Cedars Sighing in the Wind

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Cedars Sighing in the Wind

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When Cat Eyes had finished reading aloud the story of The Wobby Man, she put aside what the ancients called a “book” and looked expectantly at Tu-Swift. He seemed lost in thought — tortured thoughts filled with thorns — by his visage. Cat Eyes stood and grabbed a nearby water pouch. Reading aloud made her thirsty. She sat back down across from him. She smiled. She was happy to see him again; happy to be reunited with her parents; happy at all the things that the tribe had learned from their discovery; happy that it had taken both of them working together, with their mutual friend Suze, in order to discover how to read. The joy of Cat Eyes felt a sharp edge though because Tu-Swift seemed anything but happy. 

“But, I don’t — .” Tu-Swift didn’t finish what he said to Cat Eyes because he didn’t know what he himself meant to say. Instead, he shook his head from side to side. “Why?” 

Cat Eyes took his hands into her own and looked at him with love in her eyes, a love that he did not see because his head bowed down and his eyes were only upon the ground. After a few moments she put one of her hands under his chin and lifted it up. They looked into each other’s eyes and she could see that his eyes were tearing up. “It’s okay. It’s to learn from, like all the stories here.” 

Tu-Swift shook his head from side to side and bit his lips. “But why?” His voice was plaintive as though he had a thorn stuck painfully under his fingernail and pled for her to remove it.

Cat Eyes sighed and asked gently, “Why what? What are you struggling with? Maybe we can work it out together. Often, life is a fight, but it doesn’t mean you have to be alone in every fight.”

Tu-Swift nodded. After a pause he said, “Why did The Wobbly Man do all that evil? And why did they let him?! Why couldn’t they see what he was up to?” 

Cat Eyes nodded. “There are people who do things — evil things — such as steal children. Perhaps there always will be. But I don’t think they think of it as evil. To them, it’s their way of … living … or of having fun. They like destroying life and love in others … I guess because they cannot experience it themselves. I don’t know.” 

Tu-Swift sighed. “You are right of course. Within the Veritas where I grew up, there was one such. The Wobbly Man sounds much like him. He manipulated others. He was cruel. Yet, he was such a good liar that he almost fooled our leader, the wise She Who Saves Many Lives. He actually betrayed the tribe to NUT-PI. And here’s the worst part. He got several other braves to go along with his schemes. Without ALT-R, I don’t think POND MUD or KAVANUT would have even been evil.”

“Yes.” After a pause, Cat Eyes added, “It’s much like that Red Spotted Death. It can spread from person to person. And, just as there are evil people even in societies based on truth and trust and love, so too there are people who act in good ways even among the Z-LOTZ and the ROI. It’s much like the story about the two wolves inside someone and which one you feed. The customs of the tribe can make it easy to feed the good wolf — or easy to feed the bad wolf.” 

Tu-Swift let out a long sigh. He stood up and held out his hand. Cat Eyes took it and, for a time, they walked in silence. Without intending to do so, they ended up at the entrance to the now dysfunctional tunnel. They stood for a time, holding hands in silence staring at the tunnel. At last, Tu-Swift voiced what both were thinking. 

“How could a people know so much as to build a tunnel through a mountain — and yet be so ignorant as to let a liar destroy their village?” 

Another long silence ensued until Cat Eyes sighed and spoke again. “We still have many books to read and understand. Many books are filled with words whose meanings we have yet to understand. It appears that it wasn’t just a village here and there. The plague of evil lies destroyed everything. I know you have struggled with whether to use the fire sticks….” 

Tu-Swift wondered why Cat Eyes stopped speaking. He looked at her and saw that silent tears were streaming down her cheeks. He squeezed her hand and asked gently, “What is it, Cat Eyes? Why are you so sad?” 

“Actually, I was just thinking a little while ago how happy I am about so many things. Yet … we as a people once had so much. We knew so much. But we destroyed it. If the books are true, and if our understanding is correct, weapons were developed that … weapons were created that were far worse than fire sticks. Far worse. Yet, there were also treatments for every disease. But the people forgot that they were part of the Tree of Life. People forgot that they were all One. People — not everyone — but enough — just began to grab everything they could for themselves. Lying became commonplace. Once the truth meant nothing, decisions were made by power alone. That is bad enough in the Z-Lotz or, from what you told me, among the Cupiditas. But imagine that they had — not just fire sticks — but horrible weapons that could destroy many villages and all the people in them. Of course, in doing so, these weapons killed birds and butterflies and trees and no-one even seems to have noticed! Maybe … perhaps, we are not really understanding. Maybe they are just stories to prevent people from becoming what the books say that they became. Maybe.” 

