a causal inference from logistic progression, regressive, multivariate, okay, And that's so serious that there's a black box around it from the FDA. I wrote that up in my new book. And that should come. Box plots, for example, are an enormous censoring of data.

It's called binning. And it's two-dimensional binning when you have a row of box plots. And drug companies hide stuff all the time with box plots. Just show the data dots. Show the data, yeah. Because we have high-resolution screen cell. We can see the data. We don't have to use these summary things.

And so the box plots thing is don't trust anybody who's using them because they have cherry-picked those like crazy. They choose the bins. They choose the fact that there's a box plot. And they can find fake breaks, turns, ups and downs, which require a whole lot more data to model that, to have to go up and to, you know, start having a polynomial thing instead of just a straight line. And it's, and so you get these cheap things. There's a plateau that happens at this point when they're taking the drug, you know, and we have to add a whole lot more there.

The thing I've most discovered from a viewer's point of view is most strong. strongly in the new book where I've done 40 pages on medical research from a statistical side. And we've got to be inherently deeply skeptical of human research because of the replication crisis, because of all the false papers and medicine of a lot of cheating with the West, with the Bloth, I don't know if you know about this, the reading of Blot, Western blot tests, and they Photoshop the same blots in several times. And in some molecular biology journals, it's the Photoshop shows up in like 4% of the published papers. Oh, yeah.

Okay. Really fake things. And so I used to believe very strongly. I did quantitative political economy, election predictions and all that kind of stuff. and it's and I believed in it more I was doing it and and thankfully most of my papers got replicated I didn't cheat that much but the fact that it's medical research where there's so much their lives at stake at stake and the fact that in this country it's the only place in the world where tremendous amounts of money are made from sick people and from fudge data.

And the FDA doesn't do all that well. And they fight a losing battle because anybody who's a good biostatistician is going to work for a drug company. And it's a great big, it's an enormous, it's a public health problem. The cheating in medical research is a public health problem

and should be treated like a public health problem. And I wouldn't have said that 10 years ago or from all my other stuff, I was much more thought that numbers would, you know, help bring us to truth. And that's true. It's easy to all the, it's easy to lie with numbers, but it's even easier to lie with words. That's a good quote. I like that one. You can see the lies better than with words. But that really, of course, Mike can, you know, skepticism strongly about the routine falsity of a lot of research on human beings. When people turn to telehealth or weight loss, they're looking for real support. That's why more people are choosing orderly meds.com. Orderly meds connects you with real doctors and access to proven GLP1 medications like

semaglutide and terseptatide. No guessing, just a more supportive experience. And all shift directly to your door in discrete packaging. Do your research. Ask questions. Then visit orderlymeds.com slash podcast for an exclusive offer. That's orderly meds.com slash podcast. Individual results may vary now.

Medical advice, eligibility required, C-Sight for details. You did a very in-depth analysis that I learned a lot from of the space shuttle disasters. And there, I would say that it wasn't greed or an attempt to lie, but just people went a little astray in how they presented information. and with terrible consequences. Could you explain to the people who don't know about this example? What went wrong with? I worked in the third book,

I have the Challenger, which was I basically have Richard Feynman's take on Challenger. And I wish I could, well, I was that sharp, actually. It was really something. And he tells us a great story about it in one of the, you know. But my own independent. work was on the second accident, the challenger and the other one. And I got, right after it went down, I got all the fly.

So it was injured when at launch, when a piece of foam broke and hit the wing. and hit the wing on the launch and made a hole size of basketball and it flew for two weeks with the hole in its wing because there's no air up there. Who cares, yeah. Who cares, yep.

And they knew there was a problem. They may have known quite well by nobody ever says, but it may have been that a spy plane took a picture of that wing, but they don't want to express the resolution, you know, say what, the resolution in the system. Sure.

