Innovation Files: Where Tech Meets Public Policy

The Complicated Evolution of Information, With Jim Cortada

Information Technology and Innovation Foundation (ITIF) — The Leading Think Tank for Science and Tech Policy Episode 79

Over the past 150 years, humanity has generated an unprecedented amount and variety of information, surpassing the cumulative knowledge of previous eras.  Rob and Jackie sat down with Jim Cortada, a senior research fellow at the Charles Babbage Institute at the University of Minnesota Twin Cities to talk about how information shapes society.

Mentioned

Related

Rob Atkinson: Welcome to Innovation Files. I'm Rob Atkinson, founder and president of the Information Technology and Innovation Foundation.

Jackie Whisman: And I'm Jackie Whisman. I head development at ITIF, which I'm proud to say is the world's top ranked think tank for science and technology policy.

 Rob Atkinson: This podcast is about the kinds of issues we cover at ITIF from the broad economics of innovation to specific policy and regulatory questions about new technologies. If you're into this stuff, please be sure to subscribe, rate us, tell your friends. That really does help us. Today, we're going to talk about how information shapes society, and we have a repeat guest who writes fascinating books. Let's just say the most in depth, the most interesting, the most comprehensive books about how data, information, and computing have shaped our modern world.

 Jackie Whisman: Back again is Jim Cortada, who's a senior research fellow at the Charles Babbage Institute at the University of Minnesota Twin Cities. He's formerly worked at IBM Corporation in a variety of sales, consulting, research, management, and executive positions. His research and writing have focused on the business history of information technology and on the role of information in modern societies. His new book, which we're going to focus on today, is called Birth of Modern Facts. It tells the story of how information has evolved since the mid 19th century. Welcome back.

 Jim Cortada: Thank you. Glad to be back.

 Jackie Whisman: What are the major points you're making with your book?

 Jim Cortada: Several. First, we've created more information and different types of information in the last 150 years than probably all of humankind has created in the past. That's why we have the Second Industrial Revolution, why we call ourselves a knowledge society or an information age, because we've created not only a lot of new information, but we've also discovered a lot of information about our world. That's point number one. Point number two, it's become highly specialized.

 That's why we have academic disciplines, professions, and what have you. All of them use organized information in ways that were not conceived of even 200 years ago. That's how we get to be an information society. It's organized by disciplines, ecosystems, professions, and it's become a tool more so than ever before. It's more mathematical and it's very precise, and experts dominate our world. All three of us are members of that cohort. The thing that I find most interesting is that we've been able to change a lot of it and add a lot of it because of key factors in our society.

 We could afford to create information beginning in the 18th century. The economy could afford it. Electricity came along in the mid 19th century, beginning with a telegraph and going on the telephone and radio, and then TV, and ultimately to computers. That changed the nature of information. We got so much of it that we had to organize it. That's where the librarians came in and organized it by topics. And then we were able to create all kinds of disciplines from physics to economics and what have you worldwide.

 This isn't just a US conversation, and that's why today we know that we no longer have nine planets, we have billions of planets, why we know the temperature of the oceans every second or so all over the world, whereas we didn't even 10, 15 years ago. These are some of the findings that came out of this study. It's important because you cannot do your work in any discipline that I can think of or any profession today without consulting organized information. We would not have said that 200 years ago, but today you do. Those are some of the key findings.

 Jackie Whisman: It seems obvious to say that this history is important to understand because we're spending so much of our time discussing fake information, misinformation, conspiracy theories, cyber wars. But is there more to it than that?

 Jim Cortada: Yes, I think so. For decades, the people who were the gatekeepers, the creators of information were experts. We required the experts to go through certain quality control things like going to college, applying practices of the scientists, the scientific methods, validating what they had to say. After the arrival largely of the internet, anybody could go in and create knowledge, information, facts, whether true or not. The quality control declined. It was so easy to put information out there that people were able to use it to further their agendas.

 We have a lot of bad information out there. At the same time, because it's so easy to use information and move it about and create it, it's also affecting such things as how we deal with medical crises or wars. Just look at what's going on in Ukraine right now with cyber warfare. You would not have thought 20 years ago that that would've been so effective, but there it is. There's a lot of quality issues out there. Also, the fragmentation of information is a huge problem today. It's why artificial intelligence is increasingly becoming a useful tool to re-aggregate information.

 Now, what do I mean by that? As information increased in quantity throughout the 19th and first half of the 20th century, it got more difficult for somebody to know more than one field. After World War II, it became more difficult even to know an entire field such as all of physics or all of chemistry. So you specialize even further. We have all these little silos, and there are gaps of information in between them. How do you fill those gaps? Well, you're either going to fill them with rumors or novel research or fake facts, or you're going to use artificial intelligence to smash it together.

