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The Great Race to the Finish!

Big Zig-Zag Canyon

You Fool!

Horizons University

How the Nightingale Learned to Sing

Comes the Dawn

Dog Trainers

Where Does Your Loyalty Lie?

The Dance of Billions

Roar, Ocean, Roar

Imagine All the People

Your Cage is Unlocked

I Went in Seeking Clarity

10 Wednesday Dec 2025

Posted by petersironwood in AI, creativity, HCI, psychology, Uncategorized, user experience

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AI, Artificial Intelligence, coding, parallel programming, problem formulation, problem framing, problem solving, programming, technology, thinking, tools, X10

“I stopped by the bar at 3 A.M.
To seek solace in a bottle or possibly a friend
And I woke up with a headache like my head against a board
Twice as cloudy as I’d been the night before
And I went in seeking clarity” — Lyrics from The Indigo Girls: Closer to Fine

If you think programming is cognitively difficult, try parallel programming. It is generally harder to design, to code, and to debug than its sequential cousin. One of the fun projects I worked on at IBM Research was on the X10 language which was designed to enable parallel programmers to be more productive. Among other things, I fostered community among X10 programmers and used analytic techniques to show that X10 “should be” more productive. Although these analytic techniques are very useful, we also wanted to get some empirical data that the language was, in actuality, more productive.

Photo by Dominika Greguu0161ovu00e1 on Pexels.com

One part of those empirical studies involved comparing people doing a few parallel programming tasks in X10 to those using a popular competitor. But, like many other “chicken and egg” problems, there were no X10 programmers (other than the inventors and their colleagues). I was part of a team who travelled to Rice University in Houston. The design called for one group to spend a chunk of time learning X10 (perhaps half a day) and another chunk of time coding some problems.

Besides the three behavioral scientists like me who were there to make observations, there were also three high-powered Ph.D. computer scientists present who would teach the language. Programmers tend to be very smart. Parallel programmers tend to be very very smart. People who can invent better languages to do parallel programming? You do the math.

Anyway, after the volunteers students had arrived, one of the main designers of the language began to “teach them” X10.

But — there was a problem.

The powerpoint presentation designed to teach the students X10 was far too blurry to read!

Immediately, the three computer scientists tried to issue commands to the projector to put the images in focus. Nothing worked. The three of them began a fascinating problem solving conversation. The conversation concerned what communication protocol(s) among the PC, the projector, and the controller was the likely source of the problem. I suppose it might not have been fascinating to everyone, but it was to me. First, it fascinated me because I was learning something about computer science and communication protocols. Second, it fascinated me because I loved to watch these people think. I suppose many of the advanced computer science students who were in this classroom to learn X10 also found it interesting. Third, I found it fascinating because my dissertation was about human problem solving and I’ve been interested in it ever since.

But the study itself had completely stalled.

After a few minutes of fascinating conversation that did nothing to focus the images, something possessed me to walk over to the projector and turn the lens by hand. The images were immediately clear and the rest of the experiment continued.

The three computer scientists had “framed” the problem as a computer science problem and I found the discussion that sprang from that framing to be fascinating. But one of the part-time jobs I had had as an undergraduate was as a “projectionist” at Case-Western, and it was that experience that allowed me to try framing the problem differently. All of us have huge reservoirs of experience outside of our professional “training” and those experiences can sometimes be important sources of alternative ways to frame a problem, issue, or situation.

———————————-

Essays on America: The Update Problem

Essays on America: The Stopping Rule

Where Does Your Loyalty Lie?

Labelism

Tools of Thought

Stoned Soup

The First Ring of Empathy

Travels with Sadie: Teamwork

The Primacy Effect and The Destroyer’s Advantage

I Say: Hello! You Say: “What City Please?”

09 Tuesday Dec 2025

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

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art, communication, conversation, Design, efficiency, HCI, human factors, photography, primacy, problem framing, problem solving, sensemaking, technology, thinking, UX

In the not so distant past, people would often call directory assistance operators. These operators would find a number for you. For an additional charge, they would dial it for you. In fact, this was a very commonly used system. Phone companies would have large rooms filled with such operators who worked very hard and very politely, communicating with what was often a hostile and irrational public.

Customer: “I have to get the number of that bowling alley right near where the A&P used to be before they moved into that new shopping center.”

Operator: “Sir, you haven’t told me what town you’re in. Anyway…”

Customer: “What town?! Why I’m right here in Woburn where I’ve always been!”

