Oral-History:John King (Aug 2021)
About John King
At the time of the interview, John Leslie King was W.W. Bishop Professor at the University of Michigan School of Information. For many years prior, he had served as a faculty member and administrator in the information school at the University of California Irvine. He held both faculty and administrative roles at Michigan in both the School of Information and the university central administration. His main research deals with computerization in the public sector and municipalities, as well as other organizations. He has also worked on privacy issues and some of the primary computerization projects.
For the previous oral history with King, see John King oral history, April 2021.
Copyright Statement
This manuscript is being made available for research purposes only. All literary rights in the manuscript, including the right to publish, are reserved to the IEEE Computer Society. No part of the manuscript may be quoted for publication without the written permission of the IEEE Computer Society.
It is recommended that this oral history be cited as follows:
John King, an oral history conducted in August 2021 by William Aspray, IEEE Computer Society
Interview
Interviewer: William Aspray
Interviewee: John King
Date: August 9th, 2021
Location: virtual
Oral History Interview with John L. King, Second Session, 9 August 2021
Aspray:
(00:00:05)
Okay, we're on now. So, it is the 9th of August 2021. This is an oral history interview, a second session with John King. The interviewer is William Aspray. We're doing this interview over Zoom. In the first session, we talked about your career and some of your reflections about some of the institutions you'd been at during your career. In today's interview session, we're going to start by talking about your research, and the goal here is to get an overview of your research. And I'm going to leave it largely to you to set the framework and run with this, though I will certainly have some follow-up questions. So, tell me about your research.
King:
(00:01:04)
Probably the best thing to do is to start with an old adage: "Everybody brings their autobiography to the table". What I am and what I do is the product of stuff that happened to me. I had a bias toward biological sciences when I was in high school. This bias took me, basically, in the direction of a physician by training who specialized in occupational rehabilitation.
This guy took a shine to me. I don't know why. He asked me to come with him one time to an occupational rehabilitation technology fair. It was held near my home. This was before I had a license to drive., I rode my bicycle down to this fair. My dad had been an engineer. He got his first engineering job because he could type. He insisted that I take typing. So, I had.
The first thing I saw at the occupational rehabilitation fair was this Magnetic Tape/Selectric Typewriter from IBM. There was an IBM rep there, bored out of her mind, standing next to this thing. I was the only person interested, so, I asked her if I could play with it. I did and thought to myself, "Wow, this is a real huge improvement on regular typing." That's what took me into computers.
The doorway was at the time called office automation. That took me in. My research since then has been characterized by three points. The first is that I flit from thing to thing. This has been a criticism of my work. My attention is not held for very long to any given thing. I usually am looking for underlying connections. I do flit from thing to thing. I lose interest perhaps too easily. But I'm looking for some underlying thing that catches the essence of what I'm looking at.
Second, I do have a pretty strong sense of the old Texas expression, "Dance with the one who brung you." Part of the reason I've been able to publish a lot is because I pay attention to what reviewers say. If reviewers say you should do this, I usually do it, even if I don't agree with it. The final point has influenced my work from the start: whether my work matters is more a function of luck than my skill.
If I am on a salient topic, it's going to be picked up and discussed more than if I'm not on a salient topic. What determines salience is very hard to tell. As I was focusing on being a researcher, which you had to do in a PhD program, I started looking at policy issues: questions like, is the investment in computing technology worthwhile? Productivity issues, centralization, cost benefit analysis, staffing problems. Very nuts and bolts, how do you manage information technology?
Most of this, particularly when I got into the PhD program and started working on my dissertation, was under a NSF grant to older established faculty members or people who were trying to establish themselves. I was a doctoral student, but this grant was basically to study computerization in local government.
Aspray:
(00:06:16)
Mm-hmm (affirmative).
King:
(00:06:18)
I couldn't understand why people thought that what I was doing was so boring. I thought it was really interesting. I came across an opening line in the New Yorker Talk Of The Town section, which brought this all home. The line was, "Government is boring and local government is absolutely boring." For the first time, I realized, "Yeah, that's why people find what I do so boring." But I was looking for an underlying theme, There were two underlying themes in local government. One is it's an administrative gig. You have to get the trains to run on time and you have to send bills out to people and stuff like that. The other one is that there's a big design component that ranges from social engineering, which public safety is very concerned about, to design of the built environment, which planning and development is concerned about, to how people use their spare time, parks and rec and that kind of thing.
The big thing I learned from studying local government computing is you can't understand local government computing unless you understand local government. That is, you have to understand the domain of something before you can understand what difference information technology makes in the domain.
Aspray:
(00:07:58)
Mm-hmm ( affirmative).