 That's why, for example, when you Google something, it's agnostic. It'll go to economics, political science, whatever, to get information that you want. That's a new world that we're entering, re-aggregating information again, which humans can't do yet. We have fake facts. We have gaps. We have an attempt now to try and aggregate information. I talk a lot about that in this book and will obviously in the next one, the sequel, which we'll talk more about our issues that we have today, but it's gotten messy and it's huge.

 Rob Atkinson: Jim, one of the things that I think about with this, when everybody talks about misinformation or disinformation, they're talking about the internet and some Yahoo on there is putting something up there. But I look at it in a much more disturbing way in the sense of if you look at a lot of the new evidence on, first of all, the amount of faked data on peer reviewed journals, I mean, I've been a peer reviewer and I've peer reviewed, and let's just be honest, it's a lot looser than people think.

 Jim Cortada: Absolutely.

 Rob Atkinson: A lot looser. Then you have, what I think, again, I'm going to sound... You and I sound like old... I'll sound like an old fogey. But when I got my PhD, there was a real, real expectation that you left your political views aside. You tried to get truth. I don't see that anymore in a lot of academics. Good example of that is these economists Piketty and Sayes. Thomas Piketty wrote that book Capital. Everybody who talks about income inequality cites their study. Well, it turns out they made a mistake in their study.

 It turns out that they vastly overestimated growth of income inequality by making some mathematical errors. They ended up coming back and doing a revision three years later that said, "Ooh, well, it turns out that the bottom actually didn't go down. They went up 30%. It didn't go up as much as the richest, but it wasn't anywhere near as bad as they thought." Nobody cites that study. There's a New York Times economist who just constantly cites the original study, won't cite the new study that revised the work and showed the more accurate thing.

 Thoughts on that. We seem to be in a world where even if you can correct facts, they don't break through when they're the truer facts.

 Jim Cortada: It's very difficult. What you say is absolutely true. I've seen it in multiple disciplines as I was putting this book together, because I organized it by discipline because that's the way people identify. I noticed the same thing. I would look at, for example, arguments that economists would have or political scientists, and there'd be food fights not only in the referee journals, but now increasingly in blogs and, of course, always at conferences. You wonder, you can see people's agendas on their sleeves in the text.

 Of course, in fairness to them, how do you leave a political point of view or worldview to one side and go completely neutral on the other? It's difficult. It's a messy border. Let me give you a personal example of how this becomes messy. When I started looking at the history of information, I thought a lot of information was basically hardcore, non-negotiable, factual. I was born on September 7th. My birth certificate says that. My baptismal certificate says that. But if you were sitting in Australia, you'd say, "Well, no, Jim was born on I think the 8th." They're looking at their calendar, right?

 Information has gotten fuzzy, plastic, malleable, like Silly Putty to a certain extent, and that's legitimate. But on the other hand, if you stretch it too far, like Silly Putty, it'll break.It'll become obvious that we have an agenda here. Now, Piketty's an interesting case study of where they had a point of view, an agenda that they were exploring. That's fine. I mean, if you were, for example, a fan of a president, let's just pick a recent one, say Obama, you want to study things that Obama did well. That's fine. Okay.

 On the other hand, if you find that Obama didn't do well on something, you have a moral and ethical obligation to say, well, he didn't quite make it across the finish line on whatever the issue is. That's objectivity within reason, right? In my case, I found that you could find two people who would look at the same issue and come up with two radically different points of view. Now, was it based on the data or point of view? It's gotten harder as I've gotten older to be as absolute about it.

 But I definitely see people both who are professionals, experts with agendas on their sleeves more so than when I was a graduate student and a young person writing books. There seems to be some ethical looseness there that in some cases they know is wrong and in other cases they're just being sloppy. I hate to say this, but I find that a lot of people who write books, make presentations don't dig as deeply into the topic as they should. Let me just give you a personal example of what I mean. 2012, I published an 800 page book about how computers spread around the world.

 Up to that point, there were a couple dozen books that were 250 pages that talked about that issue. They're all going global information society. Everybody listening to this knows what I'm talking about there. But by digging deeper, I found the story to be quite different than what all the pundits were writing about. If somebody double checked Piketty's math, which a reviewer should have done, they might have gone back and said, "Hey, Piketty, you've got some additional homework to do. Check out your spreadsheets. They're a little off."

 And by the way, talking about spreadsheets, I doubt anybody in the world has ever produced first draft spreadsheet on something and got it right. It doesn't happen. My concern, particularly when I was at IBM is I'd have some 25 year old staff person working for me bringing in a spreadsheet and they believed what was on the screen. I'd have to say, "That number ought to be about 1 million, not 10 million. How'd you get to 10 million?" And they click, click, click and go, "Oops, excuse me," and redo it and come back down to 1 million. Well, that's because of how did I know that?