There were so many operators that the phone companies wanted their processes to be efficient. Operators were trained to be friendly and genial but not chatty. The phone companies searched for better keyboards and better screen layouts to shave a second here or there off the average time it took to handle a call.

There are some interesting stories in that attempt but that we will save for another article, but here I want to tell you what made the largest single impact on the average time per call. Not a keyboard. Not a display. Not an AI system.

It was simply changing the greeting.

Photo by eberhard grossgasteiger on Pexels.com

Operators were saying something like: “New England Telephone. How can I help you?”

After our intervention, operators instead said, “What city please?” It’s shorter and it’s takes less time to say. But the big change was not in how long the operator took to ask the question. The biggest savings was how this change in greeting impacted the customer’s behavior.

When the operator begins with “How can I help you?” the customer, or at least some fraction of them, are put into a frame of mind of a conversation. They might respond thusly:

“Oh, well, you know my niece is getting married! Yeah! In just a month, and she still hasn’t shopped for a dress! Can you believe it? So, I need the number for that — if it were up to me, I would go traditional, but my niece? She’s — she’s going avant-garde so I need the number of that dress shop on Main Street here in Arlington.”

Photo by Tuu1ea5n Kiu1ec7t Jr. on Pexels.com

With the “What City Please?” greeting, the customer was apparently put into a more businesslike frame of mind and answers more succinctly. They now understand their role as proving information in a joint problem solving task with the operator. A typical answer would now be:

“Arlington.”

“In Arlington, what listing?”

“Dress shop on Main Street.”

The way in which a conversation begins signals what type of conversation it is to be. We know this intuitively. Suppose you walked up to an old friend and they begin with: “Name?” You would be taken aback. On the other hand, suppose you walk up to the line at the DMV and the clerk says, “Hey, have you seen that latest blog post by J. Charles Thomas on problem framing?” You would be equally perplexed!

Conversation can be thought of partly as a kind of mutual problem solving exercise. And, before that problem solving even begins, one party or the other will tend to “frame” the conversation. That framing can be incredibly important.

Even the very first words can cause someone to frame what kind of a conversation this is meant to be.

Words matter.

https://petersironwood.com/2018/02/13/context-setting-entrance/

Cancer Always Loses in the End

After the Fall

The Crows and Me

Come Back to the Light

Imagine All the People…

Roar, Ocean, Roar

The Dance of Billions

How the Nightingale Learned to Sing

Travels with Sadie

The First Ring of Empathy

Donnie Visits Granny!

You Must Remember This

The Walkabout Diaries: Bee Wise

The Pandemic Anti-Academic.

What about the butter dish?

Problem Framing: Good Point!

08 Monday Dec 2025

Posted by petersironwood in AI, America, design rationale, HCI, management, psychology, story, Uncategorized, user experience

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AI, art, life, politics, problem finding, problem formulation, problem framing, problem solving, technology, thinking, tools, USA

You have probably heard variations on this old saw, “To a hammer, everything looks like a nail.” I’ve also heard, “If you have a hammer, everything looks like a nail.” There is also this popular anecdote:

One night, I took my dog out for a walk and I noticed one of my neighbors under a nearby street lamp crawling around on his hands and knees, apparently looking for something. I walked over and asked, “What are you looking for?”

“My car keys!” He replied.

I have pretty good vision, so I helped him. I didn’t see any car keys so after a minute or so I asked, “Where exactly did you lose your keys?”

He stood up, cracked his back, and pointed back to a nearby park. “Over there.”

“Over there?! Then, why are you looking under the street lamp? Why aren’t you looking over at the park entrance?”

“Oh, that’s obvious! The light is so much better here!”

For a time, I had to very interesting and challenging job in the mid 1980’s at IBM Headquarters to try to get the company to pay more attention to the usability of their products and services. As a part of this, I visited IBM locations throughout the world. At one fabrication plant, our tour guide took us by an inspection station. This was not an inspection statement for chips. It consisted of one person whose job was to look through a microscope and make sure that two silver needles were perfectly aligned.

After we left the station, our tour guide confided that they were strongly considering replacing the person with a machine vision system. The anticipated cost would be substantial, but they hypothesized that the system would be more accurate and faster. It was, our host, insisted, just the nature of humans to be slow and inaccurate.

Maybe.

When I looked at the inspection station however, with my background in human factors, I had a completely different impression of the situation. The inspector sat on a fixed height stool and had to bend his neck at an absurd angle to look into the microscope. He was trying to align these silver needles against a background that had almost the same hue, brightness and saturation.

