Pipsqueak Articles

Posts written by Olga Werby or Christopher Werby

Cognitive Blindness, Errors, Featured, Interface Design, Perception, Pipsqueak Articles

Color Blind Design

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Do you see any difference between these two images? About 10% of the male population (with up to 20% among some ethnic groups) do not. Do differences in the way individuals perceive and process color information matter? Sometimes… Consider this informational graphic: It’s easy to see how the information contained within this chart has been transformed and no longer carries the same meaning. Which is the right one? When designing information for communication, it’s important to consider the totality of the intended audience: What are their strength? What are their limitations? Like cognitive traits, perceptual differences have to be accommodated by good design. Some issues that individuals with deuteranope deficit (red/green confusion) face is inability to tell the difference between colored items that are too thin (lines), point sources, and blinking lights (think traffic lights blinking green or yellow). These problems effect real-life performance and can lead to accidents: think traffic light color confusion. It is the job of a product designer to reduce the difficulties these individuals face. You can use this URL to check your site for color blind usability: http://www.vischeck.com/vischeck/vischeckURL.php

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Background Knowledge, Background Knowledge Errors, Diagnostic Errors, Perception, Pipsqueak Articles, Users

Distilling Information

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When it comes to my students’ participation in this blog, it’s all about distilling information found in the news to something product designers in our midst would find useful, on a practical level. Consider the illustration below. We see a person’s face (mine in this case). We can describe some of the features. But what do we actually remember? Remembering complex visual information is hard—too many details. Recalling a drawing is easier. That’s because an artist already distilled the complexity into its essential parts—only those details that are required to remind us of a particular individual are included in the rendering. We are all pretty good at judging wether a portrait looks like the person it was intended to represent. We can quickly say if it does or if it doesn’t. But it would be difficult to explain what details in the illustration make the likeness or what’s missing from the drawing that didn’t hit its mark. Distillation of information is hard. Some people are good at it, some are not. It’s an acquired skill. And each category (e.g. sensory like visual, audio, tactile or knowledge-based like physics, economics, biology) requires its own training and its own set of talents.…

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Background Knowledge Errors, Pipsqueak Articles

Complex Nonlinguistic Auditory Processing

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aka Music. Today, I read a short interview on New York Times where Aniruddh D. Patel answers a few questions about his research into the neuroscience of music. The interview was pretty entertaining—we’ve all seen the YouTube video of a dancing cockatoo. But what got me was the last line on the difficulties of getting funding for research. In particular, getting money to study music was just not possible. So to keep his scientific research sounding like serious science, Dr. Robert Zatorre, one of the founding fathers of this field, used to write “complex nonlinguistic auditory processing” every place the word “music” should have been. To avoid structural research failure, Dr. Zatorre resorted to linguistic manipulation. And it worked! “Exploring Music’s Hold on the Mind: a Conversation with Aniruddh D. Patel,” written for New York Times by Claudia Dreifus, and published on May 31, 2010.

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Anchoring Errors, Background Knowledge, Background Knowledge Errors, Diagnostic Errors, Mental Model Traps, Pipsqueak Articles

Working Memory Limitations vs. the Size of Problem

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Three BLind Men and an Elephant Proverb

The illustration above comes from Wikipedia, which has a complete entry on the Asian proverb about blind monks who examine an elephant and generate multiple hypotheses of what it could be. In product design speak, these monks are doing collaborative problem solving with a shared goal of identifying a mysterious object—the elephant. The monks, the story goes, all come from different backgrounds: an old tailor touching an elephant’s ear describes it as cloth; an aging gardner hugging the leg imagines a tree trunk; an elephant’s tusk is envisioned as a weapon by an arms master. Each monk brings his own life’s worth of experience to bear on the problem, but each has very limited access to the whole. It’s easy to see how this story can be used to explain the pains of collaborative and cooperative group projects in which individuals focus on product design. Each person brings their own expertise to the table, hopefully contributing positively to the whole process. But this story is also a good metaphor for understanding problem solving in context of our very limited working memory capacity. Unlike elementary school math problems that we all calculated, real world problems are messy and don’t come with…

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Cognitive Blindness, Errors, Ethnographic & User Data, Pipsqueak Articles, Users

Cognitive Blindness: Super-recognizers

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Health Check, the BBC World Service’s weekly round up of global health stories, did an audio broadcast on super-recognizers—people with extraordinary abilities to recognize faces. You can listen to the entire story by Claudia Hammond at http://news.bbc.co.uk/2/hi/health/8665805.stm This story deals with differences in ability to recognize faces. There are people who are so bad at it that it is a pathology—when a mother can’t recognize her child among the pupils in the day care center, it’s more than inconvenient. Then there are all those embarrassing moments when you meet someone at a party for what you think is the first time only to have that person insist that you’ve met before. And the far end of the continuum, there are the super-recognizers—individuals that never forget a face even after a very brief interaction. We only now recognize the fact of super-recognizer, because most of us are not too bad and not too good at facial recognition—we are mostly average. And our average ability to recognize faces limits our ability to spot people who could do better. We were experiencing cognitive blindness—inability to perceive cognitive differences in abilities of others. And super-recognizers, similarly, didn’t know that they were somehow different from…

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Cognitive Blindness, Conceptual Design, Errors, Interaction Design, Interface Design, Pipsqueak Articles, Scaffolding, Users

Error Opportunity Space

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Confronted with one “True or False” question, an individual has a very small error opportunity space: three. There are three possible responses: true, false, or no answer. “No answer” will always be wrong, a betting man should choose one of the possible answers. But unfortunately situations where the error opportunity space is so narrow are rare. And in the real world, dealing with real problems, these spaces tend to be very large. Note that the size of the error opportunity space, EOS, makes no representations about the consequences of getting the problem right or wrong (or partially right or wrong). When the stock market tanked on May 7th, people involved in that process had a very large EOS. A week out, experts and participants are trying to figure out what went wrong and how to limit similar incidents in the future—they are trying, in effect, to drastically reduce the error opportunity space. This is a job of product designers. By analyzing the goals of the users and the system’s constraining variables, we can come up with conceptual design, interaction design, and interface design that would address the problems that were exposed on May 7th. Coming up with a solution is…

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Background Knowledge Errors, Causal Net Problems, Conceptual Design, Diagnostic Errors, Featured, Interaction Design, Interface Design, Pipsqueak Articles

The Anatomy of Failure

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On May 7th 2010, at around 2:30 p.m. Eastern Time, the stock market went on a wild ride, dropping over 900 points in matter of just minutes. What happened? There’s lot’s of speculation, and some know more then they are willing to say. But what’s clear is that there was just the right confluence of world events, human and computer errors, and system-wide communication breakdown that triggered a mass sell-off of stocks at fantastic prices. In other words, there was a catastrophic failure during product interaction. I’m not an investment analyst and have limited knowledge in this subject area, but I am interested in product failure. So Thursday’s stock market episode was very interesting. Here’s a little background on the events of that day broken down into steps leading to the failure. Step 1: When the New York stock market opened on Thursday, bad news was streaming in from Europe—there were fears that Greece would ultimately default on its loans; its people were staging massive demonstrations in Athens; Euro was going down. Step 2: In our very interconnected world, this kind of news makes investors skittish and the stock market was dropping value all morning. Step 3: At around 2:45…

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