“The Psychology of Design”

22 Wednesday Jul 2026

Posted by petersironwood in creativity, design rationale, HCI, management, politics, psychology, science, Uncategorized, user experience

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AI, creativity, Design, education, HCI, human factors, IBM, leadership, research, technology, UX

“The Psychology of Design”

I worked at IBM, all told, about 28 years. During that time, management put increasing pressure on us to make our work “relevant” to the business. In fact, the pressure was always there, even from the beginning. Over the years, however, we were “encouraged” to shorten evermore the time gap between doing the research and having the results of that research impact the bottom line. This was not an IBM-only phenomenon.

I was a researcher, not a politician, but it seemed to me that at the same time researchers in industrial labs were put under pressure to produce results that could be seen in terms of share price (and therefore payouts to executives in terms of stock options), academia was also experiencing more and more pressure to publish more studies more quickly — and to make sure “intellectual property” was protected to make sure the university could monetize your work. This was about the same time that, at least in America, increasing productivity and the wealth that sprung from that increased productivity stopped being shared between the workers and the owners.

In the late 1970’s, the “Behavioral Sciences” group at IBM Research began to study the “psychology of design.” For the first few months, this was an extremely pleasurable & productive group, due mainly to my colleagues. Over the next few blogs, I’ll focus on some specific techniques and methods that you may find useful in your own work.

In this short recounting though, I want to focus instead on some broader issues relevant to “technology transfer”, “leadership” and “management.” Even if you are or aspire to be an expert in UX or HCI or design, I assure you that these broader issues will impact you, your work and your career. I wouldn’t suggest becoming obsessed with them, but being aware of their potential impact could help you in your own work and career.

It is telling that, almost invariably, whenever I told someone inside IBM (or, for that matter, outside IBM) that I was studying the “psychology of design,” people responded by asking, “the design of what?” So, I would explain that we were interested in the generic processes of design and how to improve them. I would explain that we were interested in understanding, predicting, and controlling these processes to enable them to be more effective. I would explain that we could apply these findings to any kind of design: software design, hardware design, organizational design, and (see last post about IBM) communication design. I would explain that design was a quintessentially human activity. I would also explain that design was an incredibly leveraged activity to improve.

Looking back on it, I still think all these things are true. I also see that I missed the “signal” people were giving me that, while I thought of design as something that could be studied as a process, that most people did not think of it that way. To them, it was never the “psychology of design,” but only the design of something.

Don’t get me wrong. I agree that somewhat different skills are involved in designing a great advertising campaign, a great building, and a great application. I agree that different communities of practice treat various common issues differently. I still think it’s worth studying commonalities across domains. For one thing, we may find an excellent way of generating ideas, say, that the advertising community of practice uses that neither architects nor applications developers had ever tried. Or, vice versa.

My own academic background was in “Experimental Psychology.” We were forever doing experiments that we believed were about psychological processes that were thought to be invariant regardless of the domain. It was an axiom of our whole enterprise that studying memory for any one thing also shed light on how we remember every other thing. Similar studies looked at decision making or problem solving or multi-tasking. We came to understand that there were some interesting exceptions to being able to separate content from process. For instance, it is much easier to multi-task a spatial task and a verbal task than it is to multi-task two independent spatial tasks or two independent verbal tasks.

In our Behavioral Sciences lab, we used a spectrum of techniques to study “design” ranging from laboratory studies of toy problems, to observing people doing real-world design problems while thinking aloud. After about 3-4 months of very productive work, we were told that we had to make our work relevant to software development. That one domain should be the focus of our work. We were told that this command came from higher-ups in IBM. That might have been true, or perhaps partly true.

It might also be relevant that someone in our management chain might have been the recipient of a grant from ONR which was specifically focused on software development. So far as I can tell, nothing had been done on that grant. So, our past, present, and future work could have been co-opted to be “results” done under the auspices of the ONR grant.

In any case, regardless of the “reasons,” the group began to focus specifically on software design. In one study, we used IBM software experts as subjects. Each person was given information that was geared toward a specific transformation that occurred in software development. One person was presented with the description of a “situation” that included a number of “issues” and they were asked to write a requirements document. In real life, I would hope that this would be done in a dialogue (and, indeed, in other studies, we recorded such dialogues). Absent such dialogues, what we found was that different software experts — all from IBM research — and all given the same documentation about a set of problems generated vastly different problem statements and overall approaches.

In other parts of the study, other experts were variously given requirements documents and asked to do an overall, high level system design, or given a high level design and asked to design an algorithm, or given an algorithm and asked to code a section. There was always diversity but the initial phases showed the greatest diversity of behavior. The initial stage is also the one that can cause the most expensive errors. If you begin with a faulty set of requirements — a misreading about how to even go about the problem — then, the overall project is almost certain to incur schedule slip, cost overruns, or outright failure.

While the vital importance of the initial stages of design is true in software development, I would argue that it is likely also true for advertising campaigns, building designs — and even true for the design of research programs. We designed our research agenda under the assumption that we had a long time; that we were studying design processes independently of specific communities of practice or the nature of the problems people were attempting to address. We assumed that there was no “hidden agenda.” Although we believed we would eventually need to show some relevance to IBM business, we had no idea, when we began, that only relevance to software design would be “counted.”

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Some of our studies on the “Psychology of Design.”

Carroll, J. and Thomas, J.C. (1982). Metaphor and the cognitive representation of computer systems. IEEE Transactions on Man, Systems, and Cybernetics., SMC-12 (2), pp. 107-116.

Thomas, J.C. and Carroll, J. (1981). Human factors in communication. IBM Systems Journal, 20 (2), pp. 237-263.

Thomas, J.C. (1980). The computer as an active communication medium. Invited paper, Association for Computational Linguistics, Philadelphia, June 1980. Proceedings of the 18th Annual Meeting of the Association for Computational Linguistics., pp. 83-86.

Malhotra, A., Thomas, J.C. and Miller, L. (1980). Cognitive processes in design. International Journal of Man-Machine Studies, 12, pp. 119-140.

Carroll, J., Thomas, J.C. and Malhotra, A. (1980). Presentation and representation in design problem solving. British Journal of Psychology/,71 (1), pp. 143-155.

Carroll, J., Thomas, J.C. and Malhotra, A. (1979). A clinical-experimental analysis of design problem solving. Design Studies, 1 (2), pp. 84-92.

Thomas, J.C. (1978). A design-interpretation analysis of natural English. International Journal of Man-Machine Studies, 10, pp. 651-668.