Other than blindfolding the man, I’m not sure what they could have done to make the task more unnecessarily difficult. I suggested, and eventually, they implemented, a few inexpensive ergonomic changes and time and accuracy improved.

Like other companies in the technology segment, IBM often saw problems as ones that could be solved by technology. At that time, technology systems was their main business. Since then, they have expanded more fully into software and services. In fact, those services now include experience design.

If you find yourself enamored of technology in general, or some specific class of technology such as machine vision, speech recognition, or machine learning, you might overlook much simpler and cheaper ways to solve problems or ameliorate situations. Of course, you might lose some revenue doing that, but you can also win long term customer loyalty.

Even if you are a hammer, everything is not a nail.

That applies as well to User Experience. You might design the most wonderful UX imaginable for a particular product or service. But if it is shoddily made so that it is error prone; if it lacks important functionality; if the sales force is inept; or if service is horrible, those failures can completely overwhelm all the good work you have done on the UX. Because of the nature of UX, you might learn important knowledge or suggestions for other functions as well. It often requires finesse to have such suggestions taken seriously, but with some thought you can do it.

During my second stint at IBM, I worked for a time in a field known at that time as “Knowledge Management.” One of our potential clients was a major Pharma company who felt that their researchers should do a better job of sharing knowledge across products. They wanted us to design a “knowledge management system” (by which they meant hardware and software) to improve knowledge sharing.

Simply building a “Knowledge Management System” would be looking under the streetlamp. They knew how to specify a technology solution from IBM and have it installed.

However — they were unwilling to provide any additional space, time, or incentives for their employees to share knowledge with their colleagues!

Photo by Chokniti Khongchum on Pexels.com

They were convinced that technology would be the silver bullet, the solution, the answer, the Holy Grail, the magic pill. They viewed technology as less disruptive than it would have been to change employee incentives, or space layout, or give them time to actually learn and use the technology system.

This reaction to “knowledge management” was not unique. It was common.

To me, this seems very similar to the notion that health problems can all be solved with a magic pill. What do you think?

—————————————

Since originally writing, we have had the spectacle of DOGE: Destroying Our Government’s Effectiveness under the excuse of making it “more efficient.” It might be (as I strongly suspect) that the destruction was quite intentional. It might be (as some think) that it was accidental. In either case, the result was predictable because the method was guaranteed not to work to actually make things more efficient. If you really wanted to do that, you would take the time to understand a system before trying to redesign it. You would identify all relevant stakeholders and get their input. You would not redesign a system using a gang of young hackers but instead use an interdisciplinary team of experienced experts. You would check out your redesign both with those who were doing the work and with at least one group who were not familiar but had similar experience. Then, on the basis of feedback, you would redesign. When you were sure that you had the design right, you would not then institute it everywhere but in one small trial installation.

There’s a pill for that.

The invisibility cloak of habit.

Process re-engineering comes to Baseball

E-Fishiness in Government

Author Page on Amazon

Tools of Thought

Reframing the Problem: Paperwork & Working Paper

04 Thursday Dec 2025

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

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AI, ethics, leadership, life, philosophy, politics, problem finding, problem formulation, problem framing, problem solving, thinking, truth

Reframing the Problem: Paperwork & Working Paper

This is the second in a series about the importance of correctly framing a problem. Generally, at least in formal American education, the teacher gives you a problem. Not only that, if you are in Algebra class, you know the answer will be an answer based in Algebra. If you are in art class, you’re expected to paint a picture. If you painted a picture in Algebra class, or wrote down a formula in Art Class, they would send you to the principal for punishment. But in real life, how a problem is presented may actually be far from the most elegant solution to the real problem.

Doing a google search on “problem solving” just now yielded 208 million results. Entering “problem framing” only had 182 thousand. A thousand times as much emphasis on problem solving as there was on problem framing. [Update: I redid the search today, a little over three years later. On 3/6/2024, I got 542M hits on “problem solving” and 218K hits on “problem framing” — increases in both but the ratio is even worse than it was in 2021] [Second update: I did the search today, Dec. 4th, 2025, and the information was not given–but that’s the subject of a different post].

Let’s think about that ratio of 542 million to 218 thousand for a moment. Roughly, that’s 2000 to 1. If you have wrongly framed the problem, you not only will not have solved the real problem; what’s worse, you will have often convinced yourself and others that you have solved the problem. This will make it much more difficult to recognize and solve the real problem even for a solitary thinker. And to make a political change required to redirect hundreds or thousands will be incalculably more difficult.