But they knew there was a problem. And they did, engineers on about the fifth day did a big PowerPoint presentation. I got that about a week after the Columbia went down. I got it via a information, you know, federal government information thing that a reporter had done, and I got the slides. And I don't know anything about rocket science, but I know a lot about the relationship between evidence and conclusions. And that wasn't, what they were doing was perfectly clear to spot. And I take the key slide apart and you know they're in trouble because they're measuring things in cubic inches in trouble right there. There's a family of two, two things crashed into Mars because of nine of that straight.

These guys weren't cubic inches. But on one slide, they abbreviated. cubic inches three different ways. If they were sophomores at MIT and the graduate student was grading their paper, graduate student would write on the thing, have you thought about insurance sales as a career? It's just, you know, it's just a sign of something's really wrong here that the They can't get units of measurement right in three different ways of writing on one page. You know, and none of them were inches cubed.

They were in, CU, just, you know, amateur. Yeah. And they have some models and they test it and so, but it all gives it gives it away right there. That they don't have the material to make a decision that everything is okay. That's what they said. Everything's okay. And it was right there if you saw it, you know, especially if you knew it was an accident. But it's absolutely.

So I did that on my own. I got a hit call from Boeing and that they had trademark on this or copyright or something. And I said, well, it was gone by a, you know, government thing. And the commission that investigated it published in their, their final report, which is the 100-page summary of all this stuff, my analysis for that slide, and it said, we've got to stop engineering by PowerPoint. And it turns out all the documentation of every project at NASA is done in PowerPoint slides. There's no technical reports. They used to do beautiful technical reports. They were famous for them, you know,

like 10-pagers and stuff. And so they use it as a general attack on engineering by PowerPoint. But the point for me is that the shuttle people investigating, who are a pretty fancy group, investigating the accident, picked up on what I said. And I don't know anything about rocket science, but I know what the hell, I have a more powerful skill about, I can tell the difference, you know, between the relationship, I know about, I can understand the relationship between evidence and conclusion. And that's a different thing than knowing rocket science. Because it's more general.

Yeah. Broader. That's very interesting because I know that, you know, you've said you've criticized PowerPoint before very trenchantly, and I'll confess, I use PowerPoint all the time when I give talks. But I guess I would never think to use it to sort of share information as text. That makes no sense. Yeah. Yeah.

Yeah. I had a wonderful thing happened very early on about PowerPoint, which I didn't hear about until 15 years later. So the PowerPoint essay comes out, and it has the Columbia and it's among other things, and it was called the Cognity style of PowerPoint, and it had a picture of Stalin giving a talk. And the people down below, you know,

all the soldiers waiting down below, making remarks about his bad PowerPoint. And I somebody read that essay before it was published and said, why don't you say what you should do instead of just saying, you know, bad PowerPoint? And I first got kind of stony. I said, my job's not to rescue PowerPoint. And I thought, well, but I should rescue my audience, my people.

And so I wrote one page in, which is, every meeting should begin with a handout that uses sentences, two to six pages using sentences, no bullets, and every meeting begins with the 30-minute reading period. Boomie. And it's how I taught. They confused Ivy League undergraduates, but we actually had to think in class.

In class, oh my goodness. In class, we had to think. That was, yes, they were used to scribble, they were very good at scribble. but they had. And so if I had a proof on the board, I would pass the proof out. So they didn't have to take notes and then they can annotate how I got from step three to step four, you know, marked that up. And so they weren't in doing stenography anymore, you know. So a few months after that came out, Jeff Bezos and his direct assistant were flying, reading aloud my essay on PowerPoint. And they

saw that set of sentences, six pages, and they immediately adopted it. They threw out PowerPoint, and the highest level decision-making was made by the, there was no presentation. There was no rehearsal or no slide. There was the six-pageer. People can read that faster than you can talk. And so I have my courses, people got all five books, and there was reading all during the class. I mean, talk a lot too, but we would stop and read these two pages, and then I'd talk about it, so on. And so it was back and forth of them reading different mode, and they could read, they could skip things they're not interested in. So with slides, everybody has the same slide at once, and it's controlled by the, but with reading, everybody in the room can use their own priorities and their own sense of relevance with that. And so all the work of preparation went into the report.