Thomas, J.C. and Carroll, J. (1978). The psychological study of design. Design Studies, 1 (1), pp. 5-11.

Miller, L.A. and Thomas, J.C. (1977). Behavioral issues in the use of interactive systems: Part I. General issues. International Journal of Man-Machine Studies, 9 (5), pp. 509-536.

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Blog posts about the importance of solving the “right” problem.

The Doorbell’s Ringing. Can you get it?

https://petersironwood.com/2021/01/13/reframing-the-problem-paperwork-working-paper/

Problem Framing. Good Point.

https://petersironwood.com/2021/01/16/i-say-hello-you-say-what-city-please/

Problem formulation: Who knows what.

How to frame your own hamster wheel.

The slow seeming snapping turtle.

Author Page on Amazon.

Design – Interpretation Model of Communication

16 Thursday Jul 2026

Posted by petersironwood in AI, creativity, design rationale, HCI, leadership, politics, psychology, Uncategorized, user experience

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communication, deception, experiment, HCI, IBM, life, media, psychology, relationships, truth, UX, writing

In my early days at IBM Research (1970’s), we were focused on trying to develop, test, or at least conceive of ways that a larger proportion of people would be able to use computers. One of the major ways of thinking about this was to use natural language communication as a model. After all, it was reasoned, people were able to communicate with each other using natural language. This meant that it was possible, at least in principle. Moreover, most people had considerable practice communicating using natural language.

One popular way of looking at natural language (especially among engineers & computer scientists) was essentially an “Encoding – Decoding” model. I have something in my head that I wish to communicate to you. So, I “encode” my mental model, procedure, fact, etc. into language. I transmit that language to you. Then, you “decode” what I said into your internal language and — voila! — if all goes well, you construct something in your head that is much like what is in my head. Problem solved.

Of course, people who wrote about communication from this standpoint acknowledged that it didn’t always work. For instance, as speaker, I might do a bad job of “encoding” my knowledge. Or, I might do a good job of encoding, but the “transmission” was bad; e.g., static, gaps, noise, etc. might distort the signal. And, you might do a bad job of decoding. It’s an appealing model and helped engineers and computer scientists make advances in “communication theory” and helped make practical improvements in coding and so on.

As a general theory of how humans communicate, however, that notion is vastly over-simplified. I argued then that a better way of looking at human communication was as a design-interpretation process, not as an encoding-decoding process. One of the examples that pointed this out was a simple observation by Don Norman. Suppose someone comes up to you and asks, “Where is the Empire State Building?” You will normally give a quite different answer depending on whether the two of you are in Rome, Long Island, or Manhattan. In Rome, you might say, “It’s in America.” Or, you might say, “It’s in New York City.” If you are on Long Island, you might well say, “It’s in Manhattan.” If you are already in Manhattan, you might say, “Fifth Avenue, between 33rd and 34th.”

Building on Don Norman’s original example, but based on your own experience, you can easily see that it isn’t only the geographical relationships that influence your answer. If you were originally from Boston, now on your own in Rome, struggling with Italian and homesick and someone came up to you and asked that question in American English with a Boston Accent, your response might be: “Are you joking? But how did you know I was an American. My name’s … “

On the other hand, if you’re a 13-year old boy in Manhattan — one with a mean streak — and someone asks you this question in broken English and they’re looking around like they are totally lost, you might say, “Oh, no problem. Just follow 8th Avenue, all the way north up to 133rd. It’s right there. You can’t miss it.” (Note to potential foreign visitors, most kids in Manhattan would not intentionally mislead you. But they point is, someone could. They are not engaging some automatic encoding process that takes their knowledge and translates into English. Absurd!

You design every communication. I think that’s a much more useful way to conceive of communicating. Yes, of course, there are occasions when your “design” behavior is extremely rudimentary and seems almost automatic. It isn’t though. It just seems that way. Let’s go back to our question-asking example. Suppose you work at an information booth in New York City. People ask you this same question day after day, year after year. You’re seemingly giving the answer without any attention whatsoever. Suppose someone asks you the question, but with a preface. “Look here, chap! I’ve got a gun! And if you give me the same stupid answer you’ve given me every time before, I’ll shoot your bloody brains out!” You are going to modify your answer. It only seemed as though it was automatic.

When you design your answer you take into account at least these things: some knowledge that you communication about, the current context (which itself has hundreds of potentially important variables), a model of the person you’re creating this communication for, a set of goals that you are trying to achieve (e.g., get them safely to their goal, mislead them, entertain them, entertain yourself, entertain the people around you, demonstrate your expertise, practice your diction, etc.). The process is inherently creative. In many circumstances (writing, playing, exploring, discovering, partying), you can choose how creative you want to make it. In other cases, circumstances constrain you more (though likely not so much as you think they do).

Many readers think this is a classic example of a straw man argument. “No-one believes communication is a coding-decoding process.”

Well, I beg to differ. I worked for relatively well-managed companies. I’ve talked to many other people who have worked in different well-managed companies. We’ve all seen or heard requests like this: “I need a paragraph (or a slide or a foil) on speech recognition. Thanks.”

What??

Who’s the audience? Are they scientists, investors, customers, our management? How much do they already know? What are your goals? What other things are you going to talk about with them? The people who have left me such messages were all smart people. And, providing the necessary info would have only taken a minute or two. But it would have substantially improved the outcome. It’s not a straw man argument.

Sit-com plots often hinge on the characters doing poorly at designing and/or interpreting communications. A show based on encoding-decoding? No. What could be funny — indeed what often is shown in comedy — are people failing to do good design and in the extreme case, that can arise by having an actual robot as a character or someone who behaves like one.

People also interpret what was said in terms of their goals, the context, what they believe about your goals and capacity, what they already know, and so on. And, even though this may seem obvious, millions of people believe what advertisers or politicians say without questioning their motives, double-checking with other sources, or even looking for internal inconsistencies in what is being touted as true. In other cases though, the same people will not believe anything the “other side” says no matter what. Just as one can do faulty design, one can also do faulty interpretation.

In any case, I decided that it would be good to “show” in a controlled laboratory setting that the Encoding-Decoding model was woefully inadequate. So, I brought in “subjects” to work in pairs at a simple task about communicating Venn diagram relationships. The “designer” had a Venn diagram in front of them. “The “interpreter” was supposed to draw a Venn diagram. The “designer” was constrained to say something true and relevant. In addition to a “base” pay, the “interpreter” subjects would be given a bonus according to how many relationships matched those of the “designer.” The designer’s bonus depended on condition. In the “cooperation” condition, their payoff would also, like the interpreter’s, be determined by how much agreement was shown in the two diagrams. In the “competition” condition, the designer’s bonus depended on how different the two diagrams were.

