“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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“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.

Walston & Felix Multiple Regression Study

17 Friday Jul 2026

Posted by petersironwood in creativity, design rationale, leadership, management, psychology, Uncategorized

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art, books, development, HCI, IT, productivity, programming, regression, software, technology, UX, writing

As I mentioned recently, when I first arrived at IBM Research in the early 1970’s I began to work on Query By Example and other schemes to make it easier for non-programmers to interact productively but flexibly with computers. Some of the lessons learned have to do, not with my own work, but with the work of others.

At that time, some researchers labelled their work as “The Psychology of Programming.” There were many debates — and some studies — about structures, syntax, which language was better than others, etc. There were also lengthy discussions about the process that one should use for software development. Doing any kind of “controlled” experiment on large scale code development is prohibitively expensive. It is rare that a company is willing to have two independent teams build the same piece of software in order to learn which of two methods is “better.”

Of course, one such comparison would likely not prove much. It may be that one of the two teams had a “super-programmer” or an extremely good manager. Perhaps, flu broke out in one of the two teams. You would really need to study many more than two teams to properly and empirically study the impact of language, or syntax, or process. Doing reasonable-sized experiments would be far too costly and impractical. Our lab and others did do laboratory tasks in order to test one syntax variant against another and so on. The problems were generally quite small in order for the study to be practical. So, the applicability to real-world development projects was questionable.

Photo by Christina Morillo on Pexels.com

Walston & Felix (See below), on the other hand, were able to find data on a fair number of real-world projects and rather than try to control for languages, processes, etc., they did a multiple regression analysis based on what languages, methods, etc. real projects used and what the important predictors were of actual productivity.

Personally, I learned two lessons from their study.

Lessons Learned: #1 — Sometimes, when it comes to what matters in the real world, controlled laboratory experiments have to give way to other methods such as studying “natural experiments.” Despite the many issues with trying to interpret such findings, no-one will pay for massive controlled experiments that parametrically vary programming methods, programming languages, etc. while controlling for quality of management, experience, complexity of task, etc. Multiple regression studies and in-depth case studies; ethnographic studies; interviews: all of these can provide useful input.

Lessons Learned: #2 — The impact of the variables that our community of people were looking at in terms of syntax, structure, etc. were dwarfed by the impact of organizational variables. For example, Walston & Felix found that the complexity of the interface between the developers and the customers was extremely important.

DeMarco & Lister (See below) claim that, based on their decades of experience as consultants to the software development process, projects almost never fail for technical reasons; when they do fail, it’s almost always for organizational and management reasons.

That conclusion dovetails with my own experience. Many decades later, working for IBM in “knowledge management,” it was amazing how many companies wanted us to “solve” their knowledge management issues by building them a “system” for knowledge sharing.

But…

Management at the company would not provide:

Incentives to share knowledge

Space to share knowledge

Time to share knowledge

Or, commit any personnel to gathering, vetting, organizing, and promoting the knowledge repository.

So — knowledge sharing was something their workers were simply supposed to “do” knowledge sharing on top of everything else they were doing.

They did not want a computer system, IMHO; they wanted a magic system.

These experiences were part of my motivation for attempting to catalog “best practices” in collaboration and teamwork in the form of a Pattern Language. Christopher Alexander and his colleagues looked at “what worked” in various parts of the world when it came to architecture and city planning. What they did for architecture and city planning, I want to do for collaboration.

Naturally, merely creating a catalog is not sufficient. I need to have people who will read it, understand it, modify and improve it, and then promulgate it via actual use. For now, it’s free. Comments and critiques are always welcome.

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C. E. Walston and C. P. Felix, “A method of Programming Measurement and Estimation,” IBM Systems Journal, vol. 16, no. 1, pp. 54–73, 1977.

https://en.wikipedia.org/wiki/Peopleware:_Productive_Projects_and_Teams

Thomas, J.(2008). Fun at work: Managing HCI from a Peopleware perspective. HCI Remixed. D. McDonald & T. Erickson (Eds.), Cambridge, MA: MIT Press.

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Introduction to a Pattern Language for Collaboration and Teamwork

Index to a Pattern Language for Collaboration and Teamwork

Chain Saws Make the Best Hair Clippers

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

(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.

———————————-

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

Career Advice from Polonius

07 Tuesday Jul 2026

Posted by petersironwood in Uncategorized, psychology, creativity, essay, user experience

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human factors, UX, HCI, usability, learning, education, life, career, work, writing, mental-health

Career Advice from Polonius: To Thine Own Self be True

“To thine own self be true.” This advice comes from Polonius who is giving advice to his son in Act I, scene 3 of Shakespeare’s Hamlet.

Polonius says: “This above all: to thine own self be true. And it must follow, as the night the day, Thou canst not then be false to any man.”

Let’s focus on the first part.

One of the dreams of education is to customize teaching to the specific learning style(s) of individual students. This was a hot topic when I was in graduate school.

Around 50 years ago. And it still is.

Some day, your grandchildren or your great-grandchildren may be the beneficiaries of learning experiences that are individualized to their specific styles. I wouldn’t hold my breath, but it could happen. It isn’t only a question of research on what various styles are and how to present material that resonates with these various styles. There is also the question of priorities and dollars and personnel.

But meanwhile, here’s the good news. You don’t have to wait for another 50 years of research and a reshuffling of priorities so folx spend more money on education and less on, let’s say, cosmetics and professional sports. As I say, don’t hold your breath.

But let’s get back to the good news. The good news is that you can discover for yourself how to maximize your own learning as well as what your particular talents are.

One cautionary note: Don’t be a jerk about it. If you’re in a group dealing with grief, don’t say, “Well, I learn best if a subject is reduced to a few hundred polynomial formulae. So, let’s start right there. Let’s reduce grief to three dimensions. Later, of course, we can do a proper multidimensional scaling exercise to determine the optimal number of dimensions.”

Photo by Andrea Piacquadio on Pexels.com

No. Don’t say that. Of course, you’re free to suggest that approach, but chances are, in that situation, and in most realistic group situations, you will be treated to information in the same manner as many others who have different styles from yours.

