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.
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 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.
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 they were simply supposed to do 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.
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.
In my early days at IBM Research (1970’s), we were focused on trying to develop, test, or 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, it’s vastly over-simplified. I argued 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 they 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 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.”
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 only took a minute or two. But it critically 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 the agreement in the diagrams. In the “competition” condition, the designer’s bonus depended on how different the two diagrams were.
I ran about half the number of subjects I had planned to run when the experiment was ended by corporate lawyers.
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 the experiment 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?
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.
(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.
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.
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.
This is part of a series on experiences in my career in Human Computer Interaction and some lessons learned.
I joined IBM Research on the winter solstice of 1973. I had earned a Ph.D. in Experimental Psychology from the University of Michigan and for the previous few years, I had managed a research project at Harvard Medical School on the “Psychology of Aging.” At the time, I was married and had three small children. I mention this because I was funded by so-called “soft money” which basically meant that my salary depended on a research grant. I helped write a renewal of the grant but the decision was “deferred”; that is, it was neither funded nor unfunded. Then, it was deferred again. This meant that if the grant were not funded, I would only have a few weeks to find a new job. That seemed far too short so I began to look other places for a job.
Lessons Learned: #1 If you want continuity of personnel in your laboratory, make sure you have overlapping and multiple grants or other sources of income.
In this case, the grant actually was ultimately approved, but by that time, I had already agreed to join IBM Research. That turned out to be fine, by the way. It was a wonderful place to work.
One of the reasons that I got the job at IBM was that I already knew something about computers. I had taken several computer science courses in grad school along with the needed psych courses. More importantly, our “Psychology of Aging” study was run by a PDP-8 and I had programmed the computer to run our suite of experiments and to do data analyses on the results. I had taken a week-long course at DEC in Maynard, Massachusetts on the assembly language, another week-long course on the machine language, and another week-long course actually tracing the circuitry with a probe and oscilloscope. I felt I “understood” the PDP-8 at a fairly deep level.
At IBM, I did not have that familiar machine. Instead, I was connected to a mainframe via a dumb terminal. The first day at IBM, I got my userid and tried to log on to APL (A programming language I had not used before). I tried following the manual but I could not seem to get logged on. After hours of trying, I finally gave up and went down to the computer room and found someone willing to help. I showed him the logon instructions I was trying to follow and he immediately said, “Oh, yeah, that doesn’t work any more. We changed that months ago. Here’s how you need to do it now.” The manual I had may have looked new, but it was out of date.
Lessons Learned: #2 Manuals can be wrong. These days, most are online. But they can still be wrong.
Lessons Learned: #3 Someone who knows how to do something can save you hours with a few minutes of their time.
Of course, it’s more respectful, efficient, and a better learning experience if you can figure it out on your own. But sometimes you can’t. My stumbling block was not due to an error in logic, or a lack of in-depth knowledge. It was simply that the computer center administrators had changed something arbitrary so that the documentation I was given about how to log on for the first time was no longer accurate.
In order to teach myself APL, I wrote a very small program to “predict” how long I was going to live “based on” some behaviors that I was interested in controlling. My main goal was to learn APL. My secondary goal was to motivate myself, for instance, to exercise more, lose weight, and not drink too much alcohol. I had no intention or pretensions of making this prediction “accurate.” If I had been doing a consulting gig for an insurance company setting life insurance rates, for example, I would have given far more attention to see precisely what the real data were and incorporated many more variables into the regression model.
by the way, to a more accurate model than the one I used, but it’s still simple to use. Note that my goal was to motivate myself and so I intentionally exaggerated the impact of those behaviors I was trying to change. I had programmed it. I knew how “bogus” the calculation was — nonetheless — here’s the interesting thing though:
Lessons Learned #4: Even an over-simple model that the user knows is over-simple can still motivate change.
At last we come to the actual project I worked on — the usability and learnability of Query By Example. One of my colleagues, Moshe Zloof, invented the language for relational data bases. He had designed the language but not yet implemented it. I did not immediately test the design; first, I sought to understand it. In seeking to understand it in depth, prior to testing it, the two of us had some sense-making discussions. Moshe improved the design; in particular, our discussions uncovered some ambiguities and inconsistencies that were not at all obvious when he simply gave talks about the design. This brings me to the next lesson learned which has proven true in nearly every study of early stage designs that I’ve been involved with over the course of five decades.
Lessons Learned #5: Don’t just accept a surface description of something; understand it as deeply as you can before designing a study.
In this particular case, it was possible for me to understand it in some depth. Relational data bases and second order logic are things I was capable of understanding. If it had been an interface to running a nuclear reactor or using the artificial heart that Moshe had designed earlier in his career, that would have been a much more difficult task for me.