Photo by August de Richelieu on Pexels.com

I ran about half the number of subjects I had planned to run when the experiment was ended by corporate lawyers.

What?

IBM had no unions at that time. And, they didn’t want any unions. One of their policies, which they believed would help them prevent the formation of unions was that they never paid their workers for piece-work. Apparently, somehow, IBM CHQ had gotten wind of my experiment. People were being paid different amounts, based (partly) on their performance. They couldn’t have this! People might think were paying people for piece-work!

It hardly needs to said, I suppose, that IBM definitely tried to pay for performance. This was true in sales, research, development, HR, management, and so on. No-one in IBM would argue that your pay shouldn’t be related to your performance. That was exactly — in one way of describing it — was going on here. By the way, these were not IBM employees and each subject only “worked” for about an hour.

Basically, regardless of how irrelevant this experimental set-up might have been to the genuine concern of unions not to pay people in an insanely aggressive and ever-changing piece-work scheme, the lawyers were concerned that it would be somehow misrepresented to workers or in the press and used as evidence that IBM should unionize. In a way, the lawyers were proving the point of the experiment in their own real-life behavior even as they insisted that the experiment needed to be shut down.

Lessons Learned: #1 Corporate lawyers are not only concerned about what you actually do or how you represent your work; they are also worried about how someone might misrepresent your work.

Lessons Learned: #2 Even when constrained to say something true and relevant, ordinary people are quite capable of misleading someone else when it’s to their benefit and considered okay to do.

It is this second aspect of the experiment that I myself felt to be “edgy” at the time. Sure, people can mislead, but I was providing a context in which they were being encouraged to mislead. Was that ethical? Obviously, I thought it was at the time. On reflection, I still think it’s okay, but I’m glad that there are now review boards to look at “studies” and give a less biased opinion than the person who designed the study would do.

I view the overall context of doing the study as positive. As adults, these people all already knew how to mislead. I was letting them, and many other people, know that we know you know how to mislead and we’ll be on the lookout for it.

What do other people think about studies wherein the experimenter encourages one person to deceive another?

2026 Update: I’ve spend a fair amount of time recently “chatting” with ChatGPT and with Claude. It’s clear that the implementers of these systems (or, at least some of them) were quite familiar with the idea of designing and interpreting text. Claude, in particular, seems like a “nice guy” and an honest one at that. It acknowledges some of its own limitations and often praises the questioner. This shouldn’t come as a complete shock. After all, good sales people and advertisers have relied for centuries on “Design and Interpretation.” Nonetheless, I sometimes wonder whether AI systems might be more ethically employed if they were operating on principles closer to “Coding and Decoding.” What do you think?

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References published literature that describes some of the research that was done around that time.

Malhotra, A., Thomas, J.C. and Miller, L. (1980). Cognitive processes in design. International Journal of Man-Machine Studies, 12, pp. 119-140.

Carroll, J., Thomas, J.C. and Malhotra, A. (1980). Presentation and representation in design problem solving. British Journal of Psychology/,71 (1), pp. 143-155.

Carroll, J., Thomas, J.C. and Malhotra, A. (1979). A clinical-experimental analysis of design problem solving. Design Studies, 1 (2), pp. 84-92.

Thomas, J.C. (1978). A design-interpretation analysis of natural English. International Journal of Man-Machine Studies, 10, pp. 651-668.

Thomas, J.C. and Carroll, J. (1978). The psychological study of design. Design Studies, 1 (1), pp. 5-11.

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Other essays that touch on communication.

Freedom of Speech is not a License to Kill

Ohayogozaimasu

The Sound of One Hand Clasping

Fool Me

Claude the Radioman

Know What?

The Story of Story, Part 1

The Temperature Gauge

The Destruction of Natural Intelligence

A Little is not a Lot

Try the Truth

Stoned Soup

Turing’s Nightmares

“Wizard of Oz”

15 Wednesday Jul 2026

Posted by petersironwood in AI, apocalypse, design rationale, HCI, leadership, management, politics, psychology, The Singularity, Uncategorized, user experience

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AI, HCI, IBM, research, technology, usability, UX, Wizard of Oz, writing

(Some Lessons Learned from studies in Human-Computer Interaction/User Experience conducted at IBM Research in the mid-70’s.)

Wizard of Oz

One of the studies I conducted at IBM Research in the mid 1970’s was part of an effort to do “Automatic Programming” — a department under Pat Goldberg. The first level manager I worked with was Irving Wladawsky (later Irving Wladawsky-Berger). His group wanted to develop a system that would allow the owner/operator of a small business to type requirements into a computer in English (or something English-like) and have the system itself produce RPG code to run the business so described.

The underlying motivation from an IBM business perspective was that many small businesses could well afford a computer to do inventory, fulfill orders, etc. but they couldn’t afford to hire programmers to create such a system from scratch. The small business owner in the mid-1970’s did not program! Yet, for the most part, they understood how their business worked. The notion was that a natural language understanding and generation program could dialogue with the user/owner and through that process, understand their “business rules.” No costly programmers needed!

An interesting side note: at that time, we were told that IBM corporate forbade us to use the terms “Artificial Intelligence” or “Robotics” to describe our work because some PR firm had determined that these terms were too scary for the general public. So, IBM had research in “mechanical assembly” but not “robotics.” We had work in character recognition, speech recognition, handwriting recognition, automatic program generation, and compiler optimization. But no work in “Artificial Intelligence.” (Wink, wink, nod, nod).

Labelism: Confusing a thing with the label for that thing.

Another interesting side note: I worked at IBM Research for a dozen years; started an AI lab at NYNEX where I worked another 13 years; came back to IBM Research and several years later found myself working on the same problem! We were still trying to make a system to allow small businesses to generate their code automatically. In my second iteration, rather than using natural language, we were trying to make the specification of business rules in a graph language that was intuitive enough for business owners. This was a different approach, but trying to address the same underlying desire: to bring computing to small business without incurring the heavy costs of programming and maintenance.

Let’s return to iteration one — the natural language approach @ 1975. Well, one issue was that no-one had a natural language program that even approximated being able to do the job. So…how to study people’s interaction with a system that doesn’t exist?