All of that brings us to today’s story. For about a decade, I worked as executive director of an AI lab for a company in the computers & communication industry. At one point, in the late 1980’s, all employees were all supposed to sign some new paperwork. An office manager called from a building several miles away asking me to have my admin work with his admin to sign up a schedule for all 45 people in my AI lab to go over to his office and sign this paperwork as soon as possible. That would be a mildly interesting logistics problem, and I might even be tempted to step in and help solve it. More likely, if I tried to solve it, some much brighter & more competent colleague would have done it much faster.

Photo by Charlie Solorzano on Pexels.com

But why?

Why would I ask each of 45 people to interrupt their work; walk to their cars; drive in traffic; park in a new location; find this guy’s office; walk up there; sign some paper; walk out; find their car; drive back; park again; walk back to their office and try to remember where the heck they were? Instead, I told him that wasn’t happening but he’d be welcome to come over here and have people sign the paperwork.

You could make an argument that that was 4500% improvement in productivity, but I think that understates the case. The administrator’s work, at least in this regard, was to get this paperwork signed. He didn’t need to do mental calculations to tie these signings together. On the other hand, a lot of the work that the AI folks did was hard mental work. That means that interrupting them would be much more destructive than it would to interrupt the administrator in his watching someone sign their name. Even that understates the case because many of the people in AI worked collaboratively and (perhaps you remember those days) people were working face to face. Software tools to coordinate work were not as sophisticated as they are now. Often, having one team member disappear for a half hour would not only impact their own work, it would impact the work of everyone on the team.

Quantitatively comparing apples and oranges is always tricky. Of course, I am also biased because my colleagues are people I greatly admire. Nonetheless, it seems obvious that the way the problem was presented was a non-optimal “framing.” It may or may not have been presented that way because of a purely selfish standpoint; that is, wanting to do what’s most convenient for oneself rather than what’s best for the company as a whole. I suspect that it was more likely just the first idea that occurred to him. But in your own life, beware. Sometimes, you will mis-frame a problem because of “natural causes.” But sometimes, people may intentionally hand you a bad framing because they view it as being in their interest to lead you to solve the wrong problem.

Politics, of course, takes us into another realm entirely. People with political power may pretend to solve one problem while they are really following a completely different agenda. One could imagine, for instance, a head of state claiming to pursue a war for his people when he’s really doing it to keep in power. Or, they could claim they are making cities safe by deploying troops when they are really interested in suppressing the vote in areas that can see through his cons. Or, a would-be dictator could claim they are spending your tax dollars to make government more efficient when that has nothing to do with what they are *actually* doing–which is to collect data on citizens and make the government ineffective in order to have people lose confidence in government and instead invest in private solutions.

Even when people’s motivations are noble or at least clear, it is still quite easy to frame a problem wrongly because of surface features. It may look like a problem that requires calculus, but it is a problem that actually requires psychology or it may look like a problem that requires public relations expertise but what is actually required is ethical leadership.

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A Pattern Language for Collaboration and Cooperation

The Myths of the Veritas: The First Ring of Empathy

Essays on America: The Stopping Rule

Essays on America: The Update Problem

My Cousin Bobby

Facegook

The Ailing King of Agitate

Dog Trainers

The Doorbell’s Ringing! Can you get it?

02 Tuesday Dec 2025

Posted by petersironwood in creativity, design rationale, psychology, story, Uncategorized, user experience

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books, problem finding, problem formulation, problem framing, problem solving, story, thinking

After a long day’s work, I arrived home to a distraught wife. Not, “Hi, sweetheart” but “This doorbell is driving me crazy!”

Me: “What doorbell? What are you talking about?”

People differ in how they perceive the world around them. In my case, for instance, I’m very easily distracted by movement in my visual field. Noise can be annoying, but it rarely rises to that level. For instance, when TV commercials come on, I simply “tune them out” and instead tune in to my own thoughts. My high frequency hearing isn’t too great either. So, at first, I didn’t understand what my wife was referring to.

Beep.

Photo by Luisa Fernanda Bayona on Pexels.com

“That! That doorbell beep!”

Ah, now I understood. And, there it went again. Once I knew what to listen for, I had to agree it was annoying though much more annoying to my wife because she’s more tuned in to sound than I am and her ability to hear high frequencies is also better.

She then upped the ante. “I have to leave. I can’t stand it! You have to make it stop!”