I wanted to understand, not just the “logic” of Query By Example, but also possible contexts of use. For instance, my manager & I visited Burlington, Vermont to talk with IBMer’s who actually used query languages to understand what was happening in chip production lines. At one point, a particular production line that had been producing nearly 100% perfect chips starting having a much higher error rate. Using their query facility, they were quickly able to diagnose the cause of the change which was a supplier of one of the raw materials using a different source. In turn, this meant a slightly different profile of trace impurities in the substrate. Of course, this is only one example, but to me, understanding something in depth means not only understanding its internal logic but also understanding real users, their real tasks, and their context of use.
I won’t go into all the details of the pencil & paper study or the results. High School students and then college students were taught the basics of the language and then given a simple relational data base and a set of questions stated in English which they had to translate into Query By Example. Briefly, the bottom line was that Query By Example was easy to learn and easy to use. However, there were still questions that people had difficulty with. In analyzing the data and doing some further experiments, the difficulties that people tended to have, stemmed not so much from Query By Example per se, but from what I much later came to call “labelism” — that is, confusing a label with the thing that label refers to.
Here’s a simple example of the type of confusion we saw. In Query By Example (and other query languages) there is usually an OR operator and an AND operator. (These operators can be important for doing advanced queries with search engines as well). If you are interested in getting a list of pets you might adopt and you’re willing to adopt dogs or cats, you might ask for “cat OR dog.” If you only want long-haired cats, you might ask for “cat” AND “long hair.”
English, however, can be tricky.
If you and I (as opposed to you and a query language) are having a conversation, you might say, “I hear there are many pets that need to be adopted.”
I say, “Yes, there are all kinds of pets. There are snakes, dogs, turtles, rabbits, cats…”
You say, “Let me stop you right there. I’m only interested in adopting cats and dogs. Those are the only animals I’d want to adopt.”
See what you said there? You exact words included: “…cats and dog.” If you put “Cats AND dogs” into a query against the data base of available pets, however, you will get the null set (that is, nothing) back. There are no animals who are both cats and dogs! (Though my part Main Coon cats do play fetch like dogs).
When people were presented with an English statement that included the English word “and” — regardless of the actual syntax and context, some of them had difficulty using the OR operator. If instead, the query in English had set up like this: “Oh, I don’t want reptiles. I’d be happy with adopting a cat or a dog, however” then, they’d have no problem translating it into the OR operator in the query language.
Lessons Learned: #6 Sometimes the difficulty people have in using a product, a service, or a prototype is not due to the interface details but with the structure of the task, their background, and their training.
By analogy, you will not allow me to beat Nadal or Djokovic at tennis by giving me a better tennis racquet! (Although if you gave one of them a toothpick for a tennis racquet, I might have a shot).
That sounds obvious and even absurd, but I promise you, some companies get so greedy that they want you to design a system that allows people who do not understand the task and have minimal background and training to nonetheless be able to perform that task.
One example you may have run into is having “help desk” personnel who have no understanding of a product go through a script to help you “solve your problem.” Sometimes, it works. But many times it doesn’t. When it does not work, you might not be able to “fix” the system by making the interface to the scripts easier to use for the help desk folks. The problem is much deeper (in some cases). Yes, a really bad interface can make it difficult even for a really knowledgeable and capable person to do the job. But often, even a really great interface cannot always substitute for actual expertise.
“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. The yellow sun would no longer sparkle like stars after a rain. 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.”
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 her 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 to 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.”
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.”
“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 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.”
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.”
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 too 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. Tree Vines has already told me so. When that happens….?”
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. Both of which 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.
Our garden has plenty of flowers and plenty of bees. Obviously, the two are not unrelated. The flowers (and fruit trees) do better because there are so many bees. And the bees do better because there are so many flowers. And, here I am — mainly not working so hard as either one but enjoying them both.
It was not always so. As a child, I was stung a few times by bees and wasps and became quite wary of them. At one point, my family moved and my walk to school the very first day took me through a field of September wildflowers that was filled with bees and wasps of various types. (By the way, there are noticeably fewer insects in the world than when I was a child.) Anyway, I walked through that field very carefully, afraid with each step that I might get stung. Then, one day as I stood there calculating whether to slowly move a goldenrod stem with its huge blue wasp or whether it would be better to wait until the wasp flew away. But even if I waited, it was pretty likely that some other species of stinging insect would soon alight.
And then, it happened.
It occurred to me that I was causing myself more pain by worrying about getting stung than the pain would be if I actually got stung. From then on, I still tried not to annoy the bees, but I walked through the field swiftly and without fear.
I never did get stung.