We used an approach that my colleague Jeff Kelly called the “Wizard of Oz” technique; viz., use a human being (in this case, me) to simulate how the system might work and record people’s behavior. In this way, we could discover many of the issues that such a natural language programming system would have to deal with. I had already had plenty of experience interacting with a computer; and I had acting experience. I could “play the part” of a computer fairly well as I typed in my questions and answers.

(Description of “The Wizard of Oz” technique).

IBM Research in Yorktown had roughly a thousand people including not only scientists, programmers, and engineers but also a number of business people (who did not know how to program). I knew some of them from playing tennis and table tennis and we used those folks as initial subjects. What did I find? Good news and bad news.

Dealing with natural language is tricky for many reasons. One of those reasons is that English, including the English that people normally use to describe their business, is filled with words that have multiple meanings; e.g., “file”, “run”, “program”, “object”, “table”, etc. But here is the good news: although it’s true that many English words have many meanings, when these business people described business procedures, almost all of the lexical ambiguity vanished! The program to understand business English would not have to distinguish between a business file and a nail file; it wouldn’t have to worry about distinguishing a run in baseball or a run in stockings from a run of the payroll program; it wouldn’t have to distinguish between the table in a relational data base and the table in your dining room. The domain would mainly constrain! That’s the good news.

The bad news was dialogue management. How can the machine recognize a misunderstanding and how can it correct it? To make matters worse, while business people were fairly consistent in the way they described how their business ran, they were not consistent in how they talked about the communication. If a human being senses that another one is misunderstanding, then, depending on context they might: raise their eyebrows, say “Huh?”, “Come again?”, “What?” “I think I lost you.” “WTF?” “Are you kidding?”, “We’re on different wavelengths,” “I don’t get it.” “But…wait.”

Sometimes, these are referred to as “meta-comments.” Here’s a simple example that took place in the study.

One of the business people told me about various discounts. I had assumed (playing the part of the computer) that he was talking about discounts for items that were being discounted due to inventory management. I recorded all the various percentages and so on. Then, he said, “Now, we also give discounts for various items.”

At that time, most natural language systems of that era simply ignored words like “now” and “also” in this context. Stepping out of my role as a “computer system” and thinking about from the perspective of a human conversational partner though, these words are crucial! What it signals is a change in topic. In the larger context of our conversation, it shows that everything that had just been said, which I thought had been about item discounts, was not about item discounts!

This is just one example, but there were many more. In my more recent experience interacting with various computer dialogue systems, being able to recognize the signals of miscommunication and being able to repair misunderstandings is still not very well-handled more than four decades later.

I’d be interested in any pointers you have to a system that you think deals with meta-communication in a natural and robust manner. I do not think that it is beyond the pale of possibility. The general categories of the ways that people misunderstand each other is not infinite. John Anderson developed excellent tutoring systems for LISP and geometry and those systems worked something like human tutors in that, the tutor inferred the mental model of an individual student and focused instruction on correcting any misconceptions. My intuition is that a generic system built with equal complexity could deal with most of the issues as well as the average human being deals with them; i.e., imperfectly.

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Lessons Learned: #1 You can test aspects of a system even before it’s built or even completely defined. One method that has been used many times: “Wizard of Oz.”

Lessons Learned #2: Language used by professionals to talk about their domain is much more constrained in terms of lexical ambiguity than is language when considered by all native speakers.

Lessons Learned #3: People in “our culture” (i.e., US business culture) do not have an agreed upon and consistent vocabulary for talking about communication nor a consistent process for dealing with them.

Lessons Learned #4: Speaking of communication errors, I don’t recall why, but it was about this time, that I realized that my notion about how research results would be transferred to other parts of IBM was a complete and utter fantasy. I hadn’t articulated it, but it was basically that I would do research, write the results up for publication in scientific journals for an academic audience and publish Research Reports which would be eagerly consumed by anyone who needed to know. I’m not proud of this. LOL. But that’s really kind of how I viewed it. And, then, after a few years, I realized that it really mainly came about through relationships. That was something that people had been showing me all my life, but which I don’t think anyone ever stated it explicitly enough.

Update for 2026: While the four “Lessons Learned” above still seem apropos, some of today’s chatbots such as ChatGPT and Claude are much better at dealing with connected conversations with humans that were the systems of the twentieth century. Not only that, people are now describing systems in “natural language” and the computer is writing code. That’s the “good news” I suppose.

The bad news? While my impression of most of the AI researchers of the twentieth century is that they were largely motivated by intellectual challenges and a desire to help make people more productive, I get the impression that most of the AI work of today is controlled by people who are already astoundingly wealthy and want to become even wealthier. And, as UN-laudable as we may view that goal, the wealth is only a means to an end and that end is the total enslavement of most of humanity. Even being a trillionaire isn’t enough.

That’s not to say that all the workers advancing AI have those nefarious aims just because those in charge do, but as the surveillance state becomes more pervasive, their private motivations could have less influence over the outcomes.

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Author Page on Amazon

The Myths of the Veritas (an exploration of leadership & ethics in free, no ads fiction)

Index to a Pattern Language for Collaboration and Teamwork

Experiences in Human-Computer Interaction

Post on “The Story of Story”

The After Times

After All

When Greed is the only Creed

Destroying Natural Intelligence

“Turing’s Nightmares” comprises 23 Sci-Fi short stories that explore the implications and ethics of AI

Here is an example chapter from “Turing’s Nightmares” that explores a possible dilemma of working in AI.

To Be or Not To Be

Madison Keys, Francis Scott Key, the “Prevent Defense” and giving away the Keys to the Kingdom.

12 Friday Dec 2025

Posted by petersironwood in America, family, management, psychology, sports, Uncategorized

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art, books, bravery, Business, career, choice, courage, HCI, human factors, IBM, life, school, sports, technology, Travel, UX

Madison Keys, Francis Scott Key, the “Prevent Defense” and giving away the Keys to the Kingdom.

Madison Keys, for those who don’t know, is an up-and-coming American tennis player. In Friday’s Wimbledon match of July, 2018, Madison sprinted to an early 4-1 lead. She accomplished this through a combination of ace serves and torrid ground strokes. Then, in an attempt to consolidate, or protect her lead, or play the (in)famous “prevent defense” imported from losing football coaches, she managed to stop hitting through the ball – guiding it carefully instead — into the net or well long or just inches wide.