Tu-Swift bent down and plucked up a small flower that had grown in the cranny of the wall that held the now defunct controls for the tunnel door. He gently braided the stem into the silky hair of Cat Eyes. When he was done, he said, “Well, the tunnel is real. Yet, no-one really knows how it works. How could that be? I mean, unless there was some great loss of learning. I don’t know. Perhaps, we can learn from these stories, whether real or not, how to … how to ensure that we do not fall so far again. From what you said, it sounds…it sounds as though the people became sightless and witless. How can the people not see that they are a part of the Great Tree of Life? How can they not hear the song of the bird or the murmur of the stream? How can they not see the beauty of the trees and flowers all around them? How can they not taste the sweetness of honey?” 

Cat Eyes nodded. “That is one of the main question that we — those of us who are studying the books — keep asking ourselves. But when this question is asked, none of us answers. Not yet. Each of us is hoping someone else will explain. But what comes to our ears is only the silence and the cedars sighing in the wind.”  

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Roar, Ocean, Roar (A poem about the power of cooperation) 

The Only Them that Counts is All of Us

The Myths of the Veritas: The Forgotten Field 

The Myths of the Veritas: The Orange Man

The Myths of the Veritas: The First Ring of Empathy (Here begins the continuous trilogy of the Mythical Veritas who value truth, love, and cooperation).

Author Page on Amazon

An index to a proposed Pattern Language for Collaboration & Cooperation 

Life will find a way

Come to the light side

Roar, Ocean, Roar!

The Dance of Billions

Somewhere a Bird Cries

The Broken Times

Fish have no word for water

Imagine All the People

The Isle of Right

The Not-See Party

Myths of the Veritas: Stoned Soup

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“Tu-Swift, we are learning so much from the library we uncovered. Just as you came, I was putting the final touches on a translation of a story about Stoned Soup, Would you like to hear it?” 

“Yes! What’s it about, Cat Eyes?” 

Cat Eyes smiled. “Well, I’ll tell you the story and you tell me what you think it means. Here. Come sit beside me.” She patted the rough-hewn bench she sat upon. “You can watch the words as I tell them. How would that be?”

“That,” replied Tu-Swift, “would be wonderful. I love hearing your voice.” He sat beside her and took her hand in his and peered at the runes that he had helped decode. This is the story she read him: 

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Stoned Soup

Once upon a time, long ago, there was a village blessed with enough for everyone. The village, named Acirema, was located near ancient beautiful forests of beech and oak. The forests abounded with plentiful game. Long ago, the people of Acirema had cut down part of the forests and turned it into rich farmland capable of producing abundant food. Beyond the forests lay snow-capped mountains. From the mountains, several clear beautiful rivers ran to the plains near the village of the Acirema. 

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These villagers, like most villagers, had developed many customs. Among them was their shared evening feast. Except when the weather was exceptionally bad, the villagers gathered in the evening to share a feast. They built a huge fire beneath a large cauldron. When the water finally began to boil, villagers began to contribute what they had to the community soup. Some brought potatoes and turnips; others brought large yellow squash, Jerusalem artichokes, and bright orange carrots; still others brought nettles, blackberry leaves, and hickory nuts. Others, who had been lucky at hunting or fishing or gathering eggs brought those contributions and added them to the soup. Each time the villagers made this soup, the first ingredient that they added was invariably a clean stone, though no-one knew exactly why. Many simply accepted that this was the proper way to make soup. Some theorized that the stone made it tastier. Others believed it helped the flavors circulate. Some thought it was a sacrifice to the god of the fresh mountain water, the sun, or the spirits of the forests. 

When the soup was ready, everyone partook and everyone was satisfied. After the meal, they would take turns telling stories or reflecting on the events of the day. Sometimes, they would dialogue about why they began their recipe with a stone. 

On occasion, strangers would wander by and they would join in the evening meal. Some of these strangers taught the Acirema new dances or songs or showed them new ways to make things. Some were strangely silent. All of them thanked them for the soup and most continued on their way after a day or two but some liked the village so much that they joined with the Acirema. Those who joined soon found a way to make their own contribution to the village and its soup. Although some harvests were sparse and some flush, the Acirema always had enough to feed everyone in the village. They worked in harmony and enjoyed life.