King:
(00:08:00)
That was a really important lesson to me. It raised questions about why? What's going on in all of this? And that took me into the systems view, the first part of the systems view, which was heavily influenced by West Churchman, but it was also influenced by popular music: Donovan and Joni Mitchell. This was in the early '70s. There was a notion in popular music that everything is circular. Everything comes back on itself, the Great Mandalla and all this took my attention and led me into a lot of presumptions and assumptions, things like the Sciences of the Artificial by Simon and the Social Construction of Reality by Berger and Luckmann. These are the things that really had an effect on my thinking.
Also, I was working closely with somebody that we both know, Rob Kling. Rob was one of the more remarkable people I've known. On the one hand, he had very precise interests in electronics and computing. He was an Electrical Engineering major, but he was also interested in social impacts. Rob introduced me to Joe Weizenbaum and Abbe Moshowitz and other people who were talking about the implications of artificial intelligence. My advisor, Ken Kramer was an architect by training, so I was very interested in concepts about design and the built environment and so forth. I got intrigued by what I... I didn't call it this at the time …the banality of IT application. Most important IT application was incredibly banal. It had to do with things like efficiency of operations. One of the most important developments at the time was something called transaction processing.
It's not only forgotten now, it was forgotten even then. But it was really important. It changed the way things work.. There was order entry and fulfillment, which laid the groundwork for electronic commerce. There was time definite delivery, which changed the world of distribution. And of course, there was all this speculation about artificial intelligence and this got me interested, broadly speaking. Part of what I became interested in, because I moved from management, which is where I started, into a computer science department. One of the most rapidly rising topics, which was software, was marginalized. And it was marginalized for a long time. I knew it was marginalized because the computer science department lumped me in with software.
Aspray:
(00:11:57)
I see.
King:
(00:11:58)
Social impacts of computing and software worked together, known as area five. We didn't even have a name.
Aspray:
(00:12:13)
Uh-huh (affirmative).
King:
(00:12:13)
We were area five. This intrigued me because I could see that stuff was moving towards software. I started thinking about the problematic of how do you be part of the solution rather than part of problem. I had read Lewis Mumford and Jacques Ellul and so forth and so on and I knew how to be a critic of technology. And then maybe I'd read Langdon Winner and other people who were reflecting on this stuff. I was surrounded by people who basically have an engineering mindset in computer science. I wondered how what I do factors into building artifacts. That’s what engineers are interested in. The answer to that question was requirements. What I work on is requirements.
It was already known in the software world, particularly because of the failure of the waterfall model, that most system failures could be traced back to poor requirements. And yet, you would find books on software engineering that started off with statements like, "Start with clear and ambiguous requirements." My thinking was, "Where are you going to find those?" It turned out to be extremely difficult to get the requirements right. I focused on getting the requirements right. That's sort of what I made my name on in information and computer science back in the day. That's why I got promoted.
Aspray:
(00:14:19)
So, tell me about what you learned about that, what you taught to your more technical, your more engineering oriented colleagues.
King:
(00:14:32)
A simple way of characterizing the way they thought about things was”truth wins”. It doesn't. Process and power claim the truth. And of course, they claim the truth wins, but it's really process and power. I was very interested because of the work I'd done in local governments, which are inherently political entities. I was interested in power and had come to the conclusion that being naive about power results in a lot of these problems. So, Kalle Lyytinen and some colleagues and I started doing work in requirements, focusing on what we call the opposition coalition or the opponent coalition. Any project has a proponent coalition or wouldn't get anywhere, but most projects have an opponent coalition. You have to know who the opponent coalition is and why they are in opposition or you can't do a good job with requirements. My work began to focus on smoking out the opponent coalition's concerns as part of the requirements problem.
Aspray:
(00:16:27)
In a project, for example, there might be some people who are vocally opposed to the plan that's being put in place. My guess is that there are a lot of people who are passively opposed to it.
King:
(00:16:47)
Passive opposition can be very powerful over time. If every time you bring up something, people look the other way or people just nod in a way that tells you that their preference is that you go away, this has the eye-rolling effect. There have been so many expectation failures with regard to information technology, particularly AI. I talked to the person who ran the Long Beach public safety subsystem implementation of the 1960s USAC project, which was the first ever federally funded project to build integrated systems.
This person told me that the project’s computer representative said computers could predict when and where a crime would occur. All the city had to do was position the officers there ahead of time, wait for the crime to go down and then roll up the perps. When he explained this to me, I said, "You didn't believe that, did you?" He said, "Yeah, at first we did believe, and then we realized how ridiculous it was." And I will say, parenthetically, I saw exactly the same prediction in one of these recent smart cities things. Nobody remembers that these things have been around multiple times.
I had a fair amount of respect for the problematic of forecasting. For a while, I was really into this forecasting thing and a member of the forecasting association. They're still around by the way. They're still trying to forecast. I did something that a lot of people do. I wouldn't recommend it, but a lot of people do it. I couldn't make very much headway because things were so difficult, so in response I made them even more difficult.