Please understand that Madison Keys is a wonderful tennis player. And, her “retreat” to being “careful” and playing the “prevent defense” is a common error that both professional and amateur players fall prey to. It should also be pointed out that what appears to be overly conservative play to me, as an outside observer, could easily be due to some other cause such as a slight injury or, even more likely, because her opponent adjusted to Madison’s game. Whether or not she lost because of using the “prevent defense” no-one can say for sure. But I can say with certainty that many people in many sports have lost precisely because they stopped trying to “win” and instead tried to protect their lead by being overly conservative; changing the approach that got them ahead.

Francis Scott Key, of course, wrote the words to the American National Anthem which ends on the phrase, “…the home of the brave.” Of course, every nation has stories of people behaving bravely and the United States of America is no exception. For the American colonies to rebel against the far superior naval and land forces (to say nothing of sheer wealth) of the British Empire certainly qualifies as “brave.”

In my reading of American history, one of our strengths has always been taking risks in doing things in new and different ways. In other words, one of our strengths has been being brave. Until now. Now, we seem in full retreat. We are plunging headlong into the losing “prevent defense” borrowed from American football.

American football can hardly be called a “gentle sport” – the risk of injury is ever present and now we know that even those who manage to escape broken legs and torn ligaments may suffer internal brain damage. But there is still the tendency of many coaches to play the “prevent defense.” In case you’re unfamiliar with American football, here is an illustration of the effect of the “prevent defense” on the score. A team plays a particular way for 3 quarters of the game and is ahead 42-21. If you’re a fan of linear extrapolation, you might expect that the final score might be something like 56-28. But coaches sometimes want to “make sure” they win so they play the “prevent defense” which basically means you let the other team make first down after first down and therefore keep possession of the ball and score, though somewhat slowly. The coach suddenly loses confidence in the method which has worked for 3/4 of the game. It is not at all unusual for the team who employs this “prevent defense” to lose; in this example, perhaps, 42-48. They “let” the other team get one first down after another.

Photo by Pixabay on Pexels.com

America has apparently decided, now, to play a “prevent defense.” Rather than being innovative and bold and embracing the challenges of new inventions and international competition, we instead want to “hold on to our lead” and introduce protective tariffs just as we did right before the Great Depression. Rather than accepting immigrants with different foods, customs, dress, languages, and religions — we are now going to “hold on to what we have” and try to prevent any further evolution. In the case of American football, the prevent defense sometimes works. In the case of past civilizations that tried to isolate themselves, it hasn’t and it won’t.

landscape photography of gray rock formation

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This is not to say that America (or any other country) should right now have “open borders” and let everyone in for every purpose. (Nor, by the way, has any politician of any party suggested that we do that). Nor should a tennis player hit every shot with all their might. Nor should a football team try the riskiest possible plays at every turn. All systems need to strike a balance between replicating what works–providing defense of what one has while also bravely exploring what is new and different. That is what nature does. Every generation “replicates” aspects of the previous generation but every generation also explores new directions. Life does this through sexual selection, mutation, and cross over.

This balance plays out in career as well. You need to decide for yourself how much and what kinds of risks to take. When I obtained my doctorate in experimental psychology, for example, it would have been relatively un-risky in many ways to get a tenure-track faculty position. Instead, I chose managing a research project on the psychology of aging at Harvard Med School. To be sure, this is far less than the risk that some people take when; e.g., joining “Doctors without borders” or sinking all their life savings (along with all the life savings of their friends and relatives) into a start-up.

At the time, I was married and had three small children. Under these circumstances, I would not have felt comfortable having no guaranteed income. On the other hand, I was quite confident that I could write a grant proposal to continue to get funded by “soft money.” Indeed, I did write such a proposal along with James Fozard and Nancy Waugh who were at once my colleagues, my bosses, and my mentors. Our grant proposal was not funded or rejected but “deferred” and then it was deferred again. At that point, only one month of funding remained before I would be out of a job. I began to look elsewhere. In retrospect, we all realized it would have been much wiser to have a series of overlapping grants so that all of our “funding eggs” were never in one “funding agency’s basket.”

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I began looking for other jobs and had a variety of offers from colleges, universities, and large companies. I chose IBM Research. As it turned out, by the way, our grant proposal was ultimately funded for three years, but we only found out after I had already committed to go to IBM. During this job search, I was struck by something else. My dissertation had been on problem solving but my “post-doc” was in the psychology of aging. So far as I could tell, this didn’t bother any of the interviewers in industry in the slightest. But it really freaked out some people in academia. It became clear that one was “expected” in academia, at least by many, that one would choose a specialty and stick with it. Perhaps, one need not do that during their entire academic career, but anything less than a decade smacked of dilettantism. At least, that was how it felt to me as an interviewee. By contrast, it didn’t bother the people who interviewed me at Ford or GM that I knew nothing more than the average person about cars and had never really thought about the human factors of automobiles.

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The industrial jobs paid more than the academic jobs and that played some part in my decision. The job at GM sounded particularly interesting. I would be “the” experimental psychologist in a small inter-disciplinary group of about ten people who were essentially tasked with trying to predict the future. The “team” included an economist, a mathematician, a social psychologist, and someone who looked for trends in word frequencies in newspapers. The year was 1973 and US auto companies were shocked and surprised to learn that their customers suddenly cared about gas mileage! These companies didn’t want to be shocked and surprised like that again. The assignment reminded me of Isaac Asimov’s fictional character in the Foundation Trilogy — Harry Seldon — who founded “psychohistory.” We had the chance to do it in “real life.” It sounded pretty exciting!

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On the other hand, cars seemed to me to be fundamentally an “old” technology while computers were the wave of the future. It also occurred to me that a group of ten people from quite different disciplines trying to predict the future might sound very cool to me and apparently to the current head of research at GM, but it might seem far more dispensable to the next head of research. The IBM problem that I was to solve was much more fundamental. IBM saw that the difficulty of using computers could be a limiting factor in their future growth. I had had enough experience with people — and with computers — to see this as a genuine and enduring problem for IBM (and other computer companies); not as a problem that was temporary (such as the “oil crisis” appeared to be in the early 70’s).

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There were a number of additional reasons I chose IBM. IBM Research’s population at the time showed far more diversity than that of the auto companies. None of them were very diverse when it came to male/female ratios. At least IBM Research did have people from many different countries working there and it probably helped their case that an IBM Researcher had just been awarded a Nobel Prize. Furthermore, the car company research buildings bored me; they were the typical rectangular prisms that characterize most of corporate America. In other words, they were nothing special. Aero Saarinen however, had designed the IBM Watson Research Lab. It sat like an alien black spaceship ready to launch humanity into a conceptual future. It was set like an onyx jewel atop the jade hills of Westchester.