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One hot summer day, it so happened that a fat old man wobbled unsteadily into their village. Despite his obvious extra folds of fat, he demanded a very large portion of soup. His appetite seemed nearly insatiable. He didn’t say much at his first few evening meals, but he observed carefully.

The Wobbly Man noticed that some people ate more than others. The Wobbly Man noticed that some people were taller than others; that some had blue eyes and some had brown eyes. The Wobbly Man noticed that some villagers put a large quantity of carrots in the soup and others only put in a few nuts. The Wobbly Man noticed that some people were old and some were young. 

Although the Wobbly Man said little during the evening meal for the whole village, he spoke throughout the entire day, at first, only to one at a time. The Wobbly Man spoke to a strong young man thus:

“Well met, my strong young lad! You must be the strongest man I have ever seen! Surely, you are the strongest in the village! Am I right?”

The strong man answered modestly, “I may be.” He shrugged. 

“Of course you are. And, yet, I know that you could be much stronger still. You are not really getting your fair share of the evening soup. Your grandfather eats as much as you do! How is that fair? I’m sure you’re a much better hunter.” 

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“Grandfather? My grandfather no longer walks this earth. Perhaps you saw my father? He often sits next to me.” 

The Wobbly Man acted surprised. “Oh, that old man is your father. I wonder…he doesn’t seem nearly so strong as you do. Well…who knows? But anyway, he certainly eats a lot for his size. And, yet, he isn’t half the hunter you are, I imagine. I don’t really know. I’m just guessing from how little he adds to the soup.” The Wobbly Man smiled.

After a few moments of awkward silence, the strong young man said, “I’m going hunting. Do you know how to hunt? Do you wish to come too?”

The Wobbly Man replied, “Oh, no. I don’t hunt. You go ahead. And don’t pay any attention to what I said. It’s none of my concern. I like to joke a lot. That’s all. It means nothing. Sometimes a maple tree springs from an acorn, you know?” 

The strong man shook his head. “No, that never happens. What are you talking about?” 

The Wobbly Man replied, “No. Perhaps you are right. I’ve never actually seen that either. Well, you go hunting. Happy hunting!” 

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Next, the Wobbly Man spied one of the beautiful young maidens of the tribe. Long silky blond hair framed her smooth skin and her bright blue eyes. He followed her down to a nearby stream where she bathed herself. He watched with pleasure from behind some bushes. At last, she emerged, quite refreshed; she lay on a warm slab of shale to allow the sun to dry her front and back. When he judged she was about to re-robe herself, the Wobbly Man walked by casually placing himself between the young maiden and her robe. 

“Oh! Well met, young maiden. I didn’t realize anyone was here. Nor did I realize it was your custom to go naked in public. I shall join you then and learn more about your ways.” In a flash, he dropped his own clothes in a pile at his feet. 

The young maiden blushed and this excited the Wobbly Man even more; so much so, that his excitement was nearly visible. He strode up to her wondering whether his great weight would be sufficient to force her to do what he wanted regardless of her wishes. 

“Sir, put your own clothes back on and hand me mine! You are a guest here and it will not do well for people to see you naked. They may misunderstand your intentions.”

“Oh, me, oh, my,” said the Wobbly Man. “I’m just having a little fun. Is that such a bad thing? It’s of no concern to me if you prefer other women instead of a handsome guy like me. I’m sure another young lady will be along shortly. Maybe this is where you congregate? Ah, but I’m a stranger. What do I know?” 

As he spoke, the Wobbly Man reclothed himself and sauntered back toward the nearby village. Here, he spied a group of youth having a spear-throwing contest. After he spied a particularly long throw, he spoke up again.

“Nice throw! Back in my village a throw like that would earn you the right to a maiden such as the one lying naked by yon stream.” The Wobbly Man pointed in the direction he had just come. “Even now, she is quite — what is the right word? She is quite desirous of having pleasure with someone. She even begged me to have sex with her. She complained that none of the young men hereabouts were interested in wooing women. A shame really. But what do I know of your customs? But if I were younger and stronger, I wouldn’t wait so long to make my own desires known.” 

The young men looked at each other and left off their spear throwing contest and ran down the path toward the river, each hoping to win the young lady’s heart. 

The Wobbly Man smiled and chuckled to himself. He closed his eyes and imagined all of them forcing themselves on her. At least, he hoped that’s what would happen. If she were broken and exhausted, he would try his own luck again. 