I went from the organizational level, which was where my work had been, to the institution level. That was big change. I became interested in what I call highly institutionalized production sectors. I became interested in things like higher education or education generally, healthcare, public utilities, freight logistics, passage, the finance system, etc. I started tracing how information technology had transformed those.
That's where I've been since. One of the problems I was tussling with constantly was to determine to what degree does the technology really make a difference? The conclusion I came to, for better or for worse, was that it can make a huge difference, but people usually are wrong in their predictions of how. For example, the entire field of management, one can argue, is due to the Bessemer process for making steel It wasn't until the Bessemer process that you could make large quantities of high quality steel inexpensively, and it wasn't until you could do that that you could build railroads.
Aspray:
(00:21:41)
Right.
King:
(00:21:42)
The railroads were instrumental in creating large enterprise.
Aspray:
(00:21:50)
Mm-hmm (affirmative). So, to what degree would you say that you were able to make a difference in the academy with your work? How did you, for example, shape the thinking of the software scholars?
King:
(00:22:16)
I'm not sure I did, Coming back to the point I made earlier, the effect I had was more of a matter of luck than skill. I thought I had made a difference. I was into the problems of software engineering by the 1970s, yet iin 2010, I heard a physicist dependent on computational physics say, "Our biggest problem is software, but that's going to get taken care of because there's this new field called software engineering."
I couldn't believe it. I asked him if he ever heard of Tom DeMarco. He hadn't. I told him Tom DeMarco was one of the founders of the field of software engineering. He was at both of the 1968 and 1969 NATO meetings where the field was launched. He wrote an article in IEEE Spectrum in 2009 titled, “Software engineering: an idea whose time has come and gone."This guy, he wanted to believe that the problem had been solved.
I became interested in what mobilizes people, why they believe what they believe, A lot of this was influenced by my reading of the 1906 speech by William James at Stanford on the moral equivalence of the war. My dad had been an engineer in NASA. I was a NASA brat, a southern California defense/aerospace nerd. The moon landing was a big deal, obviously. One day I asked my father what makes NASA go? He said it's part of the cold war. I subsequently read William James, Of course, Carter had tried to turn the energy crisis into the moral equivalent of war. James says is that if there's a war, that works, but it's really hard to get anything else to be the moral equivalent of war.
Aspray:
(00:25:37)
Right. So, drugs for example, would be another example, right?
King:
(00:25:42)
Right. It's a long list. I became interested in the history of world war two. My father had fought in world war two. I was interested in mobilization. When I came to Michigan, I went to the Bentley historical library, the archive of the university and looked at photographs taken in November of 1941 of isolationist rallies, and photographs taken in December of 1941 of guys in uniform walking on the Diag. That change was overnight.
Aspray:
(00:26:51)
Right.
King:
(00:26:56)
That intrigued me. Anything tied to war was institutionally very intriguing. I became interested in project Sage. I was influenced by Paul Edwards and his work on the closed world. I became involved in Dave Parnas’ discussion about the software to control SDI, the Strategic Defense Initiative. There were two things about SDI that really intrigued me. The first one was that it was so successful, despite Parnas’ argument that you couldn't really test it. And the Soviets were scared to death of SDI.
Aspray:
(00:27:58)
Mm-hmm (affirmative). But there were lots of people who bought into it. He was a particularly active and effective voice against, but there were many more that were supportive.
King:
(00:28:25)
And in fairness, you can say that the SDI gambit won. An argument can be made that the SDI was one of Reagan's most successful ploys to get the Soviets to back off. I knew a guy from the Netherlands, one of the first people who got his PhD in Strategy back in the 1960s. He told me he had done a really extensive study of top aerospace defense companies when he was a high-level consultant for Philips. He said that the Cold War ended in 1978 and the United States won, despite the fact that the Berlin Wall did not fall until 20 years later.
Aspray:
(00:29:45)
Right.
King:
(00:29:45)
He said, the United States won the cold war with the deployment of the Trident D5.
Basically he was right. You couldn't defend against submarine launched ballistic missile that had a incredible accuracy. It would land with a hundred meters of its target when fired from anywhere on earth. You could use multiple, independently-targeted reentry vehicles (MIRV) on these things with 200 kilo ton devices. When they saw this thing the Soviet high command probably said it's over – those guys can knock the daylights out of us anytime they want. That's where this whole concern about first strike capability really became an issue.
Aspray:
(00:31:07)
Right.
King:
(00:31:11)
I was intrigued by underlying dimensions of these things, life or death issues. One time Rob Kling said if the department of health education and welfare, (now health and human services was responsible for America's prowess in computing we wouldn't talk about aborting jobs. It was that fundamental.
Aspray:
(00:32:09)
Right.