However, in many situations, you are, far and away the main important stakeholder. You can use your knowledge of how things work for you in order to strategize and plan how you will learn about things. You can organize and arrange your work so you’ll be more productive.

Here’s a trivial example. I have learned that my eyes have a wisdom of their own. If, for instance, I’m going out for a walk around the garden to take some pictures of the sunset on the flowers, I grab my stuff and find myself turning and staring at the hat-rack on the way out the door. When I was younger, I would ignore this. But what I have learned is that my eyes are really good at knowing what to look at. So, even if I’m in a hurry, I take a moment to reflect on why my eyes are looking there. And, then, it comes to me. I’ll do better if I wear a brimmed hat to keep the sun out of my eyes while I look at my iPhone.

By paying attention to this little quirk, I’ve saved myself a lot of grief over the years; e.g., not left the house without my wallet, etc.

Here’s another example. I’m very good at seeing “patterns” emerge from a small number of examples or when there is considerable noise involved. This serves me well as my hearing diminishes because I can use top-down processing. Generally, but not always, I understand what people are saying. On the other hand, if I try to listen to a foreign language tape that is only isolated audio words, I have no hope of knowing what they are saying. “Key” “Tee”, “Pea”, sound exactly the same.

Seeing patterns easily is generally a nice capacity. However, I’m horrible at finding my own typos immediately after I write something. I actually “see” what I meant to type. A week later, I’m pretty good at catching the errors. If I had more patience, I would wait a week to proofread for every blog post, but being patient isn’t a strength of mine either. I do go back over old posts occasionally and fix the typos (which I never saw at the time).

When I go to the movies — remember when we used to go to movies? — anyway, if I went to a comedy, I was very likely to laugh too soon. I “hear” the punchline two lines earlier than it actually occurs. There’s no benefit to my laughing early! But that’s when the punchline hits me. I do keep it soft so as not to disturb the others in the audience. On the other hand, I’m pretty good at “discovering” the playing patterns of my tennis opponents and anticipating what they are going to do. Naturally, I don’t always guess right, but I do way better than chance.

I bring up these examples to illustrate a generality; that most of these individual differences have both an upside and a downside. Mainly, learning about my own styles and capacities is something I only began to think about well after leaving high school. That makes sense. In school — or at least, the schools I went to — everybody got the same instruction in the same way almost all the time. But as an adult, you often have a lot of control over your own timing, flow of information, etc. I think it’s worth your while to look back at your experience and discover what you have difficulty with, what you’re OK at and what you are exceptionally good at. When you have a choice, use the approach you’re really good at.

Oh, and try to avoid hiding behind curtains when there’s someone with a sword around.

—————————————-

More background on “knowing yourself”

https://en.wikipedia.org/wiki/Know_thyself

https://arkintime.com/know-thyself/history/

The Walkabout Diaries Natural Variety

Where do you draw the line

Your Cage is Unlocked

Abracadabra!

20 Tuesday Jan 2026

Posted by petersironwood in apocalypse, The Singularity, Uncategorized

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"Citizens United", AI, Artificial Intelligence, biotech, chatgpt, chess, cognitive computing, Democracy, emotional intelligence, ethics, HCI, life, prediction, psychokinesis, technology, the singularity, truth, Turing, USA, UX

Abracadabra!

Here’s the thing.

There is no magic.

Of course, there is the magic of love and the wonder at the universe and so there is metaphorical magic. But there is no physical magic and no mathematical magic. Why do we care? Because in most science fiction scenarios, when super-intelligence happens, whether it is artificial or humanoid, magic happens. Not only can the super-intelligent person or computer think more deeply and broadly, they also can start predicting the future, making objects move with their thoughts alone and so on. Unfortunately, it is not just in science fiction that one finds such impossibilities but also in the pitches of companies about biotech and the future of artificial intelligence. Now, don’t get me wrong. Of course, there are many awesome things in store for humanity in the coming millennia, most of which we cannot even anticipate. But the chances of “free unlimited energy” and a computer that will anticipate and meet our every need are slim indeed.

This all-too popular exaggeration is not terribly surprising. I am sure much of what I do seems quite magical to our cats. People in possession of advanced or different technology often seem “magical” to those with no familiarity with the technology. But please keep in mind that making a human brain “better”, whether by making it bigger, or have more connections, or making it faster —- none of these alterations will enable the brain to move objects via psychokinesis. Yes, the brain does produce a minuscule amount of electricity, but way too little to move mountains or freight trains.

Of course, machines can be built to wield a lot of physical energy, but it isn’t the information processing part of the system that directly causes something in the physical world. It is through actuators of some type, just as it is with animals. Of course, super-intelligence could make the world more efficient. It is also possible that super-intelligence might discover as yet undiscovered forces of the universe. If it turns out that our understanding of reality is rather fundamentally flawed, then all bets are off. For example, if it turns out that there are twelve fundamental forces in the universe (or, just one), and a super-intelligent system determines how to use them, it might be possible that there is potential energy already stored in matter which can be released by the slightest “twist” in some other dimension or using some as yet undiscovered force. This might appear to human beings who have never known about the other 8 forces let alone how to harness them as “magic.”

There is another more subtle kind of “magic” that might be called mathematical magic. As known for a long time, it is theoretically possible to play perfect chess by calculating all possible moves, and all possible responses to those moves, etc. to the final draws and checkmates. It has been calculated that such an enumberation of contingencies would not be possible even if the entire universe were a nano-computer operating in parallel since the beginning of time. There are many similar domains. Just because a person or computer is way, way smarter does not mean they will be able to calculate every possibility in a highly complex domain.

Of course, it is also possible that some domains might appear impossibly complex but actually be governed by a few simple, but extremely difficult to discover laws. For instance, it might turn out that one can calculate the precise value of a chess position (encapsulating all possible moves implicitly) through some as yet undiscovered algorithm written perhaps in an as yet undesigned language. It seems doubtful that this would be true of every domain, but it is hard to say a priori.