And a team might even do that six-pageer. And then they discuss it for an hour and a half. And he says it gave us an enormous competitive advantage. And he said they wrote about this 15 years later. It gave us a tremendous competitive advantage, an order of magnitude competitive advantage. They said this method, that everything that we won on went through this method, and they just went bat shit.

I didn't know about, I was feeling bullied by Microsoft and Boeing and stuff, and people doing saying bad things about me and stuff. And here, Jeff Bezos was, you know, the Amazon was doing this and thinking it was the greatest thing in the world. It was unbelievable. And I would have felt very comfortable and not so paranoid and friends. It might know, you know, I could have told that story, but it didn't come out. Or maybe they could have slid you 1% for the profits.

Well, that's another point, which is I patented a medical interface a long, long time ago, but I decided to make everything open source. I thought about sparklines doing that, and I had a patent lawyer who said they could do anything. They could patent anything. Microsoft patented sparklines, but they didn't. Oh. And they used it as a trademark. But my view is I'm open source.

Yeah. And also, I'm doing just fine on all these books and all this teaching. I don't, I don't like that. I like the idea. I'm so happy to get the ideas out. Yeah. And so hearing that Amazon was using this to great success and lots of other people, you know, that made me so happy that had consequences.

And the thing about meetings, I mean, this goes a little. little bit beyond the visual display of information, right? I mean, this is a kind of a way of thinking, right? I mean, and then the PowerPoint critique gets into that as well. So is there a future book that has nothing to do with data visualization? Well, you just exposed it. I have volume six, and let's see if I can tell you the title. Presenting, analyzing, data, slash information. Smarter communications, shorter meetings, content, credibility, clarity, efficiency, honesty. Oh, very good.

Part two. How to evaluate presentations. How to make presentations. So it's both from the consumer and the producer point of view. See, so they're both thinking about credibility and content. and producer. And then the second piece of this two-chapter thing is data analysis, visualization, and the truth. And this is a sort of short course in ET. Those titles report. It turns out presentation means kind of everything. You could say it's like a medical report. You could tell it's, you know, but it's focused on both the production and consumption and the interplay between the producer

are in consumer. Hey, everyone, it's Cal Penn. I'm the host of Earsay, the Audible and I Heart Audio Book Club. This week on the podcast, I am sitting down with Ray Porter, the narrator of Andy Weir's audiobook Project Hail Mary, massive sci-fi adventure about survival

and science, and what happens when you wake up alone very far from Earth? I really had to make a decision because I caught myself getting that frog in my throat and starting to get teary as I'm narrating some of these sections and it's like okay yo yeah yo is this indulgent and I really thought about it I was like no at this point it would kind of be betraying the trust the author and the listener have in telling this story if I don't go through it but there's places in this book that that deeply emotionally affected me and I left it on the mic that's great because it served the story people will say like

oh my god I cried at the end it's like yeah dude me too Listen to EIRSA, the Audible and IHeart Audio Club on the IHeart Radio app or wherever you get your podcasts. When people turn to telehealth or weight loss, they're looking for real support. That's why more people are choosing orderly meds.com. Orderly meds connects you with real doctors and access to proven GLP1 medications like semaglutide and terseptitide. No guessing, just a more supportive experience, and all ship directly to your door in discrete packaging. Do your research. Ask questions.

Then visit orderly meds.com slash podcast for any. exclusive offer. That's orderlymeds.com slash podcast. Individual results may vary now medical advice, eligibility required, C-Sight for details. Well, it's crucially important in the modern world, right? There's so much information, so much content. Our attention is so very important. And there's, there has to be huge inefficiencies that we haven't quite figured out yet. I mean, I know when I go hear someone give a lecture seminar, colloquium in physics, and it's an hour long, I will absolutely learn more. from talking to them one-on-one for five or ten minutes, then I will from an hour-long presentation.