King:
(00:32:12)
My long-lasting effect isn't clear from my research. To the extent that there is a long lasting effect, it's probably going to show up later. Most of my efforts have been institution building. I was an academic administrator at Irvine. I came to the University of Michigan as an academic administrator. I don't know this for a fact, but I would guess that there are people at Michigan who think that I didn't deliver on my promise.
My tendency to flit from thing to thing spilled over into administration. When Hiram Johnson of California was elected to the United States Senate in World War I he said, "in time of war truth is the first casualty." The truth is sometimes the first casualty in administration.
Aspray:
(00:34:31)
Mm-hmm (affirmative).
King:
(00:34:31)
Even in the sanctum sanctorum you can't talk about what's really happening.
Aspray:
(00:34:58)
So, it's not that you put an outside face on. It's just that, that's the way you think. Let me ask you about colleagues from around the world. There are other people who have been interested in organizational or management or social understanding of computing and computers. How do you fit within that community? Are there people that you work with? Do you have informative differences and approach or attitude to some of them? Can you talk about that issue?
King:
(00:37:12)
That's a fair question. My candid response is that, if you're going to be serious about the social effects of technology, you have to know a lot about technology. The occupational hazard of knowing too much about technology because you become a technologist.
Aspray:
(00:37:46)
Mm-hmm (affirmative).
King:
(00:37:47)
To the kid with a hammer, everything looks like a nail.
Aspray:
(00:37:52)
Right.
King:
(00:37:52)
The work on social impacts of computing by computer scientists tends to have one of two political ideological thrusts. It's either libertarian utopianism: let great people do their own thing, and it will be awesome. Or people put their heads down and they don't think about it.
It's not so much that engineering oriented programs, which are great technology-focused programs, are politically weird. They're just kind of weirdly apolitical.
Aspray:
(00:38:58)
Mm-hmm (affirmative).
King:
(00:39:00)
It's hard to find somebody out of the engineering tradition who has ever heard about Marx. Of course, they've heard about Marxism and they know it's bad, but they haven't read anything by Marx. If you try to tell them, Marx was important as the first social scientist to take technology seriously. They say, oh no, it's just wrong.
Aspray:
(00:39:32)
Mm-hmm (affirmative).
King:
(00:39:35)
It's not a studied critique of Marxism. It's just politically safe.
Aspray:
(00:39:45)
Mm-hmm (affirmative).
King:
(00:39:46)
There aren't very many people who come from the Social Sciences and go native in the technology fields.
Aspray:
(00:40:02)
Right.
King:
(00:40:02)
You tend to have people who are already native in the technology fields, who look momentarily at this broader set of issues. Or there are social science people who make forays in the technical zone and often make really good observations, but then go back to the social sciences or the humanities.
Aspray:
(00:40:33)
Mm-hmm (affirmative)
King:
(00:40:35)
It's difficult to understand the full complexity of technology and social if you aren't in both. But the costs to being in both is high. Most people are dissuaded from doing it.
Aspray:
(00:41:43)
Mm-hmm (affirmative) So you've made the case, which, it seems reasonable to me, that having somebody who stands for a long time with one foot in each camp is rare. Can you identify a few of those rare individuals?
King:
(00:42:05)
Well, yeah, I can. They're interesting cases. One example would be Phil Agre. He had brilliant insights about technology and really understood the technology and also understood the social, but he was a troubled person.
Aspray:
(00:42:31)
Yes.
King:
(00:42:33)
A few other Renaissance people took on these things and made very interesting observations from a disciplinary perspective. Paul Edwards is one like that. Some of your work is like that. Some of Jeff Bowker’s work was like that, as was Leigh Star’s. There are people who have interesting perspectives on this. I didn't just have a foot in each of two camps. I had a foot in three camps.
I had a foot in the social side. I had a foot in the technical side. I had a third foot, if you will, in the administrative side.
Aspray:
(00:43:32)
Mm-hmm (affirmative).
King:
(00:43:33)
I was interested in institutional development. Often that was very preoccupying. As long as I was Dean of the school of information, I could kind of control this. When I went to the Provost Office, there was no controlling it. That beast is big and so strong, and you can't stand against it: It consumes you. A while back, purely by accident, my computer that called up my calendar for back when I was vice Provost. It was all meetings.
I never got done because I was in meetings all day long.
Aspray:
(00:44:30)
Right.
King:
(00:44:32)
This is one of the big problems. I'm not saying that there aren't good reasons to have meetings. There are, but they eclipse good reasons to work on this other stuff.
Aspray:
(00:45:48)
Right. Hmm. Are there other things you want to tell me about your research?
King:
(00:46:20)
My research kind of grounded me. I I was trying to make the case in pretty much everything I did that you're faced with a dilemma. On the one hand, you need to bring a whole bunch of stuff into the picture. But if you bring a whole bunch of stuff into the picture of the picture it is really hard to understand. This the dilemma faces people who study this because the technology can be enormously powerful, but you just can't tell in advance how or when.