There is another aspect of unpredictability and that has to do with random and chaotic effects. Imagine trying to describe every single molecule of earth’s seas and atmosphere in terms of it’s motion and position. Even if there were some way to predict state N+1 from N, we would have to know everything about state N. The effects of the slightest miscalculation or missing piece of data could be amplified over time. So long term predictions of fundamentally chaotic systems like weather, or what your kids will be up to in 50 years, or what the stock market will be in 2600 are most likely impossible, not because our systems are not intelligent enough but because such systems are by their nature not predictable. In the short term, weather is largely, though not entirely, predictable. The same holds for what your kids will do tomorrow or, within limits, what the stock market will do. The ability to do long term prediction is quite different.

In The Sciences of the Artificial, Herb Simon provides a nice thought experiment about the temperature in various regions of a closed space. I am paraphrasing, but imagine a dormitory with four “quads.” Each quad has four rooms and each room is partitioned into four areas with screens. The screens are not very good insulators so if the temperature in these areas differ, they will quickly converge. In the longer run, the temperature will tend toward average in the entire quad. In the very long term, if no additional energy is added, the entire dormitory will tend toward the global average. So, when it comes to many kinds of interactions, nearby interactions dominate, but in the long term, more global forces come into play.

Now, let us take Simon’s simple example and consider what might happen in the real world. We want to predict what the temperature is in a particular partitioned area in 100 years. In reality, the dormitory is not a closed system. Someone may buy a space heater and continually keep their little area much warmer. Or, maybe that area has a window that faces south. But it gets worse. Much worse. We have no idea whether this particular dormitory will even exist in 100 years. It depends on fires, earthquakes, and the generosity of alumni. In fact, we don’t even know whether brick and mortar colleges in general will exist in 100 years. Because as we try to predict in longer and longer time frames, not only do more distant factors come into play in terms of physical distance. The determining factors are also distant conceptually. In a 100 year time frame, the entire college may or may not exist and we don’t even know whether the determining factor(s) will be financial, astronomical, geological, political, social, physical or what. This is not a problem that will be solved via “Artificial Intelligence” or by giving human beings “better brains” via biotech.

Whoa! Hold on there. Once again, it is possible that in some other dimension or using some other as yet undiscovered force, there is a law of conservation so that going “off track” in one direction causes forces to correct the imbalance and get back on track. It seems extremely unlikely, but it is conceivable that our model of how the universe works is missing some fundamental organizing principle and what appears to us as chaotic is actually not.

The scary part, at least to me, is that some descriptions of the wonderful world that awaits us (once our biotech or AI start-up is funded) is that that wonderful world depends on their being a much simpler, as yet unknown force or set of forces that is discoverable and completely unanticipated. Color me “doubting Thomas” on that one.

It isn’t just that investing in such a venture might be risky in terms of losing money. It is that we humans are subject to blind pride that makes people presume that they can predict what the impact of making a genetic change will be, not just on a particular species in the short term, but on the entire planet in the long run. We can indeed make small changes in both biotech and AI and see improvements in our lives. But when it comes to recreating dinosaurs in a real life Jurassic Park or replacing human psychotherapists with robotic ones, we really cannot predict what the net effect will be. As humans, we are certainly capable of containing and testing and imagining possibilities and slowly testing them as we introduce them. Yeah. That could happen. But…

What seems to actually happen, however, is that companies not only want to make more money; they want to make more money now. We have evolved social and legal and political systems that put almost no brakes on runaway greed. The result is that more than one drug has been put on the market that has had a net negative effect on human health. This is partly because long term effects are very hard to ascertain, but the bigger cause is unbridled greed. Corporations, like horses, are powerful things. You can ride farther and faster on a horse. And certainly corporations are powerful agents of change. But the wise rider is master or partner with a horse. They don’t allow themselves to be dragged along the ground by rope and let the horse go wherever it will. Sadly, that is precisely the position that society is vis a vis corporations. We let them determine the laws. We let them buy elections. We let them control virtually every news medium. We no longer use them to get amazing things done. We let them use us to get done what they want done. And what is that thing that they want done? Make hugely more money for a very few people. Despite this, most companies still manage to do a lot of net good in the world. I suspect this is because human beings are still needed for virtually every vital function in the corporation.

What will happen once the people in a corporation are no longer needed? What will happen when people who remain in a corporation are no longer people as we know them, but biologically altered? It is impossible to predict with certainty. But we can assume that it will seem to us very much like magic.

Very.

Dark.

Magic.

Abracadabra!

Turing’s Nightmares

After All

All Around the Mulberry Bush

All We Stand to Lose

The Crows and Me

The Last Gleam of Twilight

Guernica

The Orange Man

Donnie Visits Granny

The First Ring of Empathy

An Open Sore from Hell

The Impossible

How the Nightingale Learned to Sing

Pattern Language Summary

The Midnight Flight to Crazytown

To Be or Not to Be

Peace

Who Won the War?

We Won the War! We Won the War!

The Dance of Billions

At Least He’s Our Monster

Stoned Soup

Fifteen Properties

Tools of Thought: And then what?

The Walkabout Diaries: Sunsets

All that Glitters is not Gold

When Greed’s the Only Creed

The Self-Made Man

The Story of Story: Part 3

17 Saturday Jan 2026

Posted by petersironwood in creativity, essay, HCI, psychology, story, Uncategorized

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books, education, fiction, HCI, knowledge, leadership, learning, life, management, sense_making, story, Storytelling, thinking, truth, UX, writing

The Story of Story: Part 3 – Good Story, Well Told.

Often in my English classes, (and yours?) we talked about the mechanisms of writing: spelling, grammar, word usage, punctuation, paragraph construction, metaphor, rhythm, and rhyme scheme, for instance. We talked very little about how to tell a story well. And we talked zero about what makes for a good story.

In the last article, I described some guidelines for soliciting stories from users and other stakeholders. From these, one may gain insight into potential problems that a product or service might solve, ameliorate, bypass, or avoid. Later, I will describe more about how stories may be used in the design and development process. Before getting into that, however, I want to describe more about what makes for a good story. In the following articles, I will also suggest ways to make the story well told.