Because you can control, yes. I guess so. I guess so. But is there, how do you make that scale? I mean, I don't always have access to the presenter myself for even 10 minutes. I write about efficiency. It's in the title. And one of the principles is show up,

and finish early, the presenter. Show up early, jet people up, get them to start reading the documents, and finish, they'll be thrilled. No one ever wished the meeting longer. Thrilled. The other thing is a good six-pageer can pretty well do it. I have thought times of, hey, read this. and just say a little bit.

And through my class, I do that. It sits all there. Read it. They can read twice as fast at least as you can talk. And they can choose what they read instead of the damn bullets. They can choose what's important to them. And everybody's reading differently. It's a tremendous advantage to, instead of poking through the slides too fast, too slow, too boring, they can skip paragraphs.

They can go, oh, ear's letting one. They can mark it up. They can, you know, they can read it twice. They can check, you know, something back. They can mark it up and then, oh, there's still a few months. Let me see now. This was good. This is good.

I don't have to worry about that. So, and, you know, you could at some places say, anybody, do you want to discuss this? People won't dare put their hand out. No, no, but except people who always. Right. They are something who always do. Yeah. Yeah. I have a strategy about people who ask questions, which is sort of this. You think about the priorities of all the other people in the audience. The person they'd most like to hear talk are themselves.

I agree. Secondly, they'd like to hear me. The people they'd least like to hear talk are their fellow audience members. So on that principle, I decide, I'll talk. You can do handle the questions and maybe under 20 people. It's more of a discussion like a little classroom or maybe 25. But it gets, if you get over, if you get over 30, you have now people sitting in front, who are people who ask questions at everything.

You know, they're professional. And it's often they have some other cause and, you know, or it's obvious or, you know, it doesn't. And we're wasting the time of, you know, the other end minus one people in the room, especially if N is big, you know, if there's 300 people in a lecture, you just can't do it.

It's not a discussion. It's these little mini speeches often. Or they saw maybe one in ten has some kind of grievance. Say, I've used PowerPoint for a 20 year. That strategy I just mentioned is in this essay about the audience and questions and about the priorities of the audience. I think that's a very convincing argument about priority. of your audience. Who would you like to hear talking? You can't talk yourself. They want to hear the presenter. Yeah, it's a very big question for the modern world, how we share information and how we

choose and what our timescales are and our methods. And I don't think that we're very good at it yet. So I'm glad to see you pushing to at least try to get better in that direction. You've got to, because there's so much stuff. So much stuff. The other thing is there's some good research on ignoring things. Oh, yeah. And being self-aware of ignoring and being self-of-deliberately ignoring this. I wish I could do that when I look at Twitter. You're not alone. I don't say.

I can throw away a whole afternoon, you know, poking around. And it's kind of interesting. It's just interesting enough. Just interesting enough. Oh, how old warriors doing? You know, they have a game tonight. I know. And it requires often beyond my self-discipline.

Yeah, yeah. I charged it away from my bed. Okay, good. I put my phone in the kitchen. We have to trick ourselves. Yeah. Well, and the relationship between art and science here is fascinating because as a scientist, you know, I like to think that a theoretical physicist,

we're trying to construct a theory, a model we're working toward that. But as an artist, it's more of a craft. There's rules for this or suggestions or whatever. And I'm wondering if you think of your own work in visualizing information as being articulations of a single underlying theory or as just learning in a more piecemeal way and trying to use our judgment along the way. The smart alec answer and half true, is that inspiration is for amateurs

and the rest of us just go to the studio every day and go to work and I see my art as what it has in common with real science is intense seeing and understanding that intensity brings some understanding and then ability to change and work from it so on. And everything serious requires, unless you're supremely talented like Picasso, requires a series of steps, of change, of discovering the material in art as you have an idea.