People look at the past as an indicator of what the future is going to be like, which is understandable. But what they can't take into account is how a breakthrough here will precipitate effects there. That has to be lived through before we look at that, and often we can't understand it until sometime after that's passed. This is why history is important. I guess if I were to classify the most important intellectual precursors or my thinking without being too nebulous about it, it was basically some combination of economic history and kind of political philosophy of the kind that I got informed of when I started studying local governments. The work we did at Irvine was informed by something called the political reinforcement hypothesis.
Aspray:
(00:48:49)
I don't know of this.
King:
(00:48:52)
In the 1970s and 1980s, many felt that the biggest effects of computerization were going to be a power shift . Power that went traditionally to political elites would go to nerds Technologists would take over from the traditional political elites. A lot of the work done on the project was testing that hypothesis. In the short run, the political elites win. Power is reinforced, it's not shifted.
Aspray:
(00:49:50)
Mm-hmm (affirmative).
King:
(00:49:51)
You can make an argument over the long run has seen a change (Facebook and Google and so forth), but the old model of power shift didn't happen.
Aspray:
(00:50:15)
Are there graduate students you have trained, postdocs you've trained, young faculty members you have influenced that continue the kind of tradition of inquiry that you've been doing?
King:
(00:50:34)
It's hard to make it doing this kind of work. The people who've been most successful academically have chosen that line of work within the context of their field.
Aspray:
(00:50:55)
Mm-hmm (affirmative).
King:
(00:50:57)
Some of them have gone on to be very successful in management, and I would characterize their work as sort of within the management information systems, for example. A few that tried to do this in computer science, but ended up focusing on some branch of computer science that was considered crucial salient by the places that they went to.
King:
(00:51:35)
Most of the rest have gone into consulting practice. They take this consciousness, this set of techniques, and try to figure out better ways to do practical things.
Aspray:
(00:52:26)
Okay. Why is it that you jumped from topic to topic over time, rather than stayed on one path and ran with it for 30 years?
King:
(00:53:27)
There's two parts to that answer. The first part is the remit. I would probably be more successful on some measures like fame or money or whatever if I had.
Aspray:
(00:53:47)
Mm-hmm (affirmative).
King:
(00:53:47)
I could be a guy who does X. I had that chance along the way. So that's, that's the ligament part. If I had done different things, things would be different. But I'm interested in stuff that interests me when I'm looking at it. I pretty quickly start asking, what does this all come down to?
Aspray:
(00:54:24)
Mm-hmm (affirmative)
King:
(00:54:24)
Most of the things I look at come down pretty quick. I haven't found very many things, except in the general sense that everything does, that illustrate what I would think of as the mystery. I think there's a mystery about why people make stuff that makes a difference. People are resourceful, creative. If somebody were to ask me to summarize that mystery in a word, the word would be monkey. Humans are monkeys. When we see something new check it out.
Aspray:
(00:55:20)
Mm-hmm (affirmative).
King:
(00:55:21)
I became very interested in what I call the stopping points that could make all of this other stuff moot. Two examples: large mass Apollo objects approaching near earth (if one of these hits us, it's over) and climate change.
To say that those things can't last is an understatement. People don’t care whether they get tenure, if they're about to die.
Aspray:
(00:56:14)
Right.
King:
(00:56:18)
I work in the space between. Some days, I think it's a really big space. Other days, I think it's more constrained, but it's interesting.
I have a great deal of respect, and well, affection to be honest about it, for technology. That has been there all along. But I am skeptical of our ability to know in advance what any given technological thing means..The combinatorics are enormous; you run into the combinatoric explosion.
I went to visit CERN in 2006. A physicist from the University of Michigan, invited me. We went down in the ATLAS pit, and we saw CMS and so forth. The most interesting thing he said to me was, "99% of the data that we collect, we throw away immediately." That's hard to square up with the notion that you keep all the data you collect. I asked, " Why do you throw it away?" He said, "It doesn't have anything to do with the Higgs Boson.” (That was the thing they were looking for.).
Aspray:
(00:58:24)
Right.
King:
(00:58:25)
It was deleting that unnecessary information.
Aspray:
(00:58:35)
Can you untangle cause and effect for me, in terms of your proclivities in your research style and your appointments, holding appointments across multiple disciplines, and so on?
King:
(00:58:58)
It's just the way I am, what attracts me, what holds my attention, what doesn't.
I'm not a very good commentator on that. People seeing it from without are better. There's also a practical element. I liked having a joint appointment at Irvine. I inherited it. When I came to Michigan I was offered courtesy joint appointments in what is now the Ross School of Business, and the Ford School of Public Policy. But, the provost at the time (Nancy Cantor) wanted me to concentrate on the school of information so I didn’t take the joint appointments.