What Makes for a Good Story?

You might find it helpful to write down a short list of 5-10 novels, short stories, movies, or TV shows that you really liked. It doesn’t have to be your all time ten best; just something good that springs to mind. Then put that list aside. Read through the criteria I propose and then check back after you’re done reading to see whether or not most of these criteria were met. I’m betting that they mostly were met.

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The Story Cube.

Imagine a cube of some really nice material that you like; e.g., polished wood, lead ore, malachite, silver. This cube has three dimensions: height, width, and depth. It must have all three dimensions. In the case of a story, there are also three dimensions in this sense: Plot, Setting, and Character. If a story lacks any of these three, it will be “flat” (not so interesting). For example, if you spent time working in a large company or government agency, you were probably given training materials about how you’re not supposed to do unethical things like steal from your company. They may have provided you with scenarios and asked what you would do or what was the “right” response. These stories tend to have people in situations making decisions. The problem with these stories is that, in order for them to be “efficient”, they spend almost zero time on character development. “Joe wants to impress his boss and make his quota for the fourth quarter so he puts down as sold this-quarter things he is sure he will sell early in January. After all, he rationalizes, calendars are arbitrary.” Of course, the answer is no Joe should not be lying on his sales report. But we really don’t know much about Joe. We don’t know enough about him to really care much about him. Of course, he shouldn’t lie. If he does, it’s pretty hard to feel anything but contempt for Joe. It should have been obvious to him that he shouldn’t lie on a sales report and if he does lie, he should be fired. Good riddance. Let’s replace Joe with someone who follows the rules.

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This story is so flat that it seems to me that the story is constructed, not so much to really educate, but more to prove that you were shown that it’s wrong to lie on sales forms so that, should the court case arise, you will not be to argue effectively that it was a mere technicality that you didn’t know about. If you really wanted to change someone’s mind about what was right, knowing about Joe’s character could make you empathize much more. Maybe he came from a Mafia-type crime family and no-one would bat any eye about lying on a sales report. They would expect him to lie on the report. Maybe even now, he is looked down upon by everyone else in his family for being such a chump and working for “the man” instead of being “the man.”

OLYMPUS DIGITAL CAMERA

Or, perhaps Joe just found out that his wife has serious cancer and is understandably but severely depressed. He desperately wants to bring her some good news. If we reveal, not only what situation Joe is in but also, how he sees that situation, how he feels about it and what conflicts he faces, we will begin to have real empathy for Joe. His choices become real, rather than predetermined.

TV commercials, like corporate training videos, are typically pretty flat too. But in some cases, the ad agency has gone out of their way to introduce you to some character that is recognizable and re-appears in commercial after commercial. Each time, just a little bit of character is revealed and eventually you find yourself watching the commercial largely because you start to care about the character. In a similar way, one might be able to make the corporate training stories more intriguing & educational if there were a cast of characters that persisted over time.

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Two Paths Diverged in a Yellow Wood…

Typically (but not invariably) the author knows how the story will turn out before he starts writing. But for the reader (or viewer), it is not at all obvious how the story will turn out. For compelling stories, the reader must be convinced to “play along with” the uncertainty of the outcome even if they are sure ‘the good guys will win.’ In good stories, bad things happen to the protagonist, but he or she is not a cork tossed on the ocean waves. The protagonist must want something; they must have a goal that is overwhelmingly important to them. They must react to changing circumstances, overcome the obstacles that are thrown at them. Characters are engaged in battles! Battles test them. If winning the battles is easy or inevitable, the character isn’t someone we can really relate to.

catman

Kryptonite

Superman is basically super-human and invulnerable! But watching someone who is invulnerable and has super-powers win battle after battle is boring. Superman has to have weaknesses. To make it more interesting and allow for more plot variation, he actually had three original weaknesses: kryptonite, friends, secret identity. In one episode, someone will have some kryptonite while in the next, someone will kidnap one of his friends. Recent movies have added a fourth weakness: other super-human and invulnerable beings.

Whatever the story, your character must have weaknesses. Otherwise, no-one will “believe” the character and you as the writer will be stymied when you try to develop an interesting plot. The weaknesses can be physical, moral, social, intellectual, situational, and so on. But they should not be merely irrelevant weaknesses. Imagine a story where Sue is the main character. She’s tone deaf. She’s also brilliant, hard-working, imaginative, driven to succeed. And, indeed, she becomes a very successful trial lawyer. Eventually, she is made partner. OK. Isn’t this exactly what we’d expect to happen? What does being tone deaf have to do with anything?

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Imagine instead, that Sue was inspired at the age of four when she went to the opera. It was her life-long dream to become an opera singer. Indeed, she was blessed with a beautiful voice. She was also brilliant, hard-working, imaginative and driven to succeed. Unfortunately, she was tone deaf. Now, the weakness becomes interesting. Perhaps she will fail and kill herself. Perhaps she will fail but find another goal that is even more important to her and succeed at that. Perhaps she will fail time after time but eventually develop a career as an improvisational opera singer. She will ask people in the audience to name five things and then and there, she will create a beautiful aria that weaves a tale of some considerable interest about the five things. No-one knows that she is singing out of tune because she is composing on the spot.

The more improbable the odds and the more horrendous the journey, the more challenge you give yourself to make it work! Blind at birth but wants to be an artist? Surely, that’s just stupid. It’s impossible. But is it? What if feedback were provided in such a way that it influenced her to make unique and beautiful paintings? What if genetic engineering allows her to grow new neural pathways? What if she can be equipped with artificial eyes? If it’s fiction, a magic spell can do the trick. Even if your ultimate goal is a real product for the real world, imagining a magical solution may lead you to a new (and real) path, previously hidden by your own expectations.

It is easy for a writer to identify with their hero. And that is potentially quite a problem. After all, if you were superman, you sure as heck would not go out of your way to go near kryptonite. You’d quite sensibly stay away from the stuff! But if you are writing about superman, you need to get him near the deadly stuff every third or fourth episode! The “weaknesses” in the character generate interest. The failures, injuries, betrayals, and conflicts of your protagonist provide materiel that allows you to architect a more interesting plot.