 Well, maybe it's gray hair experience, I don't know, but there's a tacit knowledge there. It's a chronic problem that you find in all fields. I certainly found it working on this new book. Related to that is you have these intramural food fights within each discipline. I found no exceptions to that. There are genuine differences of points of view among the scholars and the experts. And then you have in there agendas, whether it's an industry that's trying to get environmental controls changed, or some food producer doesn't want certain regulations which would constrain their sale of food.

 That's how the FDA got formed well over a century ago to mitigate those kinds of issues. It's sloppy. It's not always clean and easy, but it exists all over the place. Now, a historian will tell you that that was always the case in 1500s, 1600s 1700s, and so on, but it almost didn't matter the further back you go because it involved a fewer number of people. Today, you can tweet something and all of a sudden you got 10 million people believing you.

 You go, "Whoa, whoa, whoa." That's not the same as somebody complaining about Erasmus mouthing off 400 years ago, where only a couple hundred people are going to read him. It's a big deal.

 Rob Atkinson: There's a great line by Daniel Patrick Moynihan. I think he was head of domestic policy for Nixon, and then became a Democratic senator from New York in his own right. Wonderful man.

Jim Cortada: Yes.

Rob Atkinson: He famously said, "You are entitled to your own opinions, but not your own facts."

Jim Cortada: That's correct.

Rob Atkinson: It seems like we're now in a world where you are entitled to your own facts.

Jim Cortada: Well, people say that, yes.

Rob Atkinson: People say that. And to your point about how messy this is, I see that all the time with our team. I saw it this morning. Somebody had a spreadsheet and it had a number, and I'm like, "Hey, look at that number. Tell me why it is impossible for that number to be correct." They were just reporting the number that they had gotten from, but that number was wrong. I remember a few years ago we were looking at data on broadband in states that the Federal Communications Commission publishes. One of the measures was what share of businesses subscribed to broadband?

 It was in average state, let's say, as most states was like 0.6 or 0.7. It was like 10 years ago. There was one state, North Dakota or South Dakota, it was 2.7. In other words, each company had 2.7 lines. Now, clearly this was not possible. 49 states are between 0.6 and 0.8. I had my guy call up the FCC and they said, "I'm sorry, but this is the data they reported. This is the data we're going to publish." You just have these errors that creep in at various places, and then you end up with a report that if we hadn't... We weren't going to report that number.

 But you can imagine, oh, North Dakota or South Dakota is the best state ever. It seems to me you have two questions. Maybe even in the digital world it's harder because there's more possibility of errors because it keeps getting migrated and moved into a chart, into a spreadsheet. You have that problem. And then the other problem we just talked about is people who are convinced that their take on the data, like the Piketty part. There's a big debate in the US about has manufacturing output gone up or down and all.

 The vast majority of people who should know better, they look at only the top line number as opposed to the 18 different industries underneath, which is where you find out why there are real problems, why the top line number doesn't work.

 Jim Cortada: The detail.

 Rob Atkinson: They don't either want to be bothered, or they don't want the true answer. I don't know, are we just stuck with that forever, Jim? Do you have any optimism to share with us?

 Jim Cortada:Well, the fact that you've got so many people involved in discussing any issue that you choose means that you will have more eyeballs staring at a topic and say, "Au contraire, the data is different." You see that a lot in science, the STEM fields, because there's more rigor there. The more you move into my world of the social sciences and the humanities, the fuzzier and the squishier the data becomes.You have the issue of precision too. If you're using math, it helps. If you're using sensors, it helps. Mathematics, of course, if you think of it as a language...

 And by the way, I wish somebody had told me that when I was around 12 years old. I would've gotten math a lot better. If you think of it as a language with its own grammar and vocabulary and so on, you can understand the role of precision more. The debates can get a little bit more clarified, but you do get some genuine discontinuities. I think you and I had talked about this a number of years ago when I wrote a three volume history of how computers changed the nature of work. I was working on this book in the '90s.

 The problem there was that the economists were saying famously, "I don't see productivity increases of computers in the numbers. It's just not there." Solo and some of the others said that. Yet at the time that I was doing research and also working at IBM, trying to convince customers to use more computing and IT and what have you, people who were making multi-million dollar decisions were absolutely convinced that computing was helping them and had helped them in prior decades improved productivity.

 I say, well, how did it do this? Because you want to optimize on whatever those learnings are. They were very articulate. These were middle managers. They weren't PhDs in economics from Chicago or wherever. They were just good old boys that were running a data processing shop. They had reduced inventory cost by 15% because they had better inventory control numbers, and they reduced shrinkage in retail operations by 5% because they were tracking their stuff better and so on.