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Now, a new opportunity presented itself and required his attention. The father of the young man he had spoken to earlier was sitting alone and cleaning fish. The Wobbly Man walked over and sat down on a nearby log. “Good afternoon, dear sir. I believe I spoke earlier today with your son. I’m still learning the names of the people here. What is your son’s name again?” 

“Rigel.” 

“Rigel! Rigel! That’s a fine name. And your son seems healthy and strong as well. I must tell you that my own son, named Junior, is every bit as ungrateful. More so. I’m sure they’ll grow out of it. That’s just the way youth are. I wouldn’t worry about it. Speaking of Rigel, where is he? Why isn’t he helping you clean the fish? That seems the least — I mean, it’s none of my business, of course, but it seems as though if he’s going to complain about you getting more of the soup than he gets, he would have a stronger argument if he did more to prepare the soup.”

The man stopped cleaning the fish and looked at the Wobbly Man. “What? Rigel said I eat more than my share?” 

“What? Oh, no! No, no, no, not at all. Not in so many words.” Here, the Wobbly Man paused, tilted his head, and pretended to be thoughtful. He clicked his tongue, leaned closer to the slender old man and whispered in a conspiratorial tone. 

“If you ask me, he should be very grateful that you agreed — you know — to act as his father. Not everyone I know is man enough to do that. Right?” 

The fish cleaner stopped his work again and looked at the Wobbly Man with a frown. “What do you mean, ‘to act as his father.’? I am his father.” 

The Wobbly Man nodded his head up and down vigorously. “Of course you are. Of course you are! You are the man who raised him. I’m sure beneath all that resentment, he has great respect for you. I’m sure he does. Right? You are sure too, right? All that resentment in his tone and so on — that’s just — he’s probably angry at his mother, really.” 

Every day, the villagers of Acirema hunted, fished, gathered food, or worked their farmland. Every day, the villagers made things, observed things, added to the general well-being, the food stores, or the knowledge of the Acirema. Everyone, that is, except for The Wobby Man, who never hunted, never fished, never built or crafted anything with his own two hands.

That is not to say that The Wobbly Man was not busy. He was very busy each and every day. He told the tall people that they should receive more soup because their tall bodies needed it more than short people did. He told short people that they were short because they had not received enough soup. He told blue-eyed people that the brown-eyed people thought blue eyes were a deformity and he told brown-eyed people that the blue-eyed people thought brown eyes was a deformity. The Wobbly Man set husband against wife; he set father against son; he set men against women; he set the elderly against youngsters and he set youngsters against the elderly.

At first, the Acirema remained peaceful and kept to their own ways. But gradually, just as the sand in a river bank eventually becomes sandstone or shale, the people began to mistrust each other. As the elderly began to mistrust the young people, that made the young people suspicious of the old people. 

Day after day, week upon week, month upon month, the Acirema tribe grew ever more suspicious of each other. When the autumn harvest came, many kept back a good proportion of their food for their private consumption. The community soup grew thinner in consistency and lesser in quantity. The fire needed not to be so large. People often ate in silence. Instead of sitting around the fire sharing songs and stories, the people retired to their own dwellings. When the cold winds of autumn turned icy, they stopped bothering to make soup at all, at least as a group.  

The Wobbly Man had left. No-one seemed to have noticed exactly when he left. He did not tell them that he was going, nor did he share why he was going, nor where. No-one noticed him walk away from the Acirema, turn back and look from afar upon the village of Acirema and smile a broad grin. His last words to the Acirema, he muttered far out of earshot of the Acirema. 

He simply said, “Fools!” 

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The Myths of the Veritas: The Orange Man 

The Myths of the Veritas: The Forgotten Fields

The Myths of the Veritas: The First Ring of Empathy

Essays on America: A lot is not a little

A Pattern Language for Collaboration and Cooperation

The Dance of Billions

Roar, Ocean, Roar!

Math Class: Who are you?

Author Page on Amazon

“The Psychology of Design”

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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.

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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. 

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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

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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.

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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. 

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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. 

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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

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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. 

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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.” 

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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. 

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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”

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

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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!

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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.” 

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

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

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

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

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

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

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

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

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

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

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

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

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Author Page on Amazon

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

Index to a Pattern Language for Collaboration and Teamwork

Experiences in Human-Computer Interaction

Post on “The Story of Story” 

The After Times

After All

When Greed is the only Creed

Destroying Natural Intelligence

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

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

To Be or Not To Be

Whom to Trust?