A Garden of Delights, Flashy Sights, or Sword Fights?

Three dimensions of story is a weak metaphor only. The three dimensions of a cube can be manipulated independently. This is not generally true for the three dimensions of story. The character makes a decision, the decision determines the next step of the plot. That will influence the setting for the next scene. In addition, the actions of the protagonist may also change state of the underlying and cross-cutting conflicts.

Imagine:

two rival gangs fighting for urban turf and maybe sex,

two gardeners in a fierce competition for sex with the town’s most eligible “catch” as well as for the blue ribbon prize for best garden,

two rival secret agents vying for victory and maybe sex,

two life long friends now vying for #1 in their Harvard Law class, and maybe sex.

The structure of the underlying plot might look quite similar, but the specifics will depend a lot on how the character is developing. If they develop from ego-centric to altruistic, then they will tend to make different decisions near the beginning than near the end of the story. In addition, the setting will have to be consistently portrayed.

The four descriptions above would most naturally lead to a lot of the setting for the stories respectively in urban settings, garden settings, foreign settings & dangerous situations, mainly Law School and campus settings. Of course, you could violate expectations in a way that increases interest. Imagine that rather than have another garden scene–

The rival gardeners arrive at an urban parking lot dressed in expensive gowns, fully jeweled in their finest, both fully knowing that they will win first prize (but secretly fearing that they might not). These life-long friends now exchange icy greetings, make back-handed compliments about each other’s appearances. The verbal exchange escalates. Precisely because they know each other so well, they know exactly how the other person’s escalator functions. Soon, they are rolling around on the parking lot in their fancy gear; ruining each other’s clothes and hairdos. At this point, they hear in the distance, the loudspeaker and the chairman about to announce the Blue Ribbon Winner! In their trashed and ripped clothing, they sneak in together to hear the awards, hanging out together in the shadows so as not to be seen in their tattered clothes. “And the blue ribbon goes to” {drumroll}:

someone else entirely.

At this, the two life long friends look at each other, laugh uproariously, hug each other, and then become even more intimate friends than they were before their fight in the urban parking lot.

The fact that there are “expected” relations among various dimensions of story is wonderful. For every such expectation, you can decide to follow, bend, or break that expectation. The more expectations people develop, the greater the number of variations for creative exploration. One valid reason for the choice of setting is really where you want to spend your time. That goes for an author — but it also goes for any designer or business person or User Experience expert. What kind of setting do you want to be in? What kind of customers do you want to serve? Do you really want to make their life better or just get them to buy more product? What sorts of application areas are really cool to you? Of course, I understand people need to eat and often there is a conflict within us all about what to do. That’s what a good story is really about.

The reason that stories resonate is that, regardless of setting, people face the same kind of dilemmas. We all do. And, how we handle those dilemmas? In life, as in story,

character is revealed by choices under pressure…

——————————————

Author Page on Amazon

Dream Planet on Barnes and Noble

The Impossible

Donnie Boy gets a hamster

What could be better? A Horror Story

All that Glitters is not Gold

The Forgotten Field

Choosing the Script

The Story of Story, Part 2

16 Friday Jan 2026

Posted by petersironwood in creativity, HCI, psychology, story, Uncategorized

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AI, books, communication, education, fiction, HCI, interview, knowledge, narrative, needs, psychology, story, truth, user experience, UX, wants, writing

Introduction:

This is the second in a series about using stories and storytelling in the design, development, and the deployment of products and services. In each post, I will weave in some advice about what makes for a good story as well as how to use stories. In this first case, the emphasis is on using stories to help uncover customer needs and wants. Needs and wants are not quite the same thing. For an extremely worthwhile discussion on the difference, check out this classic article by George Furnas.

We Human Beings are not just Information Processors; we are also Energy Processors.

I had just attended a conference on “knowledge management” co-sponsored by IBM consultants and IBM Research. On the plane ride back, after finishing the crossword, I turned the page to find a full page color ad by an IBM competitor that proclaimed: “Knowledge Management is simply [sic] providing the right information to the right person at the right time.” Color me skeptical, I thought. It isn’t simple to do those things. Beyond that, the formulation seemed simplistic even in its formulation.

The image of one of my undergraduate professors flashed into my brain. Professor MacCaw, (as we will call him), taught advanced German, a language which he had learned in a Russian prison camp, which might explain his approach to testing. At semester’s end, he asked, “Who in class wants A?!”

All two dozen of us raised our hands, of course. At this point, he proceeded to — there is no other word — attack one of the students in the class who had had four years of German in high school and had also lived in Germany for two years. The contents of his questions were not really that difficult, but the manner in which he demanded the answers was horrid. He would ask, for instance, “In first story, main character went where?” (He would always ask the questions in English).

And she would begin to answer (necessarily in German), “Er geht…” And after a couple words were out of her mouth, he would scream, “Please to conjugate!” This meant that she would have to think back to the last verb she uttered and then conjugate it. “Ich gehe, Sie gehen, …” Then, he would interrupt again and scream a completely different and unrelated question in English. She would begin to answer; he would interrupt after she uttered only a few words: “Please to decline!” This meant, that she would have to give the various forms of the last noun she spoke according to the case. But once again, she could not finish but only begin declining the noun when he would once again interrupt. After 40 minutes, she was in tears and he looked menacingly around the room and asked, “NOW! Who in class STILL wants A?”

I have zero desire to go hang gliding or sky diving. But when it comes to the danger of mere social humiliation, I say, “Screw it. Been there. Done that.” I was one of only two of the remaining students who raised their hand. This act won me the next turn on the chopping block. He proceeded the same whip-saw questioning fest with me. The two-period class was almost over when he finished with me and began questioning “Mr. Lepke.” The bell rang and everyone else in the class left. Later that evening, I chanced to see Professor MacCaw in the Student Union. He walked up to me, eyes blazing. “Ha! I had Mr. Lepke after class for two hours! Finally, he said to me, ‘No, No, Dr. MacCaw, no more, I beg you. No more!’”