I looked at the wall between our entryway and the kitchen. That’s where the doorbell ringer was. I unscrewed a couple of screws and removed the housing. Inside was the actual doorbell and three wires. A quick snip should at least stop the noise until we figured out a more permanent fix. I sighed. I suspected we would have to buy a new doorbell. Then, I laughed a bit as the Hollywood scenes from a hundred movies flashed before my eyes:

The Hero finds the bomb, with its conveniently placed timer, but it’s counting down 30 seconds, 29, 28. He has to cut to cut a wire! But which one!?

The consequences of my error would not be so great. Still…So, I cut the black wire.

BEEP! BEEP!

OK. I cut the red wire.

BEEP! BEEP!

OK. I cut the green wire, the last wire. I was having trouble understanding why it would be necessary to cut all three wires. But whatever. I had now cut all three wires.

BEEP! BEEP!

??

Electrical circuits don’t work by magic. How can the doorbell be beeping when it has no power?

It can’t.

It wasn’t the doorbell at all.

Months earlier, my wife & I had attended a Dave Pelz “Short School” for putting, chipping, and sand shots. At that course, we received a small electronic metronome — about the size of a credit card. The metronome was to be used to help make sure you had a consistent rhythm on your putting stroke. Since the course, the metronome had sat atop our upright piano. Apparently, one of the cats had turned it on and then slapped it onto the floor behind the piano. The sounding board both amplified the sound and made it harder to localize. Eventually, we tracked it down, fished out the metronome from behind the piano and clicked it off. Problem solved.

Except for the non-functional doorbell.

I had initially “solved” the wrong problem. I had solved the problem of the mis-firing doorbell by cutting all the wires. That was not the problem. I had jumped on to my wife’s formulation and framing of the problem. There are plenty of times in my life when I had solved the wrong problem without any help from someone else. This isn’t a story about assigning blame. It’s a story about the importance of correctly solving the right problem.

Photo by Karolina Grabowska on Pexels.com

It is very easy to get led into solving the “wrong” problem.

In the days ahead, I will relate a few more examples.

———————————————

What about the Butter Dish?

Index to “Thinking tools”

Wednesdays

Labelism

The Update Problem

Where does your loyalty lie?

The stopping rule

Business Process Re-engineering

Measure for Measure

01 Monday Dec 2025

Posted by petersironwood in AI, essay, psychology, science, Uncategorized

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art, context, decision making, Democracy, framing, HCI, photography, politics, problem formulation, problem framing, problem solving, technology, thinking, Travel, truth, USA, UX

(More or Less is only More or Less, More or Less)

Confusing. I know. Let’s unpack.

We like to measure things. And, generally, that can be a very good thing. Once we measure and quantify, we can bring to bear the world’s most incredible toolbox of mathematical, engineering, and scientific methods. However…

It often happens that we can’t really measure what we’d like to measure so instead we measure something that we can measure which we imagine to be a close cousin to what we’d really like to measure. That’s still not a bad thing. But it’s risky. And it becomes a lot more risky if we forget that we are measuring a close cousin at best. Sometimes, it’s actually a distant cousin.

Here’s an example. Suppose a company is interested in the efficient handling of customer service calls (who isn’t?). A typical measure is the average time per call. So, a company might be tempted to reward their Customer Service employees based on having a short average time per call. The result would be that the customer would get back to whatever they were doing more quickly. AND — they wouldn’t have to be on hold in the service queue so long because each call would be handled, on average, more quickly. Good for the customer. The customer service reps would be saving money for the company by answering questions quickly. Some of the money saved will (hopefully) mean raises for the customer service reps. It’s a win/win/win!

Or is it?

Imagine this not unlikely scenario:

The managers of the CSR’s (customer service reps) say that there’s a big push from higher management to make calls go more quickly. They may hint that if the average service time goes down enough, everyone will get a raise. Or, they might set much more specific targets to shoot for.

In either case, the CSR’s are motivated to handle calls more quickly. But how? One way might be for them to learn a whole lot more. They might exchange stories among themselves and perhaps they will participate in designing a system to help them find relevant information more quickly. It might really turn out to be a win/win/win.

On the other hand, one can also imagine that the CSR’s instead simply get rid of “pesky” users as quickly as possible.

“Reboot and call back if that doesn’t work.”

“Sounds like an Internet issue. Check your router.”

“That’s an uncovered item.”

“What’s your account number? Don’t have it? Find it & call back.”

With answers like this, the average time to handle a call will certainly go down!

But it won’t result in a win/win/win!