and I can tell within about half an hour whether this is going to work out or not and I have learned if I can't find promise for it's a half an hour as I call my backhoe operator in and say bury that because it's not going to work and it's going to waste time

that I know this is going to work it's not working now but I know it will and then it's trying to avoid words of not saying it looks like Picasso. It looks like Stonehenge. It's a piece of stone. And so I see it for its traits. Not what it's name, but it's color, its texture. And the very special thing about sculpture and about physics is air is a material. Space, absolutely. You know, the only two things in that in that world

are sculptors, air is a material, and space is a material in physics. And that's, I'm not quite sure what that means, but, well, it is thinking about air as a material. That's what sculptors do. When I'm working with my colleagues on a piece, probably half our comments are about airspace. And it's like figure ground on paper. That's trivial. That's just flatland design. I wrote a whole book about

basically escaping flatland. And that's where I knew graphic design was easy because it was flatland. Really hard stuff is you've got air as a material and it's a vague and it changes from every perspective on every kind of light

and every kind of sky and whether it's raining or not. And so there's such a multiplicity of things out there. there to sort among and make decisions about. But it's, I don't call it, it's not craft, it's a kind of, of the technical name of doing a piece is disjointed incrementalism. Okay. Otherwise known as muddling through. They're small steps. They're kind of separate steps. It is a muddling through. It's drying things out. It has a clear stopping point. In the work, I find it at the end of the first

kind of ending, at the end of maybe a day or a couple of days of work, I think it's really great. And I believe that fairly strongly. And I get up the next morning and see three things wrong. And I'm willing to change my mind, but there's something I have to believe in it. for a while and defend it, you know? Yeah. And then gather myself with fresh eyes. Sometimes it's the next morning or maybe even the next day. And we said, we've got to do this now and try that.

And that's especially the case because I locate the art. That is, I have 234 acres of my own sculpture. It shows only my sculpture. And we have backhoes and we make ridges. And no other artists has control of space of the land. Richard Serra gets a few hundred to maybe 500 square feet in front of a building laid out by an architect. And they say that's where you're going to put your piece.

And this, I have control of the landscape, of the trees, of their seven ridges, ups and downs, the location. We can change it. I usually will change it maybe after six months, some better space. And all of there is now completely changing the air, too. Air is a material. And so it's just like in self-publishing my books or have complete control. There's no bureaucracy.

There's no, thanks to the books, I've been able to pay for all the sculpture stuff. Yeah. I do big landscape pieces. The market for landscape abstract landscape art is like to market for Canadian experimental poetry. It's not a big market, which is actually good, because I'm free of pitching to rich people about why they should do it. Good.

So that's the same thing with making the books. There's no bureaucracy. There's no editor. There's no editorial board. There's no, I choose the printer. I work directly with, so it's all this hands-on thing that is combined with the mind. And those are, those two, it's those two things that have really helped me because it's, though there are, there are no middle people.

Yeah. There are no assistant deans. universities have become bizarre in the last 15, 20 years with the deputy assistant provost and endless I have a law of university growth, which is the doubling time of the bureaucracy is 12 years, during which time the number of faculty and students remains constant.

It's astonishing the rate of that. Yeah. Well, they're doubling time. That's something. Yeah, that's right. I do want to give you a chance to talk about one other artistic thing, which is the Feynman diagram. Oh, yes. I love all the Feynman diagrams in your new book.

And, you know, the audience can't see, but as we're talking to each other, there are Feynman diagrams behind you. Well, what is it that make, I love Feynman diagrams, but why do you love them as much? I grew up in Beverly Hills, or I went to high school. And I never knew Feynman. I never went to a talk, but a couple of my friends went to Caltech. I found out about his physics textbook, the three-volume. Yeah. And so that was kind of introduction.