This oral exam was difficult (even with my “screw it” attitude). It was much “harder” than my dissertation defense, for example. Again, it was not the information requested but the manner of questioning that made it difficult. People are not emotionless robots, as it turns out.

The next semester, not surprisingly, only about half the class returned. One day in class, as Dr. MacCaw began one of his lengthy digressions on Eastern European history, he stopped himself in mid-sentence to say, “What is THIS!? Someone is passing notes in my class! I will take note and read in front of entire class!” He snatched the note, unfolded it, and indeed read the note in his loud ringing voice: “Doctor MacCaw: your zipper is down.” And, indeed it was. He had meant to humiliate someone in front of the entire class — and he had succeeded. He had the necessary information delivered at the right time to the right person, but — thanks to his own actions — it had not been done in the best manner — at least not the best manner for him.

Human beings are not just information processors. We are living things and as such, the emotions, the vibes, the manner, the intensity of presentation — these are all vital to how we will react at the time and also how we will feel about the people involved and what we will recall years later. And this fact also means that the atmosphere you create when you interact with various stakeholders will vastly impact the quality of the insights and stories that you receive. If you really care about the people and are really committed to doing something to making people’s lives better; if you are truly open to hear and take in something unexpected or even disruptive to the project; and if you allow your informant to feel that truth about you, you will obtain the gold ring.

Stakeholder Stories Solicited at their Sites.

If you use a mechanical method and a mechanical tone and a mechanical manner to ask your users and other stakeholders about their needs and wants, what you will uncover are the most mundane, most rudimentary, most superficial and socially acceptable needs and wants. You can indeed use this information to design a product or service, and you may even have a product or service that succeeds in the marketplace. It will likely be, however, a rather short-lived “win.” Why? Because you are designing to fulfill wants that are subject to the wild winds of passing fashion rather than to catch the fire of an underlying passion.

What I found for myself was that it typically took about an hour of talking with a stakeholder, and most importantly, listening attentively, before they began to tell me their real stories. Your mileage may differ according to culture, context, power relations, your personality, and so on. I like to use a semi-structured interview. In this type of interview, there are known questions that I want to ask. But I also schedule plenty of time to let them elaborate, tell me what’s what behind the scenes. I know that in the corporate world, there is an ever-present push for being “efficient” and getting the job done as quickly as possible. So, it’s tempting to get the informant “back on track.”

I always prefer to interview an informant in their workplace. This seems like common courtesy; it puts them more at ease; and it sometimes reveals their use of other people, references, private notes, etc. as well as what they are dealing with in terms of atmosphere, noise levels, interruptions, desk space, etc. It also makes it much more likely that they can retrieve more of their own memories about work incidents more accurately because of all the contextual cues.

John Whiteside, who ran the Usability group for Digital Equipment Corporation for a time, recounts running various usability studies and gathering data in various ways about a product they were designing for manuscript centers (places where human beings, historically almost always women, transcribed the dictation of others into text on a computer so that it could be edited, re-written, stored, etc.). The first time that they visited their users in the field, they discovered that they spent about seven hours a day typing and about an hour every day counting up, by hand, the number of lines they had typed. So, in one instant, they realized a feature that would improve productivity significantly.

Guidelines for Soliciting Stakeholder Stories.

When I managed the storytelling project at IBM Research, I was fortunate enough to hire Deborah Lawrence to help with the project. She thought it would be a cool idea to interview experts in a number of fields whose job, in one way or another, involves soliciting stories. So, she went out and did just that. I believe that her interviewees included medical doctors, policeman, reporters, social workers, and psychotherapists. These various practitioners had very similar guidelines.

Story Elicitation Guidelines:

Provide a “warm-up” period.
Tell something personal and revealing about yourself; perhaps tell a story that is a model of the kind of story you’re looking for.
Observe an implicit contract of trust.
Provide a motivation for the story — why it’s important.
Accept the storyteller’s story and worldview. Don’t resist the story.
Reveal who you are, how the story will be used, potential audience and goals, answer questions.
Use questions to probe. Sometimes, a totally “off the wall” question can create space for story to emerge.
Empower the storyteller — they are the expert.
Avoid threat; don’t appear as an expert yourself.
Listen with avid interest.

These may seem fairly obvious such as does a lot of the advice in the book, How to Win Friends and Influence People. (Come to think of it, that might be the single best book you can read if you want a career in HCI/UX). However — back to the guidelines. I think they seem obvious once pointed out, in much the same way that once someone points out the “pig in the clouds” (or the face in the tree) you cannot not see it.

The above list is not, of course, meant to be the definitive such list. This was based on one study. If you have additional guidelines or disagreements, please let me know.

Author Page on Amazon

The Walkabout Diaries

The Myths of the Veritas

A Pattern Language for Collaboration

Imagine All the People

The Dance of Billions

Roar, Ocean, Roar

The Story of Story, Part 1

15 Thursday Jan 2026

Posted by petersironwood in creativity, management, psychology, story, Uncategorized, user experience

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AI, Design, development, HCI, knowledge, leadership, life, management, persuasion, story, thinking, thought, truth, UX

The Story of Story, Part 1

Background.

Right around the turn of the century, I managed a research project at IBM’s T. J. Watson Research Center on the business uses of stories and story-telling. The project was part of a larger effort on “knowledge management.” One of IBM’s major reasons for being interested arose from their increasing revenue stream from services. However, services such as consulting required a lot of labor; it was competitive. Therefore, the margins on this business were not so high as, for instance, in hardware or system software. IBM invested a lot in tools so that they can make hardware very cheaply and effectively using relatively little labor. The company wanted to be able to something similar with consulting services. The idea was that we could use knowledge management so that the knowledge assets of top-level consultants could be, captured, organized, and then re-used by more junior (and less expensive) people thus rendering higher margins for the company. The success of this approach was fairly limited partly because the knowledge management methods were geared toward explicit rule-based knowledge and specific facts. Much of what experts “know”, including IBM’s top-level business consultants was tacit knowledge. Stories provided a natural way to capture tacit knowledge. Thus, the story project began.