 But they weren't publishing that. The economists had the voice and they were saying, "Well, we don't see productivity in the data." Now, at the same time, these managers and I and others, a lot of people, were talking to economists saying, "Hey, guys, you really need to go get new metrics. We understand you want to run with the numbers, so go get numbers." The BEA and other government agencies bought into that. And now we have lots of data that the economists trust and bless that shows that in fact, productivity increased enormously with IT starting as early as the 1960s.

 One, my study that did that is hundreds of studies that have done that. That kind of phenomena is going on today. It continues to do that. But over time, information does get better, but it may not be synchronized when the interest is there to see that better data. I know that sounds a little funky, but that's reality. That's probably going on right now with such things as cybersecurity, privacy, all the conversations about regulating social media platforms.

 The Europeans are more intensely involved in that conversation than the Americans at the moment, but the Americans are borrowing from the Europeans.

Jackie Whisman: That might be a whole new podcast.

Jim Cortada: That's a whole podcast.

Jackie Whisman: We have to have you back for it.

Jim Cortada: You got folks like... Oh, what's that lady's name? Sarah Lamdan just recently published a book on that issue. You might want to consider inviting her. I think her book just came out the last few weeks, Data Cartels. There are dozens of books like that that look at privacy issues. Zuboff is another one and so on. But the point is that...

Rob Atkinson: We try not to look at Zuboff.

Jim Cortada: But she's out there and people are...

Rob Atkinson: She's out there and everybody's goes to...

Jim Cortada: Just like Piketty. Just like Piketty is out there.

Rob Atkinson: Everybody loves Zuboff because she exaggerates and she makes it black and white. People eat that stuff up.

Jim Cortada: Yeah, exactly.

Jackie Whisman: With one more minute to go, we should close on your book.

Jim Cortada: Yeah. The conversation about disparate forms of evidence exist there. My feeling is that in aggregate in general, over time, the quality of evidence improves. My bigger issue is, is that evidence being used in ways that are, I don't know, from my point of view, morally or ethically, or from a sound business point of view, the most optimal, the most efficient? I think we all struggle with that. It doesn't matter whether you're a Republican or a Democrat, whether you're in a large corporation or a small company, whether you're a priest, a scholar, what have you.

 I think we all have to deal with that. We started this conversation by my saying that we have reached a point in society or have been here for close to a century, where you really don't want to form opinions or take action or decisions without consulting some body of organized information. I use the phrase organized information. I think it's a good term to use. Otherwise, it's just, to quote a Princeton philosopher, then it's just [inaudible 00:24:36]

Rob Atkinson: Jim, we completely agree with you that the world is one where you have to consult organized information. Our advice is there's only one source for organized information on tech policy, and that's ITIF. Everything else is second rate.

Jim Cortada: We laugh about it, but actually it's a true statement. I mean, whether it's my grandsons that I'm teaching how to vet information, or folks who listen to your podcast, clearly one of the things you have to do is use trusted sources. Everybody knows how to get the trusted sources once you define what it is. People who do their homework. People who make sure their math is right. People who've been doing it for a long time. It's one reason why when we were getting ready for this podcast, I said, remind me how long you folks have been in business, and you said 17 years.

Well, that makes you a trusted source because in Washington, DC, you would've been blown away years earlier. New York Times, I go to the New York Times. I'll go to The Washington Post, depending on which era we're in and all that and who's writing for it. Trusted sources are very, very important. It's absolutely critical. I would not be on this podcast if you were not a trusted source. Let me just cut to the chase, because I wouldn't want to be associated with a sleaze operation.

The only thing I have is my reputation. I got to protect it because I don't want to embarrass my grandchildren when they come to my funeral someday.

Rob Atkinson: Jackie, our new tagline would be ITIF, we're not a sleaze operation.

Jim Cortada: Perfect.

Rob Atkinson: That'll be where we go.

Jim Cortada: Well, I didn't mean it quite that way, but yeah.

Rob Atkinson: No, I'm just teasing you, Jim. Thank you though for the good words. Jim, thank you so much for being here. It was really great, and I've really enjoyed. I do have your book, and I'm about halfway through it. It's really an interesting book. I encourage everybody to pick up a copy. You definitely will learn a lot and it'll hopefully change the way you think about information and data.

Jim Cortada: Well, thank you for inviting me on.

Jackie Whisman: And that’s it for this week If you liked it, please be sure to rate us and subscribe. Feel free to email show ideas or questions to podcast@itif.org. You can find the show notes and sign up for our weekly email newsletter on our website itif.org. And follow us on Twitter, Facebook, and LinkedIn @ITIFdc.

Rob Atkinson: And we have more episodes of great guests lined up. We hope you'll continue to tune in.

 



People on this episode