Fast forward nearly 70 years, and I now talk to the bees in the garden when I happen upon one. They are fun to watch. In their own way, they are every bit as remarkable in their performances as is a professional dancer, or a professional tennis player, or an Olympic gymnast. Just as required by those humans, their beauty is crafted in three dimensions and in real time. The bee, however, is simultaneously working six limbs, not four; she is also working her antenna, and often her mandibles as well.
The other day, I was out taking pictures of flowers and I happened to notice a honeybee fly into the thick green foliage of our mulberry bush. I said to her, “Well, you’re a bit late. The flowers are all gone and now there’s fruit but it’s not ripe yet.” Then, I began to wonder whether she was there simply to take a nap. On several occasions, I had come across bees napping in flowers. But no. As I began to watch her, it was apparent that she was quite busy doing…
…something. But what? I had never seen a bee act like this. Why not watch this short movie and see what you think she’s up to? Then, you might want to watch again. This time, instead of doing your detective work, just enjoy the show. Imagine this cute little bee as a professional dancer or athlete. Revel in her speed, rhythm, coordination and beauty.
Then come back, to learn a little more about bees.
I posted the movie on various fora that know about bees and from looking at the answers posted (thank you!) and reading on-line, I have come to the conclusion that she is most likely collecting plant resin that will be helpful in producing propolis. Have you ever heard of propolis? I had not. Here’s a bit about it.
Propolis is a natural resinous mixture produced by honey bees from substances collected from parts of plants, buds, and exudates. Due to its waxy nature and mechanical properties, bees use propolis in the construction and repair of their hives for sealing openings and cracks and smoothing out the internal walls and as a protective barrier against external invaders like snakes, lizards, and so forth, or against weathering threats like wind and rain. Bees gather propolis from different plants, in the temperate climate zone mainly from poplar. Current antimicrobial applications of propolis include formulations for cold syndrome (upper respiratory tract infections, common cold, and flu-like infections), wound healing, treatment of burns, acne, herpes simplex and genitalis, and neurodermatitis.
Look at that list of uses of propolis! That alone should encourage us to want to save the bees. Not to mention that they benefit us by making our world yummier and more beautiful! In reading about bees and propolis, I also discovered that the worker bees in a hive have a regular sequence of jobs. They are not just foragers. They are cleaners, child-bee care workers, builders, defenders, and finally foragers. Here’s a link that describes that and more about honeybees.
When it comes to life, the more I learn about a particular type of animal or plant, the more remarkable I realize it is. And, that does not just apply to the honeybee. It’s true of all life. Recently, scientists have discovered that trees communicate and cooperate in very sophisticated ways! We know honeybees communicate information to other members of the tribe about food sources, plentifulness, and type. Do they tell stories as well? In the middle of the night, right before the hive goes to sleep, do the foragers tell their tales about the joys and wonders and dangers of the world outside the hive to the janitors, nurse-maids, plumbers, and plasterers? When a bee graduates to hive defender, that is when they have their first glance at the outside world. While they’re doing that — defending the hive — are they eager with anticipation of the time that they will become foragers? Caterpillars can be taught things that the butterfly remembers.
The pleasure of discovery is not only about wild forms; it is also true of people, all of whom are filled with remarkable stories. Not everyone shares their stories, and some people lie about their experiences. I find, however, that the vast majority of folks are willing to recount their experiences fairly truthfully.
If you watch and listen, there are many-splendored somethings to be gleaned from every story.
You may or may not have heard of the so-called “bystander effect.” It refers to the observation that, in some circumstances, any particular person is less likely to help someone else when there are many others who could help. It’s also of some interest that most people believe that they will make their own decision independently of what others do.
In some ways, the feeling that, after all, you are only one person, and so what you do cannot possibly impact climate change much, might be a close cousin. It’s true that if everything else in the world stays the same and you stop driving your car 10 miles to work every day and instead decide to ride your bike, it won’t have a huge impact on global climate change, but it will have some. Your actions may not save a million lives, but they could save one.
More importantly, why did your mind skip right by that premise I snuck in there? “If everything else in the world stays the same…” Why would it stay the same? When you think about it, it’s fairly well impossible that everything else would stay the same. For one thing, you would be fitter because of riding the bike. For another thing, you’d likely be in a better mood. People at work would notice that you’re riding a bike and you would end up in conversations about it. These conversations could lead to others. You’d be having people wonder why you did that. Some of them might try too.
Those are just a few of the predictable consequences. Of course, you’d be impacting the world differently all the time. There’s no way to predict all the “Butterfly Effects” you’d be causing without your knowledge. In general, however, if your actions are kinder to the ecosystem, the ecosystem will be nicer to you.