And he has a very, the QED book is very good. It's mainly in English. It's four lectures he gave. And there are lots of Feynman diagrams. And they're a miracle about, you know, you get the 17th significant digit accurate in theory and practice and so on. And so that went in the fourth book, a whole lot of confinement. And then I, here's how I started making the sculptures. I made a huge rocket, 80 feet long with an airstream trailer on the end.

And it's like in launch position only, it's at an angle. It's a sculpture of mine, big sculpture. Rocket Science 3. And it has lights inside and rotating TV antenna in an airstream trailer with wheels and all this. And it's quite prankish. And I showed it in front of Fermilab along with Feynman's van. I paid $10,000 to have Feynman's vans repaired. They brought it in and they brought just my airstream trailer in, which I didn't bring the rocket in.

It's 80 feet long and put it in front of Fermilab. when I had a big show of things. And the Department of Energy Cabinet member came and loved them, and so they bought a bunch of them. And they're at a Terminatorial Lab. I first used them on that irstream trailer.

It's going, you know, to some other place. And the aliens, or the people, whoever they are, far away, they're not going to understand what the NASA logo was or the flag, people understand Feynman diagrams. Interesting.

And they'll say the people inside are pretty smart because it's universal. It's universal. And, you know, they're, while we find the diagrams, all kinds of places,

because they're based on nature's laws. And some days it'll just a little code of it and and so on. And so it, and so it was a lovely prank. And I just put three, fine the diagrams on the side and they cast shadows on the aluminum thing and it looked beautiful.

They're also beautiful. That's the thing, right. And this turned out to be the G-minus-2 or something things and came out just a year or two ago. That was an accident. I chose these because they were 10th order and they were the coolest ones and a guy had printed the like 500 of them. There's thousands of them. But these are, I believe 10th order, Feynman diagrams. And it happened to come up with the, I know, something that was minus two. G minus two of the muon, yeah. Yeah. A way to find new physics, right.

Yes. And I showed that at Fermilab about three or four years ago. And that was kind of scary because, you know, they actually knew what these were, you know, understood them. And one of them said, complained about one of the things, you know, that was, you know, it was maybe not appropriate. He said, what's that? And I had prepared. And I had said, well, you guys divide by zero.

But we divide zero by zero, so maybe it's okay. Maybe I should have said, okay. And then five minutes, hundredth birthday, say the Nobel Foundation took them on, or the Nobel Library, some, that took him on some tour, they went to Hong Kong and then Colwood King. Yeah, okay. Went for his 100th anniversary of Feynman. Right.

And that was, I didn't go to the opening, unfortunately. It was just too much. Yeah. I'd already seen them. But the pictures are wonderful. And that just made me so happy. They were out there. And the secret of them is to make them raise them about two to three inches off the surface.

Then they cast shadows. And they're the most amazing things because you have a couple of perpendicular things coming out that pull them away, which create now a space going backwards to the wall, from the metal to the wall, by those posts. And the shadows look three-dimensional because of the light. And then, of course, the shadows change as the sun goes by. And so they just are totally alive and always different because the shadows are strong often, along with the silvery part. And this is a sign of a really good art piece.

And you get all kinds of amazing things for free. That's my favorite expression about a piece of a piece of a piece of art piece of, It's not true of all. That is, things you didn't plan on at all, but when it was raining, it did something magical. Or when there was butterlight with sunrise and sunset, it did something magical with the butterlight of sunrise and sunset. And I call that, this is all for free. And that's such a wonderful thing to make a piece that you can say that about. You can't say that about, you can say that about a lot of outdoor pieces because you've got rain.

and shadow and the light and the earth's rotating all of that. And all those were for free and completely unfathomable until you actually see them. You know, the combination of a shadow that's also raining or dogs running by and there's this and that. And that's a way of a good piece of art. And you never say that against a flat on the wall. It's the dead same, the optical experience.