I liked the interdisciplinary stuff, but for many it is a pain. Most organizations don't like it.
Aspray:
(01:01:58)
Right. Well, I can tell you that, I had this image of what the well-prepared scholar would be like in these kinds of interdisciplinary fields, and I felt like an abject failure in training my students to be there, right?
King:
(01:02:24)
I'm not sure you can train. I think it's something that's in you.
Rob Kling was able to pull this off because he was so intelligent. There was almost nothing Rob couldn't understand. He might not want to understand it, but he could. He's one of the very few people I've ever met, much less worked with, who could literally power his way through things.
Aspray:
(01:03:15)
Are there a small number of publications you can cite as being the ones that you feel are the most representative, or which ones made the most difference, or which ones you're proudest of? Those are slightly different questions, I understand, but are there a few things you can point to, that you've published?
King:
(01:03:41)
The papers that have had the biggest impact have been papers that explained why practical questions are so problematic. For example, the first paper that I really published in a mainstream journal, in 1978 with Ned Schrems on cost benefit analysis of information systems, has remained the best seller. That was in computing surveys.
I published another article on computing surveys on centralization, which ended the discussion of that for about 20 years. It's back. You know, nobody cites that old paper anymore.
Much of my effect was in the management of computing. I also had an effect with an old stage model of development. I concentrated on why it's difficult to figure things out that are complicated and not amenable to simple solutions.
In a lot of ways, my most long-lasting effect was to make the case, "Well, you think it's this, but you can make a case that it's that."
I wrote a paper with a former student a couple of years ago on productivity vampires. It was an exercise. The student and I were talking and I owed the editors of this journal something.
Academic work is a central life interest. It’s consuming. I didn’t want tp be consumed. I liked administration. It was like a puzzle. Every day, there was a different puzzle I had to solve and I would solve it. That kept me entertained. The research work kept me grounded, moving in the same general direction. I am now working on autonomous vehicles. I am intrigued by autonomous vehicles because the space has so many expectation failures. Lots of people think I'm weird. Maybe I am.
Aspray:
(01:08:16)
I don't know. I have a strong affinity to your style of working and the kinds of questions, and in part, because I'm like this in a way, but anyway…
King:
(01:08:29)
My guess is that, higher education made up entirely, or mostly of people like this couldn't survive. Higher education with a lot of people who just do the stuff that they advertise makes room for people like this, but that's just a guess.
Aspray:
(01:09:01)
To what degree do the information schools and similar organizations provide an opportunity and a good structure for being the kind of researcher that you were?
King:
(01:09:22)
I think that they provide a better opportunity to do that than the default options. The information systems field in management schools tends to be hampered, because management schools are dismissive of technology. Their primary intellectual overseers are from the social sciences, and the social sciences don't like technology, generally. Technology is just a variable. Marx's ideological parts were appreciated by the social sciences, but I’m not sure his views of technology were.
Engineering can be too swept up in technology, to the exclusion of social explanations. This is one of the things that I see a lot in the autonomous vehicle world. To the extent that autonomous vehicle work is dominated either by experimental or scientific engineering, it tends to be dismissive of the biological and social. If you want to include biological or social, it's like stirring in a tablespoon of salt tol correct it. It doesn't.
Most information schools are more appreciative of technology than B schools, and more appreciative the social than the engineering schools. I think this is a good thing.
The biggest problem facing the iSchools in my opinion is that, they're small relative to big, powerful schools elsewhere (engineering schools, business schools, social science programs). ISchools are easily pushed aside. In many cases, they come either from library science or from communications. Some have a huge approach avoidance conflict around professionalism. Should they be intellectual ventures without professionalism, or they should be professional schools.
Aspray:
(01:13:03)
One of the problems I have with the information schools is that they don't seem to have enough discipline, or discipline doesn't matter enough; there is this philosophical belief, unexamined philosophical belief that anything goes.
King:
(01:13:26)
Right.
Aspray:
(01:13:33)
Yeah. I had asked this last question of you intentionally, as a transition into the other topic that we start, that we were going to talk about today, which was about the information schools themselves. Are you ready to move on, and talk fully about that?
King:
(01:13:58)
The best explanation about the fact that the information schools aren't dead is need to incorporate both the technical and the social. If a university didn't already have an entity that did that, strong enough to survive on its own feet, the information schools were an opportunity to create that. There still aren't very many compared to how many chemistry departments there are, and they're spread across a range from research universities to teaching schools. It's a weird club. It doesn’t have enough members to create sustainable strata.
With chemistry a handful of schools are elite in chemistry research schools. Many universities have chemistry majors. Chemistry is required as an adjunct to other thing. There are a bunch in teaching schools, down to the community colleges, who do chemistry as prep. You have to satisfy O. Chem, or P. Chem requirements to do something else. It's probably on the order of thousands. With information schools, you're probably on the order of less than 100.