Users will have to call back 2, 3, 4 or even more times to get their issues adequately resolved. This will glut the hold queues more than if they had had their question answered properly in the first place. Endlessly alternating between raspy music and a message re-assuring the customer that their call is important to company XYZ, will not endear XYZ’s customers to XYZ.

Ultimately, the CSR’s themselves will likely suffer a drop in morale if they begin to view their “job” to get off the phone as quickly as possible rather than to be as helpful as possible. Likely too, sales will begin to decline. As word gets around that the XYZ company has lousy customer service and comparative reviews amplify this effect, sales will decline even more precipitously.

There are two approaches executives often take in such a situation.

Some executives (such as Mister Empathy) may be led to believe that quantification should be less emphasized and the important thing is to set the right tone for the CSR’s; to have them really care about their customers. Often, the approach is combined with better training. This can be a good approach.

Some executives (such as Mister Measure) may be led to believe that they need to do more quantification. In addition to average work time, measures will look at the percentage of users whose problem is solved the first time. Ratings of how effective the CSR was will be taken. Some users might even be called for in-depth interviews about their experience. This can also be a good approach.

There is no law against doing both, or trying each approach at different times or different places in order to learn which works better.

There is a third approach however, which never has good results. That is the approach of Mister Misdirect.

Mister Misdirect’s approach is to deny that there is an issue. Mister Misdirect doesn’t improve training. Mister Misdirect doesn’t put people in a better frame of mind. Mister Misdirect does not add additional measures. Mister Misdirect simply demands that CSR’s continue to drive down the average call time of individual calls and that sales go up! In extreme cases, Mister Misdirect may even fudge the numbers and make it appear that things are much better than they really are. Oh, yes. I have seen this with my own eyes.

Unfortunately, this way of handling things often makes Mister Misdirect an addict. Once an executive starts down the path of making things worse and denying that they did so, they are easily ensnared in a trap. Initially, they only had to take responsibility for instituting, say an incomplete measure and failed to anticipate the possible consequences. But now, having lied about it, they would have to not only admit that they caused a problem, but also that they lied about it.

The next day, when executive wakes up, they have a choice:

1. Own up

2. Continue to deny

If they own up, the consequences will be immediately painful.
If they continue to deny, they will immediately feel relieved. Of course, if they have surrounded themselves with lackeys, they will feel more than simply relieved; they will feel vindicated or even proud. It’s not a “real pride” of course. But it’s some distant relative, I suppose.

For a developer, UX person — or really any worker in an organization, the lesson from this is to anticipate such situations before they happen. If they happen anyway, try to call attention to the situation as quickly as possible. Yes, it may mean you lose favor with the boss. If that is so, then, you really might want to think about getting a new boss. Mister Misdirect will always ultimately fail and when he does, he will drag down a work team, a group, a division, or even an entire company. Mister Misdirect has one and only one framework for solving problems:

Try whatever pops into consciousness.

If it works, take the credit.

If it fails, blame an underling.

But the real fun begins when he takes credit for something and then it turns out it was really a failure. Then, there is only one choice for Mister Misdirect and that is to claim that the false victory was real. From there on, it is Lose/Lose/Lose.

—————————————————-

Pattern Language: “Reality Check”

The Truth Train

————————————

Relevant essays, poems, & fiction about the importance of speaking truth to power:

The Pandemic Anti-Academic

How The Nightingale Learned to Sing

Process Re-Engineering Comes to Baseball

——————————————————-

Posts on Problem Framing:

How to Frame Your Own Hamster Wheel

Wordless Perfection

Problem Formulation: Who Knows What?

I Went in Seeking Clarity

I Say Hello

Problem Framing: Good Point

Reframing the Problem: Paperwork & Working Paper

The Doorbell’s Ringing! Can you Get it?

Problem Formulation: Who Knows What?

28 Friday Nov 2025

Posted by petersironwood in AI, creativity, design rationale, psychology, Uncategorized

≈ 1 Comment

Tags

AI, browser, HCI, problem formulation, problem framing, problem solving, query, search, seo, technology, thinking, usability, UX

This post focuses on the importance of discovering who knows what. It’s easy to assume (without thinking!) that everyone knows what you know.

At IBM Research, around the turn of the century, I was asked to look at improving customer satisfaction about the search function on IBM’s website. Rather than using someone else’s search engine, IBM used one developed at IBM’s Haifa Research lab. It was a very good search engine. Yet, customers were not happy. By way of background, it’s worth noting that compared with many companies who have websites, IBM’s website was meant for a wide variety of users and contained many kinds of information. It was meant to support people buying their first Personal Computer and IT experts at large banks. It had information about a wide variety of hardware, software, and services. The site was designed to serve as an attractor for investors, business partners, and potential employees. In other words, the site was vast and diverse. This made having a good search function particularly important.