I had mistakenly thought that because New York City was such a giant metropolis, everything north of “The City” (as locals call it) would be concrete and steel for a hundred miles. But no! Westchester was full of cut granite, rolling hills, public parks of forests marbled with stone walls and cooled by clear blue lakes. My commute turned out to be a twenty minute, trafficless drive through a magical countryside. By contrast, since Detroit car companies at that time held a lot of political power, there was no public transportation to speak of in the area. Everyone who worked at the car company headquarters spent at least an hour in bumper to bumper traffic going to work and another hour in bumper to bumper traffic heading back home. In terms of natural beauty, Warren Michigan just doesn’t compare with Yorktown Heights, NY. Yorktown Heights even smelled better. I came for my interview just as the leaves began painting their autumn rainbow palette. Even the roads in Westchester county seemed more creative. They wandered through the land as though illustrative of Brownian motion, while Detroit area roads were as imaginative as graph paper. Northern Westchester county sports many more houses now than it did when I moved there in late 1973, but you can still see the essential difference from these aerial photos.

YorktownHts-map

Warren-map

The IBM company itself struck me as classy. It wasn’t only the Research Center. Everything about the company stated “first class.” Don’t get me wrong. It wasn’t a trivial decision. After grad school in Ann Arbor, a job in Warren kept me in the neighborhood I was familiar with. A job at Ford or GM meant I could visit my family and friends in northern Ohio much more easily as well as my colleagues, friends and professors at the U of M. The offer from IBM felt to me like an offer from the New York Yankees. Of course, going to a top-notch team also meant more difficult competition from my peers. I was, in effect, setting myself up to go head to head with extremely well-educated and smart people from around the world.

You also need to understand that in 1973, I would be only the fourth Ph.D. psychologist in a building filled with physicists, mathematicians, computer scientists, engineers, and materials scientists. In other words, nearly all the researchers considered themselves to be “hard scientists” who delved in quantitative realms. This did not particularly bother me. At the time, I wanted very much to help evolve psychology to be more quantitative in its approach. And yet, there were some nagging doubts that perhaps I should have picked a less risky job in a psychology department.

The first week at IBM, my manager, John Gould introduced me to yet another guy named “John” — a physicist whose office was near mine on aisle 19. This guy had something like 100 patents. A few days later, I overheard one of that John’s younger colleagues in the hallway excitedly describing some new findings. Something like the following transpired:

“John! John! You can’t believe it! I just got these results! We’re at 6.2 x 10 ** 15th!”

His older colleague replied, “Really? Are you sure? 6.2 x 10 ** 15th?”

John’s younger colleague, still bubbling with enthusiasm: “Yes! Yes! That’s right. You know. Within three orders of magnitude one way or the other!”

I thought to myself, “three orders of magnitude one way or the other? I can manage that! Even in psychology!” I no longer suffered from “physics envy.” I felt a bit more confident in the correctness of my decision to jump into these waters which were awash with sharp-witted experts in the ‘hard’ sciences. It might be risky, but not absurdly risky.

person riding bike making trek on thin air

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Of course, your mileage may differ. You might be quite willing to take a much riskier path or a less risky one. Or, maybe the physical location or how much of a commute is of less interest to you than picking the job that most advances your career or pays the most salary. There’s nothing wrong with those choices. But note what you actually feel. Don’t optimize in a sequence of boxes. That is, you might decide that your career is more important than how long your commute is. Fair enough. But there are limits. Imagine two jobs that are extremely similar and one is most likely a little better for your career but you have to commute two hours each way versus 5 minutes for the one that’s not quite so good for your career. Which one would you pick?

In life beyond tennis and beyond football, one also has to realize that your assessment of risk is not necessarily your actual risk. Many people have chosen “sure” careers or “sure” work at an “old, reliable” company only to discover that the “sure thing” actually turned out to be a big risk. I recall, for example, reading an article in INC., magazine that two “sure fire” small businesses were videotape rental stores and video game arcades. Within a few years of that article, they were almost sure-fire losers. Remember Woolworths? Montgomery Ward?

At the time I joined IBM, it was a dominant force in the computer industry. But there are no guarantees — not in career choices, not in tennis strategy, not in football strategy, not in playing the “prevent defense” when it comes to America. The irony of trying too hard to “play it safe” is illustrated this short story about my neighbor from Akron:

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Wilbur’s Story

Wilbur’s dead. Died in Nam. And, the question I keep wanting to ask him is: “Did it help you face the real dangers? All those hours together we played soldier?”

Wilbur’s family moved next door from West Virginia when I was eleven. They were stupendously uneducated. Wilbur was my buddy though. We were rock-fighting the oaks of the forest when he tried to heave a huge toaster-oven sized rock over my head. Endless waiting in the Emergency Room. Stitches. My hair still doesn’t grow straight there. “Friendly fire.”

More often, we used wooden swords to slash our way through the blackberry and wild rose jungle of The Enemy; parry the blows of the wildly swinging grapevines; hide out in the hollow tree; launch the sudden ambush.

We matched strategy wits on the RISK board, on the chess board, plastic soldier set-ups. I always won. Still, Wilbur made me think — more than school ever did.

One day, for some stupid reason, he insisted on fighting me. I punched him once (truly lightly) on the nose. He bled. He fled crying home to mama. Wilbur couldn’t stand the sight of blood.

I guess you got your fill of that in Nam, Wilbur.

After two tours of dangerous jungle combat, he was finally to ship home, safe and sound, tour over — thank God!

He slipped on a bar of soap in the shower and smashed the back of his head on the cement floor.

Wilbur finally answers me across the years and miles: “So much for Danger, buddy,” he laughs, “Go for it!”

Thanks, Wilbur.

Thanks.

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—————————————-

And, no, I will not be giving away the keys to the kingdom. Your days of fighting for freedom may be over. Mine have barely begun.

Author Page on Amazon

Where does your loyalty lie?

Essays on America: The Game

The Three Blind Mice

Roar, Ocean, Roar

Stoned Soup

The First Ring of Empathy

Math Class: Who are you?

The Last Gleam of Twilight

The Impossible

Not-Separateness

24 Tuesday Aug 2021

Posted by petersironwood in Uncategorized

≈ 1 Comment

Tags

beauty, Design, ecology, GreenNewDeal, HCI, IBM, peace, TNOO, UI, usability, UX

Not-Separateness

It seems odd to specify a property of natural order in terms of what it is not. On the other hand, I cannot come up with a positive alternative that doesn’t bring other connotations with it. I think it’s related to “unified” or “integral” or “belonging” or “inter-related” but none of those seem quite so on the mark as does “Not-Separateness.”