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“Whom can I trust?” Shadow Walker paced, his energy still high from his second brush with death since becoming the “King” of the Z-Lotz. He didn’t wait for Eagle Eyes to answer and instead ‘ran ahead without his footwear’ as the Veritas liked to say. “I mean who? I am supposed to be their King! Can you imagine someone plotting to overthrow or kill Many Paths?” 

Eagle Eyes nodded. “Yes, I can. If we are going to discuss this, you must keep your voice low. We might be overheard and that would not do. I can imagine someone trying to overthrow or kill Many Paths.” Eagle Eyes paused, watching the face of her friend carefully. When she saw that he understood, she continued. “Shadow Walker, you had better be able to imagine that you might be undone. Or, we surely will be. And I have an inkling that your death would be of some interest to Many Paths. Thunder clouds she would see on every horizon. For her, bright green would turn dark blue and blue would look brown. After a refreshing morning rain, the yellow sun would no longer sprinkle the forest floor with stars. She would just find annoyance in the rain. Her large bright heart that sets a glow in all the people would instead be a siphon to suck their sunny spirit out and replace it with spent black embers from a fire once so bright.”

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Shadow Walker took deep breaths and consciously calmed himself while Eagle Eyes spoke. Just thinking of Many Paths helped. But it also awakened an overwhelming desire to leave; to return home; to see Many Paths; to touch Many Paths; to smell and taste her; to make love with her; to be home where he could trust everyone. 

“Yes, Eagle Eyes. She would grieve for a time. But she is our leader. And she takes that responsibility — that is above everything else, her own comfort, her own desires — even her love for me. She would not allow herself to stay in such a foul place very long. Because of exactly what you say. She would well understand that by seeing a snake in every river, she would lead others to see the same and eventually the people would die of thirst. She knows how important it is to lead by example.”



Eagle Eyes nodded again. “Yes. And an angry leader may anger everyone. A stupid leader encourages the people to be stupid. A cruel leader inspires more cruelty. Do you agree?”

Shadow Walker admitted to himself that it sounded plausible. But then he tried to imagine a counter-example. He couldn’t. Yet, something tickled in his mind that the truth of Eagle Eyes was a partial truth. “There is much truth in what you say. However, just a few minutes ago, I was very upset — for obvious reasons. But you didn’t let it make you upset. Instead, you calmed me down so that I might think more clearly and not do something impulsively that might make the situation worse.”

Eagle Eyes considered. “Yes. You’re right. Sometimes bad behavior produces a good reaction in good people. But that only works at first. Imagine –these people, the Z-Lotz — the leaders lie to the people. They choose their king by assassination. The king — well, certainly NUT-PI, but conversations with Cat Eyes suggest that others were similar — the king shows no loyalty at all to the people whom he depends on. He tries to control them all with fear.” Eagle Eyes bowed her head and shook it side to side. She sighed a deep sigh. “How can people let themselves live like that? It’s horrible. Anyway, the effect of all this on our current circumstance is that because NUT-PI himself was so untrustworthy and so disloyal, many of the Z-Lotz could well be the same. They may think you’re better than NUT-PI, but the ambitious ones are all able to convince themselves that they’d do a better job than you! After all, you’re not even a Z-Lotz.”

“All right, Eagle Eyes. So…” He broke off because Eagle Eyes put her index finger on his lips. He remembered her admonition to speak softly so as not to be overheard. He took several deep breaths and continued.

“So, let’s leave! Let the Z-Lotz sort out their own issues! For all we know, Many Paths needs our skills right now. Why are we saving these people when we may still have more problems at our own Center Place.?”

“First, I don’t think sneaking out is all that feasible. But even if we did leave, might they not be affronted by a King who simply — abandons them. Hard to know whether they would become so ensnarled by their own fighting that they would ignore us or whether they would somehow find this a good excuse to attack the Veritas. And — the very best we could hope for is that things would “get back to normal.” And these people would come and steal children again. If we stay…and we live…there is some chance we could improve relations between … well, really among all the tribes. And, they know things that could be important for us. Besides, none of the people born into the Z-Lotz chose to be born there. If we can help them….”

“If. Yes. If. They know their ways. We don’t.” Shadow Walker looked at Eagle Eyes, who was clearly deep in thought. “I don’t even know how many of them know about that cache of weapons and gold that we found. I don’t know whom I can ask about those weird liquids in the see-through rocks that are not rocks.” 