A little study of the existing data which had been collected showed that the mean number of search terms entered by customers was only 1.2. What?? How can that be? Here’s a website with thousands of products and services and designed for use by a huge diversity of users and they were only entering a mean of 1.2 search terms? What were they thinking?!

Of course, there were a handful of situations when one search term might work; e.g., if you wanted to find out everything about a specific product that had a unique one-word name or acronym (which was rare). For most situations though, a more “reasonable” search might be something like: “Open positions IBM Research Austin” or “PC external hard drives” or “LOTUS NOTES training.”

We invited a sample of users of IBM products & services to come into the lab and do some tasks that we designed to illuminate this issue. In the task, they would need to find specified information on the IBM website while I observed them. One issue became immediately apparent. The search bar on the landing page was far too small. In actuality, users could enter as many search terms as they liked. Their terms would keep scrolling and scrolling until they hit “ENTER.” The developers knew this, but most of our users did not. They assumed they had to “fit” their query into the very small footprint that presented itself visually. Recommendation one was simply to make that space much larger. Once the search bar was expanded to about three times its original size, the number of search terms increased dramatically, as did user satisfaction.

In this case, the users framed their search problem in terms of: “How can I make the best query that fits into this tiny box.” (I’m not suggesting they said this to themselves consciously, but the visual affordance led them to that self-imposed constraint). The developers thought the users would frame their search problem in terms of: “What’s the best sequence of terms I can put into this virtually infinite window to get the search results I want.” After all, the developers knew that any number of terms could be entered.

Although increasing the size of the search bar made a big difference, the supposedly good search engine still returned many amazingly bad results. Why? The people at the Haifa lab who had developed the search engine were world class. At some point, I looked at the HTML of some of the web pages. Many web pages had masses of irrelevant metadata. I found some of the people who developed these web pages and discussed things with them. Can you guess what was going on?

Many of the developers of web pages were the same people who had been developing print media for those same products and services. They had no training and no idea about metadata. So, to put up the webpage about product XYZ, they would go to a nice-looking web page about something else, say, training opportunities for ABC. They would copy that entire page, including the metadata, and then set about changing the text about ABC to text about product XYZ. In many cases, they assumed that the strange stuff in angle brackets was some bizarre coding stuff that was necessary for the page to operate properly. They left it untouched. Furthermore, when they “tested” the pages they had created about XYZ, they looked okay. The information about XYZ was there. Problem solved.

Only of course, the problem wasn’t solved. The search engine considered the metadata that described the contents to be even more important than the contents themselves. So, the user would issue a query about XYZ and receive links about ABC because the XYZ page still had the “invisible” metadata about ABC. In this case, many of the website developers thought their problem was to put in good data when what they really needed to do was put in good data and relevant metadata.

A third issue also revealed itself from watching users. In attempting to do their tasks, many of them suggested that IBM should provide a way for more than one webpage to appear side by side on the screen so that they could, for instance, compare features and functions of two different product models rather than having to copy the information from the web page about a particular model and then compare their notes to the second page.

Good suggestion.

Of course, IBM & Microsoft had provided this function. All one had to do was “Right Click” in order to bring up a new window. Remember, these were not naive users. These were people who actually used IBM products. They “knew” how to use the PC and the main applications. Yet, they were still unfamiliar with the use of Right Click. Indeed, allowing on-screen comparisons is one of the handiest uses of Right-Click for many people.

This issue is indicative of a very pervasive problem. Ironically, it is an outgrowth of good usability! When I began working with computers, almost nothing was intuitive. No-one would even attempt to start programming in FORTRAN or SNOBOL, let alone Assembly Language or Machine Code without looking at the manual. But LOTUS NOTES? A browser? A modern text editor? You can use these without even looking at the manual. That’s a great thing. But —

…there’s a downside. The downside is that you may have developed procedures that work, but they may be extremely inefficient. You “muddle through” without ever realizing that there’s a much more efficient way to do things. Generally speaking, many users formulate their problem, say, in terms like: “How do I create and edit a document in this editor?” They do not formulate it in terms of: “How do I efficiently create and edit a document in this editor?” The developers know all the splendid features and functions they’ve put into the hardware and software, but the user doesn’t.