Aspray:
(01:16:14)
Right. In the US, that's probably true.
King:
(01:16:17)
Yeah.
Aspray:
(01:16:20)
One of the things that I've noticed is that, when we talk only about the research universities that are in information schools, they're overwhelmingly public universities, not private universities. Why do you think that is?
King:
(01:16:37)
It's a multi-fold explanation. I don't know how to portion the weighting on all of these factors. One factor is duty. I think some private universities use the number of people who want to take this, together with some notion about duty to the commonweal, or whatever, to say that, it’s the public university's job, not our job. We've got a lot of things we need to worry about, so we're not going to invest.
Also, there’s the old problem that having strong library and information science programs doesn't help the institution very much. A really strong library and information science program doesn't bring the distinction of a really good medical school, or whatever. It's a size issue and a throw weight issue. Like computer science or the material sciences, the degree of change in library and information science has been very rapid and very extensive.
People don’t argue that higher education shouldn't do chemistry anymore because others do it. You can hear people say library and information science shouldn't be done because it's being done by Google or somebody.
Aspray:
(01:19:14)
Yes.
King:
(01:19:17)
You have to think about that argument and develop your responses to it in ways that are effective to the people that you're talking with. It's a very hard problem to overcome. By the time you hear about it, there are some who want to believe it.
Aspray:
(01:19:44)
Right, so I introduced this topic in a roundabout way. You have presumably done some thinking about these issues, and maybe you had also thought about how you wanted to approach them in this discussion today. Maybe I should give you a chance to start again, at the place you want to start this conversation about this topic.
King:
(01:20:23)
I see two main zones of activity here. There might be three, but I see two for sure. One is the memory zone, which library and information science historically has been committed to – memory in the sense that, we know how to put things away, and we know how to get them back again. This is crucial to information infrastructure and epistemic infrastructure. Margaret Hedstrom and I have written about this. It includes not only what we know, but how we know it. This becomes important when what we know is challenged, which in a healthy society, happens.
The other piece is information processing. By that, I mean two things. One is crunching, transformation, taking this information and turning it into that information. It also involves data communications. Information science in LIS deals primarily with memory. The Shannon side of information science deal primarily with digital signal processing, digital communication. When you put those things together, and this is where the third one begins to come in, you can move to the importance of the communication of meaning. This is certainly a big issue now, with respect to Facebook and so forth.
These are all areas that you have to touch. The problem is, people have a hard time looking at all of these things as possibly of equal value. They tend to think some things are really important, and don’t pay much attention to other things. Some library and information science people acknowledge that computers are important. Some who build computers who think memory thing, other than computer memory is important. And then there's communication people who use Ev Roger's diffusion of innovation or the distinction between personal and mass communications.
But if you look across these three, the library and information science schools, some of which have morphed into information schools. Computer science programs, some of which are beginning to move into information programs and communication programs. That encompasses most of the waterfront.
Aspray:
(01:25:08)
At these four, those schools that have a serious research element to them. Right.
King:
(01:25:16)
Right. And into the library and information science world, I would place the archives world. But by tradition, archives don't see themselves as part of the library and information science world. They kind of see themselves as a standalone thing. In some instances, they're more public policy.
Aspray:
(01:25:46)
Hmm.
King:
(01:25:49)
Some of them are history-related.
Aspray:
(01:25:55)
My experience has been that the archival faculty members are put off to some degree by the institutional and very practice focus of the library science faculty members, even though there are a whole set of practice issues for the archivists as well. And they're much more driven by the literatures from the humanities as well as from the social sciences about culture and memory.
King:
(01:26:45)
Yeah. And to a large extent they have a foot in law.
Aspray:
(01:26:51)
Yeah. They sure are…
King:
(01:26:52)
The European focus on archives was as the voice of the state. Archives was the memory of the state with respect to the exercise of power.
Aspray:
(01:27:25)
Yes. Several times as you were speaking, I was remembering a conversation I had, six or seven years ago, with Elizabeth Churchill. She said to me, I have all these really smart young people who have trained to be data scientists. They can find patterns in the most imaginative ways. And not a one of them can tell me what the meaning of this is, the cultural meaning of what they find. In some ways the two traditions you've talked about in the information schools, it seems like those people are very high on one of them and not so high on the other.
King:
(01:28:25)
There is a critical saying that a cynic is somebody who knows the price of everything and the value of nothing. Archives, Library and Information Science, Computer Science, Information Science, Communications etc. sometimes exhibit this. Few people see how these things are connected. I think they are profoundly connected. If you look just at the history of OCLC, it started off as a skunk works trying to figure out how to put card catalogs online.
That turned out to be a problematic area. They embraced the problems and became a big player in that. The number of new titles (new books) in print continues to go up. We're not going paperless yet.