Christopher Alexander’s degree from MIT was in architecture. Part of the reason he may have chosen this particular term is in reaction to some examples of architecture in which the architect seems to be in the business of constructing a building whose primary purpose is to make them famous regardless of what that building does to the neighborhood or the occupants.

Imagine Mr. Bigg designs a house that is a perfect black cube set on on vertex. In effect, this design says to me: “I am BIG. I am Mr. Bigg! I am a genius! You would have never been brilliant enough to design a house that is a cube on its vertex! You would have wasted your time and done something mundane like placed the cube on the ground on one of its faces. Anyone could think of that! But I put it on a vertex!” Indeed, we may easily imagine that he says words to this effect when his interview is reported on in the (mythical) architectural journal, Things that look different!

“Mr. Bigg, you made the Bigg House out of black steel and black glass. Some critics have argued that this doesn’t fit with the existing neighborhood of stone cottages with thatched roofs.”

“Of course, little minds will always criticize Bigg ideas.”

“Yes, yes. It also means that the construction costs of the house were quite high. And, the estimated costs of heating and cooling are much higher as well.”

“Nothing that a worthwhile (i.e., wealthy) client can’t afford.”

“Some have also argued that it is inconvenient for the occupants who have to walk up and down at a steep angle and that furniture such as dressers, tables, chairs, and beds do not accommodate well to the tilted walls.”

“Let me ask you aquestion. Would you have ever thought of putting a cube on its corner? No. I didn’t think so!”

Of course, this is exaggeration. But not much.

We would hope that User Experience designers take into account the users, their tasks, their contexts, and the way in which their designs interact with other related artifacts, people and processes. We would hope that applications and artifacts and services are all designed with the property of “Not-Separateness.”

In the early 1980’s, I worked in the IBM Office of the Chief Scientist. My main assignment was to get IBM to pay more attention to the usability of its products. As part of that process, I visited quite a few IBM development labs around the world and spoke to many development teams. On many of these visits, I was accompanied by the Chief Scientist, a brilliant physicist, who “got” usability.

On one occasion, we watched a new printing technology. Instead of printing out black printing on a white sheet of paper sized 8.5” x 11” or A4, this printout was of no standard size. The printing was black on a shiny silver sheet that curled severely. The Chief Scientist asked the head of the development team how they envisioned this being used.

Chief Scientist: “Once someone printed this out, what would they do with it?”

Answer: “Oh, anything they liked.”

Chief Scientist: “I mean, would people tape this into a notebook or paste it? Or would you imagine notebooks that would bind such paper?”

Answer: “It’s not up to me to decide how people would use it. Doesn’t it look cool?”

Another type of answer we heard more than once to the question, “How would this be used?”

— “Oh, it’s a (replacement/upgrade) for this other IBM product.”

“But who would use it and for what?”

“It has three main components. Would you like a description of the components?”

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Of course, there is a place for “playing around” with technology and thereby discovering things which someone else may find a use for. But in design and development of a product or service, having a clear notion of context of use and the users and tasks is fundamental. Of course, other users may appropriate a product or service for purposes beyond those envisioned by the original designers. That’s cool.

What’s not cool is designing a device that is to be used in the bright outdoor sunlight and then testing the display in a typical office environment. Have you ever run across something like that? I have.

A more subtle lack of contextualization in design occurs when the design team fails to realize how many interruptions happen to the user while they are trying to accomplish a single task with the new application. If you “test” the application while the user is in a quiet “usability lab” and can give your tasks their undivided attention, then necessitating them to remember the invisible internal state of “Insert” versus “Edit” mode may not be a big deal at all. They will simply remember. But in their office environment, they may be interrupted by a phone call, a message, or their boss entering their office and asking a series of detailed questions. If they now go back to the task at hand, there is about a 50-50 chance that they will correctly guess whether they are in “Edit” mode or “Insert” mode.

A design which shows the property of Not-Separateness is the natural result of a process which shows not-separateness. Here are a few common ways to help ensure the design process grows organically from the users and their goals & contexts.

* Put people on the design team who are familiar with the users, and/or their tasks, and/or their contexts.

* People on the design team observe people engaging in the relevant processes, whenever possible, not — or not only — in a “Usability Lab” but in the actual work environment.

Jointly develop a product or service with the group who will use the product or service.

Observe people actually using product P (or service S), version N so that version N+1 will be better attuned to the needs of the users.

Gather and understand feedback from service calls and help desks and customer complaints in order to improve over time.

There will be benefits to a company who takes such approaches beyond initial sales. If you’ve done any gardening, you will appreciate that the quality of the tomatoes you enjoy eating is related to the quality of the soil and the quality of the care you give the tomatoes. Similarly, a product or service that has the quality of Not-Separateness will not only be useful — users will fight to keep your product or service. It becomes integrated with the environment. To change the brand means that they will have to change the way they work; possibly even with whom they work. Not-Separateness is likely a path to what business people like to call a “Cash Cow.”

If you’ve ever walked through a neighborhood after a hurricane, you’ve likely seen many uprooted trees. When you look at the roots of an uprooted tree, what do you see? Of course, you see roots. But what else? You see rocks and soil all around and embedded into the roots. They are Not-Separate. In a hurricane, there are typically not only high winds. There is also a lot of rain. The trees are hit with a double whammy. The wind pushes the tree but the rain weakens the solid soil in which the tree is embedded. It is the combination that makes it very difficult for the tree to “hold on” and keep from falling over.

Living things, just like us, have a 4.5 billion year history of living. The living things adapt over time to their environment and they mold the environment to their needs. They are not separate. Flowers appeal to the insects who pollinate them. The insects who pollinate them are adapted to the characteristics of the flower. A horse adapts to their rider and the rider adapts to their horse. A product or service must have a design that serves the needs of its stakeholders. For a product or service to have maximum beauty, utility, and longevity, it must also have a way to adapt to the changing needs of the users and other stakeholders. At the same time, if the users and their organizations adapt to the product or service, then true Not-Separateness is achieved.

If you want to skimp on designing your product or service, you can make it more separate, more divorced from its context, its users, and its tasks. Of course, if you do that, you also make much easier for your users to abandon your product and switch to a new one.