It’s also worth noting that results in HCI/UX are dependent on the context. I would tend to assume that in 2021 (when I first published this post), most PC users knew about right-clicking in a browser even though in 2000, none of the ones I studied seemed to realize it. But —

I could be wrong.

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Index to a catalog of “best practices” in teamwork & collaboration.

What about the butter dish?

Labelism

The Stopping Rule

The Update Problem

Turing’s Nightmares: Eight

21 Friday Nov 2025

Posted by petersironwood in psychology, The Singularity, Uncategorized

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AI, Artificial Intelligence, cognitive computing, collaboration, cooperation, openai, peace, philosophy, seva, teamwork, technology, the singularity, Turing, ubuntu, United Peoples Ecosystem

Workshop on Human Computer Interaction for International Development

In chapter 8 of Turing’s Nightmares, I portray a quite different path to ultra-intelligence. In this scenario, people have begun to concentrate their energy, not on building a purely artificial intelligence; rather they have explored the science of large scale collaboration. In this way, referred to by Doug Engelbart among others as Intelligence Augmentation, the “super-intelligence” comes from people connecting.

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It could be argued, that, in real life, we have already achieved the singularity. The human race has been pursuing “The Singularity” ever since we began to communicate with language. Once our common genetic heritage reached a certain point, our cultural evolution has far out-stripped our genetic evolution. The cleverest, most brilliant person ever born would still not be able to learn much in their own lifetime compared with what they can learn from parents, siblings, family, school, society, reading and so on.

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One problem with our historical approach to communication is that it evolved for many years among a small group of people who shared goals and experiences. Each small group constituted an “in-group” but relations with other groups posed more problems. The genetic evidence, however, has become clear that even very long ago, humans not only met but mated with other varieties of humans proving that some communication is possible even among very different tribes and cultures.

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More recently, we humans started traveling long distances and trading goods, services, and ideas with other cultures. For example, the brilliance of Archimedes notwithstanding, the idea of “zero” was imported into European culture from Arab culture. The Rosetta Stone illustrates that even thousands of years ago, people began to see the advantages of being able to translate among languages. In fact, modern English contains phrases even today that illustrate that the Norman conquerers found it useful to communicate with the conquered. For example, the phrase, “last will and testament” was traditionally used in law because it contains both the word “will” with Germanic/Saxon origins and the word “testament” which has origins in Latin. Many other traditional legal terms in English have similar bilingual origins.

Automatic translation across languages has made great strides. Although not so accurate as human translation, it has reached the point where the essence of many straightforward communications can be usefully carried out by machine. The advent of the Internet, the web, and, more recently google has certainly enhanced human-human communication. It is worth noting that the tremendous value of google arises only a little through having an excellent search engine but much more though the billions of transactions of other human beings. People are exploring and using MOOCs, on-line gaming, e-mail and many other important electronically mediated tools.

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Equally importantly, we are learning more and more about how to collaborate effectively both remotely and face to face, both synchronously and asynchronously. Others continue to improve existing interfaces to computing resources and inventing others. Current research topics include how to communicate more effectively across cultural divides; how to have more coherent conversations when there are important differences in viewpoint or political orientation. All of these suggest that as an alternative or at least an adjunct to making purely separate AI systems smarter, we can also use AI to help people communicate more effectively with each other and at scale. Some of the many investigators in these areas include Wendy Kellogg, Loren Terveen, Joe Konstan, Travis Kriplean, Sherry Turkle, Kate Starbird, Scott Robertson, Eunice Sari, Amy Bruckman, Judy Olson, and Gary Olson. There are several important conferences in the area including European Conference on Computer Supported Cooperative Work, and Conference on Computer Supported Cooperative Work, and Communities and Technology. It does not seem at all far-fetched that we can collectively learn, in the next few decades how to take international collaboration to the next level and from there, we may well have reached “The Singularity.”

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For further reading, see: Thomas, J. (2015). Chaos, Culture, Conflict and Creativity: Toward a Maturity Model for HCI4D. Invited keynote @ASEAN Symposium, Seoul, South Korea, April 19, 2015.

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

Thomas, J. C., Kellogg, W.A., and Erickson, T. (2001). The Knowledge Management puzzle: Human and social factors in knowledge management. IBM Systems Journal, 40(4), 863-884.

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

Thomas, J.C. (2016). Turing’s Nightmares. Available on Amazon. http://tinyurl.com/hz6dg2

An Inside View of IBMs Innovation Jam

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