Eagle Eyes and Shadow Walker reflected on their situation in comfortable silence for a time. The Veritas were unafraid to give their ideas space enough to breathe; time enough to mature. 

After a time, Shadow Walker said, “We desperately need to understand more of their language. Perhaps we could find some tutors to trust. More than one. It may be very hard to decide whom to trust, but it may be possible to find someone to trust. If we could ask questions of multiple tutors, and we get the same answers, we might presume that they are telling the truth, or at least the truth as they see it. Yet, if they say almost the exact same words, then they are telling a rehearsed story to gain our trust.”

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Eagle Eyes added, “In addition to learning more about the Z-Lotz and their language, for others, we can simply be honest. Tell them that, because of the assassination attempts, you don’t know whom to trust so we will need to test their loyalty. Give them the Veritas Test of Truthfulness. If they pass, you will trust them and that will be a very good thing for them as well as for you. On the other hand, if they lie to you, they will not pass the test and that will be a very very bad thing for them.” 

“What is the Veritas Test of Truthfulness? Why have I never heard of it, Eagle Eyes?”

Eagle Eyes smiled. “We will need to create it.” After all, She Who Saved Many Lives created seven tests of empathy. We ought to be able to create one test of truthfulness.” 

Shadow Walker suggested, “Suppose we observe someone doing something very difficult without their knowing that we are watching. We note how they do. Then we ask them how they did. We will see how accurate they are in their description. If they are honest about their mistakes, they are likely to be honest about other things. On the other hand, it seems a bit ironic — and more than a little sad — to build a test of honesty that relies on deception.” Shadow Walker looked down to the side and bit his lower lip.

“Then let’s not,” said Eagle Eyes after a time. She saw the questioning look in the eyes of Shadow Walker. “I mean, let’s not be deceptive. I don’t think we need to. We will ask them to do something and observe them. I believe, the dishonest will still give themselves away. They are so used to lying that they won’t be able to give a fair description of what they did and did not do.”

Shadow Walker considered: ALT-R had been able to fool nearly everyone about his true nature. For most people though — Eagle Eyes was likely right. What if the Z-Lotz had their own ALT-R? Would they be able to smoke them out? After all, Cat Eyes had said that the Z-Lotz leaders convinced the people who actually worked that they believed in a whole jungle web of lies when actually, they didn’t. She had seen their hypocrisy. Perhaps that was partly because, as a slave, they saw her as not fully human or not very clever. Shadow Walker realized that he would benefit from the thoughts of Eagle Eyes so he said aloud, “We need to start with the people I do trust. I can explain to Tree Vines that the sooner he can help me vet the Z-Lotz, the sooner he can leave to see his daughter — and — that his daughter will grow up in a safer world. If we do this right, we might be able to prevent kidnappings such as what happened to his own daughter so many years ago.”

Eagle Eyes laughed.

Shadow Walker frowned. “Is that funny?” 

Eagle Eyes said, “No, it’s just that I had an image. I saw honesty spreading through the Z-Lotz like a plague.”

Shadow Walker chuckled too. “That would be something.” Then another frown passed over his brow. “But that seems like we’re making them into Veritas. Is that right? What if they prefer being dishonest and choosing Kings by assassination rather than competence?” 

Eagle Eyes said, “Yes, in the same way that watering the squash turns it into something edible instead of a barren stalk. We’re not talking about their preferences for how well done they like their meat. We’re talking about truth — which is every bit as vital as water is for life itself. Lies, dishonesty, cruelty, hate — these are not the paths of Life. These are paths of Death. As shown by our story of the Orange Man.”

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The Myths of the Veritas: The Orange Man 

The Myths of the Veritas: The Forgotten Field 

The Myths of the Veritas: The First Ring of Empathy (Beginning of Book I)

The Myths of the Veritas: Feast and Fire (Beginning of Book II) 

The Myths of the Veritas: A Map of Sorts (Beginning of Book III)

Author Page on Amazon

Index to Patterns for Collaboration and Teamwork

An Essay on the Nature of Nature

A Lot is Not a Little

The Ailing King of Agitate

Cancer Always Loses in the End

The Silent Screams of Dead Mens Dreams

Somewhere a Bird Cries

The Broken Times

Roar, Ocean, Roar

The Dance of Billions

Finding the Cache

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Shadow Walker and Eagle Eyes spoke softly to each other in their native tongue — Veritas — as they explored their “House of the King.” They wanted to plan without being overheard.

