Cognitive Design

Cognitive design makes an unique contribution to improvement and innovation efforts by focusing on the workflow between the ears. By discovering and documenting mental processes and psychological needs cognitive designers bring important new requirements, constraints and opportunities to the table.   There are five ways to get at the workflow between the ears:

1. Search the literature and develop a hypothesis. If someone else has already developed a cognitive model of the domain you are working in make use of it. This can include general processes such as recognition-primed decisions making or something more specific such as threat detection in battle field management.
2. Do some fieldwork. This means going out and watching and making inferences about what people are thinking and feeling. Ethnographic methods and empathy mapping used in design thinking are popular examples.
3. Use lightweight modeling techniques. These often include using validated psychological assessment instruments to measure individual’s strengths, weaknesses and needs against a known model. For example, two instruments that are very useful for cognitive designers are the learning style inventory that gives insights into how individuals learn from experience and the sensory profile that provides a measure of how sensitive an individual is to sensory stimulation.  Both these instruments are very useful when you are designing for behavior change.
4. Use heavyweight modeling techniques.  These are cognitive engineering and artificial intelligence techniques and include for example cognitive task analysis and protocol analysis.   With these techniques experts are sometimes asked to  think-aloud while they are doing the mental work of interest. These verbal reports are treated as data and are analyzed and scored to develop a model of the mental process.  Another technique is the Zaltman Metaphor Elicitation Technique  that focuses on the collection and analysis of images that users provide to infer the mental models and metaphors that are guiding their thinking.  While the use of these heayweight techniques requires considerably more expertise than the previous techniques, they are essential for many application of cognitive design.
5. Lab and Clinical Modeling: These are often the most expensive and complex to use and include for example eye-motion. EEG and brain scanning studies.  The idea is to directly measure brain states or related psychological states to understand how people think-and-feel when interacting with a product or other artifact.  Usually this happens in a cognitive or neuroscience lab but over the last few years companies have formed to make the techniques more accessible especially in advertising, marketing and brand management.  See NeuroFocus for example.

It is best to work these in order as each provides context and insights for how best to scope the next one in line.

While many current innovation methods stress field work and rapid prototyping with users, it is often necessary to use light-and-heavy weight modeling methods to generate real insights into how to move hearts and minds.

I’m often asked for good examples of cognitive design.  Some of the best are:

Powerball (multi-million dollar jackpot lottery tickets), Angry Birds (a mobile game), the Dom Zu Kohn (cathedral in Germany), your favorite piece of art, using the placebo effect to heal, pictures of cute baby animals, the alert tone on a cell phone and magic tricks you can’t see even after they are explained.

The success of all of these artifacts turns on the fact that they generate far  more mental energy than it takes to interact with them. They deliver a powerful think-and-feel experience because features and functions are optimized for how our minds actually work.  Said another way, they reveal the secret sauce for how to design for psychological impact . They are a laboratory for applied cognitive scientists and a potential design pattern for innovators.

 So far our attempts at applying the lessons learn from these artifacts to other design problems has seen little success.   For example, serious games (i.e. application of game mechanics to education, health and and business) have yet to produce a block buster and lottery-based savings products have yet to make a dent in our need to prepare for retirement.

Cognitive design needs to mature.  One strategy is to get much better at translating the results of cognitive science and engineering into innovations that authentically move our hearts and accelerate our minds.  What we need are scientific studies of artifacts with high cognitive impact that are specific enough to offer design insights. For example, actionable research on the visual neuroscience of magic has come out of the Barrow Neurological Institute. In a recent press release they shared these  findings:

“The researchers discovered that curved motion engaged smooth pursuit eye movements (in which the eye follows a moving object smoothly), whereas straight motion led to saccadic eye movements (in which the eye jumps from one point of interest to another).”

“They studied a popular coin-vanishing trick, in which King tosses a coin up and down in his right hand before “tossing” it to his left hand, where it subsequently disappears. In reality, the magician only simulates tossing the coin to the left hand, an implied motion that essentially tricks the neurons into responding as they would have if the coin had actually been thrown. “

These have very specific implications for designers.  For a deeper dive into the neuroscience behind magic check out Sleights of Mind and the Best Illusions of the Year Contest.

It is interesting to note that magic was developed through experimentation and tradecraft.  Neuroscience is trying to catch up but once it does we should see a new type of magic emerge. The same it true for games, art and much of architecture, marketing, education and entertainment. Tradecraft trumps science’s ability to generate breathtaking think-and-feel experiences but for how long?

Emotions play a huge role in how our minds work. They shape and sometimes determine how we learn, make decisions, solve problems, change behavior and interact with others.  Decoding emotions is critical step in cognitive design no matter what application you are working on.