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My simplistic initial idea was to build a story platform that would enable consultants to write stories about their experiences. After all, sharing stories orally is what experts naturally do anyway. Since I enjoy writing stories, I failed to realize initially all the reasons consultants would not want to share their experiences by writing stories. Writing stories is not so natural or fun for most folks. Partly because of the medium and partly because of higher expectations, it also takes more time. Perhaps, even more importantly, it takes extra time. When consultants share stories, they are often traveling, eating dinner, having drinks together. Sharing stories is something done in a friendly off-hand way, and importantly, it does not take extra time in the way that writing a story would.

In addition, when a consultant says something out loud it is not typically recorded. So, if they misspeak or said something untoward, they have plausible deniability. When someone tells a story live, they also can sense how the story is being received in real time. If the listeners are “into it” the teller can draw things out and make it more vivid. On the other hand, if they are starting to play “Candy Crush” on their phones, you can cut it short. In writing, typically, first you write and then you get feedback. Of course, professional writers often improve things considerably with the help of a copy editor, beta readers and a proofreader. Anyway, over the course of time, we did develop a feasible way to have people tell stories and from those stories, provide information of use to other knowledge workers.

Three Patterns for using stories.

Narrative Insight Method describes techniques for gathering valuable knowledge from experts through the use of storytelling.

Fostering Group Cohesion through Common Narratives is another storytelling technique: in this case, one focuses on building and disseminating stories that illustrate common values.

Fostering Community Learning via Transformed Narratives. This helps solve a dilemma. For organizational learning, it’s crucial to learn from people’s mistakes. Ordinarily though, mistakes are not just used for learning but can bar one from advancement, or from getting raises, and lessen the esteem one’s colleagues might have of the teller.

In this post, however, I want to describe some of the things I found interesting about stories from personal observations and, to a lesser extent by reading. Here are just a few examples of interesting aspects of stories.

Good story writing is not magic. It’s craft. Mastery is a life-long quest, but one can quickly learn a few important things that will help you to write better stories as well as to enjoy more thoroughly the stories you see or read.
Stories are memorable and motivating. If you watch people telling stories, they are animated and engaged in a way that is rare when people are discussing facts, pronouncements, or pleasantries.
Business-speak is grey, toneless, neutral, abstract and speaks to the intersection of people’s experiences. Stories on the other hand, can be colorful, concrete, emotional, and, collectively they add to the union of people’s experiences.
Although stories are generally presented in a linear sequence, beneath that, the story actually has a hierarchical structure. Most stage plays have three acts. Within each act, there are a number of sequences. Within each sequence, there are scenes. Within each scene, there are “beats.”
The three major dimensions of story are setting (where, when), plot structure (what happens), and character (the people; what they are like and what they want).
Story lives on conflict; a story explores the edges of human experience; it takes us on an empathic roller coaster ride.

In the next essay, we will begin to see more specifically how to use stories to help us discover problems and issues. Later, we will see that stories are a tool of thought that can be used in many different contexts and in many phases of problem solving and development.

———————————————

Author Page

There’s a Pill for That

Inventing a New Color

The First Ring of Empathy

The Forgotten Field

The Sound of One Hand Clasping

Stoned Soup

The Three Blind Mice

Finding the Mustard

What About the Butter Dish?

How the Nightingale Learned to Sing

Absolute is not Just a Vodka

My Cousin Bobby

If Only

Tools of Thought: Symmetry

07 Wednesday Jan 2026

Posted by petersironwood in management, psychology, Uncategorized

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beauty, Business, Design, HCI, human factors, Human-Computer Interaction, poetry, politics, problem_solving, symmetry, truth, UX, Web design, writing

Symmetry

(Original, free-hand drawing by Zoe Colier).

There are many varieties of symmetry. Symmetry exists rampantly in nature and symmetry is also incorporated into many human designs. In this short essay, I want to remind people of several varieties of symmetry and then show how symmetry may also be used as a tool of thought to help solve problems by simplifying the space of possibilities that must be considered.

Symmetry is a concept with far broader application than cutting out paper snowflakes or choosing a nice looking Christmas Tree, Menorah or other Holiday decoration. It is fundamental in logic, mathematics, physics, chemistry, biology, and even in social science.

Symmetry exists at many different scales as well. Planets are generally roughly spherical and their orbits are roughly circular.

The human body, along with most other animals, exhibits rough bilateral symmetry in external appearance. If you examine your own fingerprints or the pattern of your moles, for instance, you will see that one side of your body looks slightly different from a mirror image. If, like me, you are a righty who play tennis, you will find the forearm muscles on your right arm are slightly larger than those on the left. What is remarkable to me is not that there are slight variations between left and right but just how slight those variations are. And, we are not alone. Fish, insects, flatworms, roundworms, snakes, turtles, lizards, horses, dogs, cats, apes, and humans are all roughly bilaterally symmetrical in appearance. I say “in appearance” because our internal arrangement of organs is not at all symmetrical.

External Appearance and Internal Organs

In general, it seems to me that most animals possess more complete or “perfect” bilateral symmetry than do most plants. I suspect that this is because animals generally move through a physical environment. Since we can move around, the environmental forces are generally symmetrical and so our ability to react to those environmental forces is also symmetrical. A tree, on the other hand, may have a genetic “blueprint” to be bilaterally or (more likely) radially symmetrical, but it may be subject to strong asymmetrical forces such as wind, a water source, or sunlight versus shade.