Shadow Walker suggested, “At no time should both of us be asleep. I think I can trust our three ministers, but I am not sure. Cat Eyes told us that most of the Z-Lotz do not even believe the myths and legends that they insist everyone else believe! How can one see into such a heart? They shade their soul windows. Can you know the heart of such a one? Can your eagle eyes penetrate the blank stare?”

Eagle Eyes shook her head. “I cannot.” She paused for a moment and took a deep breath. “You are strong and wise and handsome and these things help. But you are still seen as something foreign. I cannot imagine that the people held much love for NUT-PI. He was a cruel and ineffective leader who repeatedly betrayed those loyal to him. There may be others from among the Z-Lotz…no, there must be others from among the Z-Lotz who are popular and who are ambitious enough to be King. Even among the three ministers.”

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Shadow Walker nodded. As they spoke, they strode through the King’s House. Shadow Walker’s hand’s idly trailed along the walls as they spoke. The surface felt shiny like rock, but felt warm, something like a rock in the sun, but they were inside. Odd. The surface seemed rock-like but not really rock. It was also much too regular. He wondered whether some of the tiny but deadly red spiders were on the walls. 

Eagle Eyes explored her surroundings a different way — by darting her eyes everywhere. Shadow Walker stopped and took the hands of Eagle Eyes. Unlike the Z-Lotz, his eyes were open as he said, “Thank you for saving my life! We will get through this, but I must confess…I don’t know how. I need you and your quick thinking if we are to survive.”   

Eagle Eyes tried not to blush, but she couldn’t help herself. She bit her lip and tried to plan. That helped some. Wild images swarmed before her like hiveless bees not knowing where to alight. “Sometimes, I wish we could escape in the night. I’m not sure we could even do that, but it would be wrong. Even if these are Z-Lotz and ROI, they need a leader who isn’t corrupt.” 

Shadow Walker gave no outward sign as to whether he had seen her blush. He nodded. “To leave now would be — cowardly. I do trust the parents of Cat Eyes. And, that’s good because we need them to translate. But — now that they know their daughter is alive, I presume that they will wish to journey to see her very soon. In fact, Tree Vines has already told me so. When that happens….?”

Original drawing by Pierce Morgan



Eagle Eyes nodded. “Regardless of what the future brings, it seems that you and I would do well to learn more of the language — and of the ways — of the Z-Lotz and ROI.” 

Shadow Walker grimaced. “You are right. Though I wish they would learn more to be like the Veritas, to tell the truth. Just think. The only way for me not to be leader is for someone to kill me! That method ensures that only the most powerful — or most treacherous — will become King. And it will encourage intrigue among the people — not honesty and openness — which are two virtues we desperately need to kill off this plague.”

Eagle Eyes sighed. “If we even can kill it off. We have to try though. That has to be our top priority. Meanwhile, we need to learn as much as we can including who, if anyone, we can trust. I know you must miss Many Paths. I miss her as well. Still, our lives would be simpler if we were together. We could stay here and rule and teach our children to rule and how to stay alive. When the time comes, our offspring could wrest control from you by “force” — though — “farce” might be closer to the truth. We could feign your death and then, once the new ruler was firmly in place, you and I could leave.” 

Shadow Walker frowned and then laughed. “That is way too long to wait! But I — I do like your idea about faking my death. That might be a way to provide them another ruler. Anyway, first we must try to help them avoid being killed off. They’ll be plenty of time to plot out our leaving after that. But you said you missed Many Paths.” 

Eagle Eyes nodded. “I do. Don’t you?” 

Shadow Walker nodded. “Of course, but … I thought you would say you miss Trunk of Tree.”

Eagle Eyes frowned. “Have you noticed how all of the rock in this place is the same exact color?” 

“I don’t think it’s really rock. At least, it’s not like any rock I’ve seen before, but — yes. It’s all the same. Too much the same. Not like real rock.” Shadow Walker wondered whether Eagle Eyes wanted to avoid answering his implied question.  

Eagle Eyes pointed, “Except over there. Look.” She strode over to a spot behind the throne.

Shadow Walker followed her over. It was subtle, but there was a definite set of lines making a rectangle. Shadow Walker traced the line. It felt different too. He pushed on various spots and felt a slight give. They tried pushing at the same time in a variety of places but nothing happened. 

Shadow Walker again found himself wishing that Many Paths were here — or, even better, that he was with her back in the Center Place of the Veritas. Yet again, he took out the Sixth Ring of Empathy. As he felt it and stared at the crystal, as always, he felt a little closer to her. 