You may be able to see different things somewhat, but not this stuff you get for free. Every day you see us, so this gives you free, fresh eyes. I have a flat painting, say, on the inside. After a month, I don't even see it anymore. I have to move it. These things, the pieces out here are,

they're always alive. They're always different. I'm always happy. to see them. I like rain the best. The rain makes the rust and the iron in the stone, you know, warm, have this nice warm, wash his, blushes color to them. Plus the stone looks great, you know, when it's wet. Well, I mean, this forces me to ask one more thing, then we can wrap it up, which is the importance of the time domain to everything that you're talking about. I mean, you're making the point that these kinds of works of art, even though they're stationary, they interact with their environment in such a way that at different times, they give you different experiences.

But you've also really emphasized, even in the data visualization world, the importance of when you collect the data and the importance of when you present the data. And maybe this is yet another frontier that people need to think about. I think the best idea in the new book is the following. never learn more about a process than when you watched the original measurements being made. That came from a great applies gladysician with the lovely name Cuthbert Daniel, who did industrial statistics. And so add a little more sulfur and, you know, step 34, that's industrial, and he do little experiments. And it was incredibly smart, MIT, et cetera. And he did applied work. And it was a famous consultant on drugs, but on industrial processes. And we wrote a

paper together about the FDA. And he told me that. And he said, here's an example. General Electric put PCBs in the Hudson River. And they spent billions trying to make up for it. And they had to do testing every day of how good the water was and report to the EPA. And so let's go out of the little boat to make a test. And it's a guy in a little small boat and he's got kind of a no one of a cup on the end of a stick. And he leans over out of the boat to take a sample. And he leans over to the side where the water's cleaning. The statisticians maliciously call that,

was sampling to please. The only time what you can see that is when you're watching the measurement. Right. You're there. And I have come to play many people's backyards. I watched three whole surgeries

at the Cleveland Clinic. One open heart. Two, robotic. I saw all of NASA's toys. Play at other people's backyard. And I did a section about being at the point of measurement in the book. And I did an interview about once every six weeks with a ICU and emergency room nurse for four years, five years now, before the epidemic, because she was my hairdresser. And for an hour and a half, I would just ask her a question and another question, and just listening.

and dropping, and see when there's, when the system variance is zero, you can use it, you can need an nana of one. Okay. That's a cool point. So she was talking

about drawing blood. She's talking about all drawing blood. Uh-huh. There isn't much variation. You can adhere most of, most everything in this one sample, of size one. Okay. And that's a very good way.

And it's accidental she's come to me. It's not any kind of drawing, you know, it's not any kind of cherry picking. It's just convenient. And I learned so much from her of the general system, of how it worked. I'm not there in the ICU with her, but I am asking questions,

emergency room now. And, you know, you think, okay, this is happening in every emergency room. There's this room in the country. You know, they're totally jammed up, and these things happen, and they're always filled with journeys and stuff. And it's better than shows and anecdotes, see, because we're having this observer who's just telling us what's going on, you know.

And that, I think, is the best idea in the whole book, and it's in my spirit of being hands-on. Yeah. And instead of these guys writing the 500th way to do such and such, logistic regression is what everybody uses. Go out and watch how the stuff's measurement. Get out on the field and watch the measurements and the scales will fall from your eyes.

You're assuming these observations are independent? There's a saying in physics that no one believes a theory more than the theorist who proposed it and no one is more skeptical of data than the experimentalist who collected it. I like that. I like that because they know the dirty stuff. Exactly.

That's probably the most important reason why we do labs in undergraduate physics. So you know that it's not a completely clean, painless experience to collect that data. There's some things that happen that you should be aware of. It's because a person doing it often knows the right answer. That's the, you know, you're seeing measurement error right, right? from the start in a way. Yep. Yep. Well, Edward Hepti, thanks so much.

I think you've given us a lot to think about and new ways of thinking in a very information-rich world that we live in today. Oh, well, thank you. I love doing this. Good. Thanks. Bye-bye.

Good. Take care. Bye.