Our designed objects are also most often (at least) bilaterally symmetrical, and particularly for those objects which must interact and move through the physical world. Cars, boats, motorcycles, busses, trains, trucks, bikes, skis, surfboards, roller skates, ice skates, snowshoes and tennis shoes all tend to be bilaterally symmetrical. On the inside, however, again just like us, there are often some irregularities. The arrangement of controls of the car, for instance, are asymmetrical. (Each control in itself often does show symmetry. In some cases, this makes it easier to use, especially without looking. I suspect that the symmetry may often be for aesthetic reasons, for ease of manufacturing, for ease of maintenance or replacement or some combination.) The asymmetry of arrangement “works” because the arrangement of displays and controls does not interact with the natural world the way that the car body and wheels do. The controls are designed to interact with a human being. There are also rough conventions for where controls are laid out, how they operate, and what each type looks like. Asymmetry of arrangement is also evident under the hood. However, some of the components such as the engine, the battery, the radiator have symmetry within them. The radiator, which arguably has the most interaction with the outside world, is symmetrically placed though its plumbing is not.

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In the design of User Interaction and Experience, an argument can be made for certain kinds of symmetry. For example, in the Mac editor Pages, which I am using to write this, if the B for bold button background turns blue when bolding is turned on, I expect the background will turn back the way it was (white) when bolding is turned back off. I also expect that italics and underlining will behave the same way, especially because all three are in the same toolbar.

Where possible, it also generally makes sense, I believe, to design so that the functionality of a system is symmetrical. This isn’t always possible. Some actions are necessarily irreversible. If you don’t believe me, ask anyone who has toddlers or who has pets. In the real world, if you shoot someone dead, you cannot “unshoot” them. Unlike a computer system who asks, “Do you really want to delete all your files?” before doing so, guns do not ask that. If you are designing what can be done with a toy robot however, if you can make it go forward, you want to make it so it can go back as well. If it can turn right 90 degrees, you would like to enable it to turn left 90 degrees. Saying, “Oh, yes, but don’t you see, you can, in effect, make it turn left 90 degrees by making it turn right 90 degrees three times?!” does not cut it, IMHO.

Typically, you not only want the functionality to be symmetrical, you also want the control functions and appearances to mirror the symmetry of the functionality. For example, if you can issue the command: “MOVE ROBOT FORWARD THREE PACES” you want the symmetrical function to be evoked this way: “MOVE ROBOT BACKWARD THREE PACES” and not, “THREE PACES BACKWARD FOR ROBOT MOVE.” If you decide to give auditory feedback for the first command that says, “ROBOT MOVING FORWARD THREE PACES” you do not want the reverse command to provide feedback that says, “ROBOT THREE PACES BACKWARD MOVING.” (Oh, by the way, if you cannot provide symmetrical functionality, please do not pretend to do so with a facade of symmetrical looking commands that actually behave asymmetrically!)

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A lack of symmetry (or consistency) in the functionality, command structure, or visual appearance often arises because of a lack of communication within the development team. If different functions of the robot are to be implemented by different people, then it’s important that those various people use an agreed upon style guide or Pattern Language or that they communicate frequently. Of course, this is not the only cause of asymmetry. Even if your team communicates really well, they can’t design an effective gun with an “unkill” function.

There are, of course, various types of symmetry. Bilateral (mirror) symmetry is what the external appearance of our bodies has. There is also translational symmetry, where the same shape is repeated along a line. The string ABCCBA shows bilateral symmetry while ABCABC exhibits translational symmetry. Most human factors people now agree that hot water faucets (usually on the left) and cold water faucets (usually on the right) should both be turned off by turning to the right and turned on by turning to the left (translational symmetry) as opposed to having the faucet on the right turn off to the right and the left faucet turn off to the left. But you will definitely experience both types.

In both music and poetry, at least in the culture I am most familiar with, translational symmetry is more common than mirror symmetry. It does sometimes happen that musical composers experiment with playing a tune backwards or even with the staff turned upside down. But this is far less common than repeating a theme or melody. Similarly, a rhyme scheme like ABCABC is much more common than is ABCCBA. {In this notation, ABCABC means that the first line rhymes with the fourth line, the second line rhymes with the fifth line and the third line rhymes with the sixth line.}

black and brown millipede on a green and brown branch

Photo by Pixabay on Pexels.com

In biology, we also find translational symmetry or something close to it. The segments of a tape worm, the segments of the body of a millipede or centipede, the small legs of a lobster, and even our own vertebrae and ribs show translational symmetry. In social structures as well, we find both mirror symmetry and translational symmetry. For instance, the Golden Rule says to do unto others as you would have them do unto you. In addition, as it happens, if we are nicer to other people, then, generally speaking, they are also nicer to us. This is not always true, however. Some people simply take advantage and view all of life as a zero sum game. Whatever you gain, they lose and vice versa. This is a very limited, inaccurate, and self-defeating attitude in most social situations. Most social situations, are, of course, much more complicated. Generally speaking, there are a great many situations that both you and your “opponent” or even your “enemy” would agree are good and a great many others that both of you would agree are bad. If you are playing tennis or golf outdoors, for instance, you may be fiercely competitive but both of you would probably find a game that brings out the best play is better for both of you. Both of you would probably also agree that being rained out is a bad outcome.

men in black and red cade hats and military uniform

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In the military and in many industrial settings, there is a great deal of translational symmetry. The “ideal” set-up is to have many groups at each of many levels and each group is meant to be as similar as possible to all the other groups at that level. The marching that military groups learn is both symbolic of this translational symmetry and practice in behaving as a unit composed of identical parts. Whether or not this is the best way to run a military is debatable. To me, it’s undeniable that this management style has been imported into a huge number of organizations where it is definitely not the best way to organize.

The last thing to note is that symmetry also pops up in design. There is often a whole series of information exchanges from people who have quite different areas of expertise. These exchanges can result in mutual learning, solutions that work, and often patents, and occasionally, some really cool, transcendent, game-changing designs. In my experience, it is much better to have a design process based on symmetrical relationships founded in mutual respect than to have a design process based on having someone in a hierarchical power relationship make decisions that are to be implemented by an identical set of “underlings.”

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The Takeaway

Symmetry is everywhere. There are many forms. If you start looking for symmetry, you will find examples in nature, in mathematics, poetry, art, music, machine design, the military and even in design problems and design processes. Thinking quite consciously about the types of symmetry that exist in a problem space and what could or should exist in that problem space, can lead to novel solutions.