When I was transitioning from 4th to 5th grade, our family moved to an area of new development and our little neighborhood was surrounded by acres of woods and fields. In the woods immediately behind our house, mayapples blanketed the rich forest floor beneath the tall canopy of oaks, ashes, and cherry trees, all overhung by wild grape vines. I loved the forest! But as an eleven-year old, it also seemed that my friend Wilbur and I would be required to destroy our “enemies” (i.e., the Mayapples) with our wooden “swords” (i.e., broken branches with the bark stripped off). And destroy them we did.
The next year, the mayapples were “replaced” with thorn bushes — mainly blackberry and black raspberry but there were some wild roses and cat briers in the mix. Coincidence? Perhaps. We continued to fight these hardier “enemy warriors” and every year, unlike the mayapples, they kept coming back for more, though these berry bushes never bore any fruit.
Consider “The Golden Rule” — “Do Unto Others As You Would Have Them Do Unto You.” It’s the right thing to do. But it’s also a very practical thing to do. If you are nice to people, then by and large, they are more likely to be nice back to you. Why wouldn’t it be the same with other species on the whole? I’m not suggesting that it’s true in every case. No matter how nice you are to the mosquitoes that bite you, they are unlikely to throw a party for you even if you let them suck you dry!
I’m happy to say that I soon outgrew that pre-teen phase of cutting down vegetation for the sheer “joy” of it. So, I don’t have many stories that illustrate how being intentionally unkind to nature came back to bite me.
However, I do know that when it comes to honeybees, if one of them stings you, crushing the offender could well get you in worse trouble as could flailing about swatting at them. Decades after the mayapple episode described above, I went on a hike on “Turkey Mountain” with my son-in-law and some of my grandchildren when one of the boys stepped in a bee’s nest. I was holding my grand-daughter and didn’t have the option of trying to run or trying to flail at them. I just stood still. I didn’t get stung nor did my grand-daughter. But everyone else who was swatting at the bees, did get stung.
In general, it makes sense to me that if you are kind to nature, you will generally experience more pleasure yourself. Since humans are social animals, your kindness to nature will typically not go unnoticed by others. Though there might be some few perverse folks who will do the opposite of what you do, most will follow your lead. Humans are social animals. Except for pre-teen boys and a few spoiled sociopaths, most people are predisposed to be nice to other forms of life. Life competes with other Life. But Life also collaborates and cooperates with Life. Big time. And, one of the many examples is that people collaborate and cooperate. That is the natural tendency and they must be manipulated to instead be needlessly belligerent. A more natural stance is to see what others are doing that has a good result and join in.
For several years, my wife & I attended the Newport Folk Festival. Like most people, I love music, but I especially love outdoor concerts because I can dance to the music. Most of our ferryboat trips to Fort Adams State Park were accompanied by spectacular summer sunshine. Hot sunny weather meant a great time to dance to the music and occasionally take a short dip in the water to cool off.
One summer day, however, our lucky streak of sunny weather came to an end. Everyone at the festival, including our little group, huddled and shivered under their umbrellas and leaky raincoats. You think a raincoat is pretty effective at keeping the water out. But that’s because you’re judging its effectiveness on not getting wet when you walk from your home to your car and your car to your workplace or the drug store. Under those circumstances, they work well. But when you sit for hours in a downpour, you’ll get wet, raincoat or no raincoat.
So, after about an hour and a half, the thought came into my head: “Hey! I came here to dance. I’m soaking wet anyway. I’m going to dance!” I stripped off to my bathing trunks and do what I came there to do: dance. Why let the rain stop me?
I enjoyed myself. After about a half hour, a few others began to dance. Performers on the stage commented favorably on the spirit of the dancers. More joined us. Within a few hours, hundreds of people had joined in the joy. At some point, I felt a tap on my shoulder. I turned around to see a microphone in my face and a large TV camera. At that time, I had the exulted title of “Executive Director” so my first thought was to wonder whether my management chain would see this interview with me in my bathing trunks, and if so, what they would think of it. In moments like that, it seems to me, the best thing to do is simply continue to embrace the moment. So, I simply told the truth about what I was doing and why; that I came to dance and I was enjoying it; that there was no point *wishing* it wasn’t pouring down rain, and that instead, it was more enjoyable to embrace the rain and make it part of the dance along with the music.
If scores of people pile on to crazy and easily disprovable conspiracy theories, wouldn’t many more people pile on to something that is positive and joyous and life-affirming?
If you make some small change that is pro-planet, wouldn’t that tend to induce others to do the same? And, if they did, wouldn’t that tend to induce still others to do the same?
You may or may not be on the nightly news and induce still more people to change their attitude or behavior, but you’ll certainly have a positive influence on those in your immediate vicinity.
If denial of reality can spread like a pandemic, why not small life-affirming changes in the behavior of your fellow human beings?