Another way to think about this in terms of systems theory is where you draw the boundary. If you draw a sharp boundary around your product, you may find that, over time, your product becomes ever more peripheral to the community you’re trying to support and your product is ever more fungible with others in its class. On the other hand, if you draw the boundary around the product or service and the people and organizations who provide the product or service then, you are on the path of ever tighter interconnect.

Not-Separateness is not only a quality of good design in terms of not overly separating the context and users from the product or service. It is also a good quality for the organization that produces products & services. Of course, some people today must manage a giant amorphous “organization” of tens of thousands of people so they set up divisions, and departments, and groups, and teams, and positions etc. There may indeed be a “UX Department” and a “Software Department” and a “Hardware Department.” That’s all fine. But it is counter-productive if the UX Department sees itself as separate from the rest of the company. To a great extent the success of the UX Department depends on the success of the Hardware and Software Departments. The Sales Department’s success will, of course, depend partly on the skills of the Sales Department. But it will also depend on the success of the UX Department, HW, SW and Services.

Have you ever had a paper cut? It isn’t just the skin on a quarter inch of the inside of your ring finger that’s cut. You’re cut! It isn’t just that the finger feels pain. You feel pain! That causes you to take steps to ameliorate the pain and to try to make sure it doesn’t happen again. That’s why empathy in leadership is important. A leader must feel empathy for all, or the organization will disintegrate from lack of Not-Separateness. At some point, a raccoon may chew off its own arm in order to escape a trap.

But it isn’t the first thing that occurs to them every time they experience a thorn in the paw!

The raccoon doesn’t say to itself: — “that paw is giving me pain! I’m going to chew it off! Then, it won’t hurt any more.”

Evolution did not evolve a raccoon that acts that way. Self-mutilation exists but it is typically a last resort.

But not for corporations. It is the first thing they think of:

“Our (you name it) Department is not performing well. Let’s lay them off and outsource it.”

What does that say to every thinking employee in the entire corporation? It says:

“You know what? All this talk about teamwork and pulling together is a total bunch of bull$hit. You cannot trust management to do what’s best for everyone. You can only trust them to do what’s best for them.”

Living forms in nature are living forms. Their parts have severe Not-Separateness with the other parts of that form. Often, as in well-functioning families or teams, that extends to all members of the group.

Not-Separateness is essentially deep cooperation. I give to the larger community by becoming a part of it and doing my part in it. I lend strength to the community. In return, I gain strength from that community. It is not a zero sum game, of course. The community, if it is functional, is much stronger than the sum of the individuals in that community.

This is so deeply embedded in 4.5 billion years of evolution that it does not surprise me that we recognize beauty as being even more beautiful if it is not separate. Not-Separate enhances beauty because, like all the other properties, it is essential to life.

Eventually, if humanity is to survive, we will realize that Not-Separateness applies to all of us. We are not there yet. But that doesn’t mean we cannot appreciate and design Not Separateness in our products, in our services, and our lives.

—————-

The Declaration of Interdependence

How the Nightingale Learned to Sing

Roar, Ocean, Roar

Imagine all the people

Ripples

Author Page on Amazon

Thomas, J.C. and Kellogg, W.A. (1989). Minimizing ecological gaps in interface design, IEEE Software, January 1989.

Thomas, J. C. (2012). Patterns for emergent global intelligence. In Creativity and Rationale: Enhancing Human Experience By Design J. Carroll (Ed.), New York: Springer.

Thomas, J. C. (2001). An HCI Agenda for the Next Millennium: Emergent Global Intelligence. In R. Earnshaw, R. Guedj, A. van Dam, and J. Vince (Eds.), Frontiers of human-centered computing, online communities, and virtual environments. London: Springer-Verlag.

Thomas, J.C. (1985). Human factors in IBM. IBM Research Report. RC-11267. Yorktown Heights, NY: IBM Corporation.

“The Psychology of Design”

08 Thursday Jul 2021

Posted by petersironwood in Uncategorized

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Tags

creativity, Design, HCI, human factors, IBM, leadership, research, UX

“The Psychology of Design”

I worked at IBM, all told, about 28 years. During that time, management put more and more pressure on us to make our work “relevant” to the business. In fact, the pressure was always there, even from the beginning. Over the years, however, we were “encouraged” to shorten evermore the time gap between doing the research and having the results of that research impact the bottom line. This was not an IBM-only phenomenon.

In the late 1970’s, the “Behavioral Sciences” group began to study the “psychology of design.” For the first few months, this was an extremely pleasurable & productive group, due mainly to my colleagues. Over the next few blogs, I’ll focus on some specific techniques and methods that you may find useful in your own work.

In this short story though, I want to focus instead on some broader issues relevant to “technology transfer”, “leadership” and “management.” Even if you are or aspire to be an expert in UX or HCI or design, I assure you that these broader issues will impact you, your work and your career. I wouldn’t suggest becoming obsessed with them, but being aware of their potential impact could help you in your own work and career.

Don’t get me wrong. I agree that somewhat different skills are involved in designing a great advertising campaign, a great building, and a great application. I agree that different communities of practice treat various common issues differently. I still think it’s worth studying commonalities across domains. For one thing, we may find an excellent way of generating ideas, say, that the advertising community of practice uses that neither architects nor applications developers had ever tried. Or, vice versa.

My own academic background was in “Experimental Psychology.” We were forever doing experiments that we believed were about psychological processes that were thought to be invariant regardless of the domain. It was an axiom of our whole enterprise that studying memory for any one thing shed light on how we remember every other thing. Similar studies looked at decision making or problem solving or multi-tasking. We came to understand that there were some interesting exceptions to being able to separate content from process. For instance, it is much easier to multi-task a spatial task and a verbal task than it is to multi-task two independent spatial tasks or two independent verbal tasks.

We used a spectrum of techniques to study “design” from laboratory studies of toy problems, to observing people doing real-world design problems while thinking aloud. After about 3-4 months of very productive work, we were told that we had to make our work relevant to software development. That should be the focus of our work. We were told that this command came from higher-ups in IBM. That might have been true, or perhaps partly true.

In other parts of the study, other experts were variously given requirements documents and asked to do an overall, high level system design, or given a high level design and asked to design an algorithm, or given an algorithm and asked to code a section. There was always diversity but the initial showed the greatest diversity. The initial stage is also the one that can cause the most expensive errors. If you begin with a faulty set of requirements — a misreading about how to even go about the problem — then, the overall project is almost certain to incur schedule slip, cost overruns, or outright failure.