Aspray:
(01:31:01)
Right. You remarked earlier in our conversation today about the information schools not being large enough. And yet I remember very distinctly from the case when I was at Indiana University of this new school being set up and merging things into it, of how much resistance there was from lots of existing disciplines who said "you're starting to do things that we do, and you don't do them with the same kind of precision that we do them with". And so can you talk about the trade-offs, the potentials for the kind of size that you think is needed to do this more successfully?
King:
(01:32:11)
It's not just size, it's size plus history. Many computer science departments are dominated by theoretical computer science, typically analysis of algorithms, data structures, computational geometry, etc. These were really important when computers were processor bound (the most expensive resource for that computer was the central processor. People who worked on those problems seized the high ground and they ever get it back. Library and information science never seized anything that anybody else wants.
Aspray:
(01:33:29)
Yes.
King:
(01:34:46)
If you look at the history of library programs, most of them stem from the Carnegie Library Commission’s report that says the reason that libraries are failing across the country Is there aren't any librarians. Programs to produce librarians, like the department that was the precursor to our school, started in 1926 in response to this report. It mainly produced librarians for high schools. That was not very mathematical. Who's going to win?
Aspray:
(01:35:57)
Yeah.
King:
(01:35:59)
People in library and information science and archival communities have difficulty articulating the importance of what they do in ways that compete with computer scientists who point at things like Google and Amazon. There are two periods history for iSchools. The first was 1995 to 2020 boost phase; not getting killed and becoming a real thing. Most of the iSchools have been successful with that. The second is starting now, what does iSchool do beyond be a weak computer science program.
Aspray:
(01:37:43)
Right.
King:
(01:37:45)
It's a serious problem. Students want a job and perceive that computer science will give them that.
Aspray:
(01:38:02)
Right. Well, states and local communities are increasingly de-professionalizing library positions. [They say,] why do we need to hire somebody who has a degree in library science, a master's degree, why can't we just hire somebody smart that got a high school or college education? And so this undermines, the theme of we are here as a state institution to train that group of professionals, professional librarians. Do you see this threat as one that will end up driving the library scientists out of the information schools?
King:
(01:38:59)
One of my laments from my time as Dean of the School of Information at the University of Michigan was that I didn't come up with arguments to preserve the Library and Information Science focus. Many people from this field don’t want to give up ground they worked hard to get. The idea of requiring masters degrees to hold professional jobs is over, especially if it means master's degrees that pay bachelor's wages.
Aspray:
(01:41:37)
Yes.
King:
(01:41:38)
I would like to see kick-ass library bachelor's programs and the libraries come around.
Willi[am Aspray (01:42:15)
Right.
John King: I would say, there's another element to this. There is this culture and memory portion that needs to go into doctoral education into research. And there needs to be a way for this group of people to show their worth in those enterprises. In our program two areas stand out: data science and UX. I've asked that doctoral students, why do we need UX?
Aspray:
(01:43:37)
Yes.
King:
(01:43:38)
We have UX because the systems as they're deployed are bad for users. Maybe it's hard to build systems that are good for users. Or maybe we intend to build systems that are good for users, but we don't -- something gets in the way. Many seem to think UX important because with it they can get a job.
Aspray:
(01:44:36)
Right. I'm mindful of our time. We've been on this call for almost two hours. Do you want to go on, do you want to stop now? What's your preference?
King:
(01:45:04)
I'm happy to do some more of this if that's useful. You know what you're looking for, better than I know what you're looking for.
Aspray:
(01:45:29)
I think that I'd like to stop now because I can't ask as focused a set of questions as I would like to.
King:
(01:45:42)
Okay.
Aspray:
(01:45:42)
And I'll think about whether we should do this again.
King:
(01:45:52)
I am glad to hear that you're thinking about this. I think there's a really interesting and important story there. Not only is it a timely story now, but I think it's a story that will stand the test of time. To me it comes down to the existential question, is this thing involving information as big in the course of human evolution, as it seems to be? To my thinking the answer is yeah, but the explanation as to why doesn't work very well.
Aspray:
(01:47:24)
Right.
King:
(01:47:26)
I went to an IEEE conference and talked to an IEEE member in 2016 who was scandalized that I had serious doubts about whether autonomous vehicles would be ubiquitous by 2021. He responded that people in urban planning departments are already planning on this. People in urban planning departments plan for all kinds of stuff.
Aspray:
(01:48:33)
Right.
King:
(01:48:34)
This guy didn't know zip about government. Most people in urban planning are demoralized because they thought they were going to shape the built environment, not issue permits.
Aspray:
(01:49:03)
Right.
King:
(01:49:05)
They get on a high horse about autonomous vehicles, because this is liberating, but it’s got nothing to do with reality.
END OF SESSION