In his mind’s eye flashed a clear image. Shadow Walker saw himself as a very young boy. He held a leaf in his hand — a dry leaf. He turned and looked up to the side where he saw a beautiful woman smiling at him. It wasn’t Many Paths though. It was She Who Saves Many Lives. Her hair was only flecked with a little gray. Shadow Walker’s tiny hand moved from the dry leaf to a dry seed pod. He heard his little boy’s voice ask the plant, “Thirsty?” He looked up to the kind face of the Shaman and saw her nod. He saw himself bend down and pick up his cup of water from the ground. He lifted it to the leaf and frowned, unsure how to give the plant a drink. She Who Saves Many Lives gently took the cup from his hands and bent down beside him. “Here, Shadow Walker. Here is where the plant drinks.” She slowly poured the water into the ground all around the base of the plant. The soil darkened and turned muddy. He heard his young self ask the Shaman, “Why did you waste the water and not give the plant a drink?” 

She Who Saves Many Lives smiled and said, “I did. Be patient and you’ll see.”  

Shadow Walker shook his head to clear his mind of the clear memory. He turned away from the wall and looked instead at the back of his Throne. He shook his head. He didn’t like sitting up there. It seemed absurdly huge. It was elaborately carved, not only on the front, but here on the back as well. The front and sides at least were beautifully turned out. The back however…? He glanced at Eagle Eyes who had also turned around and she was pointing to a part of the carving that looked like a small house with rectangular windows and a rectangular door. He touched the door and heard a loud creaking behind him. The noise startled them both. Shadow  Walker’s hand flew instinctively to his sword. But no-one else was near. The noise, it became obvious, arose from the grinding of stone rubbing against stone as a hole appeared in the wall behind them. After the noise stopped, the pair peered into the darkness beyond the wall. They each cupped their hands around their eyes and waited for their eyes to adjust. 

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The Myths of the Veritas: The Orange Man

The Myths of the Veritas: The Forgotten Field

The Myths of the Veritas: The First Ring of Empathy

The Myths of the Veritas – Beginning of Book Two

The Myths of the Veritas – Beginning of Book Three

Author Page on Amazon

A Successful Project

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A successful project. 

Who doesn’t like those? 

But what exactly *is* a successful project? 

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Some are quick to reply (and that very quickness might be an indicator of indoctrination more than conscious choice) that a project is successful if it meets its objectives and is on time and within budget. I have to admit that seems logical and tidy. 

In comparing two projects, we might say project A is more successful than project B if project A achieves more objectives in a shorter time with fewer resources.

A little more about objectives however. Does every objective need to be explicitly stated? Or, to put it another way, if an objective seems obvious to most people but it hasn’t been put in writing, then it need not be met?

Suppose I contract someone to build a pool in the back yard and they do indeed build a pool of the proper size and they do it at estimated cost and time frame. Wonderful! But what if, in the process, they made so much noise, I was successfully sued for twice the cost of the pool? The answer is: “Hey, it wasn’t in the contract we couldn’t do it at night and loudly.” ?

Or, if the pool construction allowed water to run under the nearby house and ruin the foundation and the house fell down and killed everyone inside. But “Hey, it’s not in the contract.”?

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Does every aspect of every contract have to be in writing? 

What about the successful projects of life?

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Here are some sample objectives that might be included in every contract. I’d prefer that we would all simply agree to abide by them as members of the human race, but if not, we could boilerplate it I suppose.

You project should, on the whole, provide a positive environment for everyone working there. People should not be harassed, belittled, or needlessly endangered.
People who work on the project will learn new skills.
Your project will not destroy innocent people or their environment. 

Your employees will not have to lie to the public.
If the project is wildly successful in any way, that success should be shared.

There are many more constraints that might be suggested. What do you think? 

If we put too many constraints on people, maybe no-one will never become a multi-billionaire and become too rich to jail. 

I guess I could live with that. 

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Essays on America: The Game

When Greed is the Only Creed

The Orange Man

At Least He’s Our Monster

Stoned Soup

The After Times

The Silent Screams

After All

The Crows and Me

We Won the War!

The Dance of Billions

Somewhere a Bird Cries

Career Advice from Polonius

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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.

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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.”

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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). 

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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.

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More background on “knowing yourself” 

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

The Walkabout Diaries Natural Variety

Where do you draw the line

Your Cage is Unlocked