Emotions are visible through actions, body-language (especially facial expressions) and words.  Learning to read emotions in people and animals is not only good cognitive design, it builds emotional intelligence.   A well-known observational technique plays off the assumption that our biology determines how our facial muscles react when we experience a basic emotion such as surprise, fear, joy, disgust, anger, contempt and sadness. I frown when sad, my eyes widened when surprised and so on.

Of course it is more complex than that. For a deeper dive, check out Humintell’s microexpression recognition training, especially the tab on The Science.

Over the years of use I have noticed individual differences in how emotions play out on faces, perhaps due to context or something more fundamental.  For instance, some people narrow their eyes when surprised or smile when angry. While I could never prove they were in a base emotional state and exhibited a facial expressions that conflicts with the standard view, my experience supported it.  And the closer I looked the more variation I found.

Now there is a small but growing body of scientific work that is focused on the variations in the facial expression of emotions.  A recent press release by the Association for Psychological Science highlights some of the work:

“Contrary to what many psychological scientists think, people do not all have the same set of biologically “basic” emotions, and those emotions are not automatically expressed on the faces of those around us, according to the author of a new article published in …”

The note goes on to claim:

“Some scientists have proposed that emotions regulate your physical response to a situation, but there’s no evidence, for example, that a certain emotion usually produces the same physical changes each time it is experienced, Barrett says. “There’s tremendous variety in what people do and what their bodies and faces do in anger or sadness or in fear,” she says. People do a lot of things when they’re angry. Sometimes they yell; sometimes they smile.”

The implications for cognitive design are clear.  General rules for decoding emotions from facial expressions are fine but they only go so far. In complex or high-risk situations the real value might be in the variations from those rules.

Source of Image:  Seven Basic Emotions

Sometimes progress and success messes things up.   For example,  demand for a start-ups product or service grows so fast they cannot meet it. Quality slips and promised delivery dates are missed.  Or a successful company becomes complacent and arrogant because they dominate the market and starts making mistakes.

According to an interesting post by Dr. McGonigal on her Science of Willpower Blog, this can happen during the behavior change process. As we make progress our executive function exerting the self control becomes satisfied and our impulse for the old behavior can kick in. Focusing on the progress we have made actually sets us up for a relapse.  Indeed, celebrating success, the way we traditionally do with a minor indulgence, may be the worse thing to do.

What to do? One way is to reframe what progress means so it maintains emphasis on the executive function of self-control:

“Progress can be motivating, and even inspire future self-control, but only if you view your actions as evidence that that you are committed to your goal. You need to look at what you have done and conclude that you must really care about your goal. So much so, that you want to do even more to reach to it. This perspective is easy to adopt; it’s just not our usual mindset. More typically, we look for the reason to stop.”

The goal is to reflect on the why or reason for your self-control, not just the accomplishment.  Using your accomplishment to stay focused on the psychology of commitment avoids success-related relapse.

Clearly a good insight into how  minds actually work and it is actionable enough for cognitive designers working on behavior change challenges.  The post in the Willpower Blog is sneak preview of one of the chapters in Dr. McGonigal’s  new book,  The Willpower Instinct.  I have it on pre-0rder and will do a review.

Studies in cognitive science and psychology in general are often done on a small group of subjects with a similar psychographic profile.  University college students are by far the most popular subject pool. This sampling bias slows the development of the science  and blocks useful generalizations.

Conducting large-scale and more empirically robust studies of how our minds work has until recently been far too costly and complex for most academic researchers. Mobile and social media is changing that.   A new generation of experimental design is emerging in cognitive science that makes use of the internet and smart phones as data collection tools that can involve hundreds if not thousands of subjects from diverse cultures around the world. But will it really make a difference?

According to the 17 authors of the paper, Smart Phone, Smart Science, not only will it make a difference, it will revolutionize cognitive science.  They show how the smart phone can be applied to study reaction times in lexical decision making, a classic research question in cognitive psychology. While the details of the experiment might not be of interest to readers of this blog, the general conclusion should be:

“The use of smartphones for scientific experimentation heralds a new era in behavioral sciences. The approach has wide multidisciplinary applications in areas as diverse as economics, social and affective neuroscience, linguistics, and experimental philosophy. Finally, it becomes possible to reliably collect culturally diverse data on a vast scale, permitting direct tests of the universality of cognitive theories.”

Changing how you can collect data in science, often revolutionizes the field. Think about the impact of the telescope and microscope.

If social mobile media can advance scientific practice, it can certainty also be used to improve how we  prototype, test and refine cognitive designs. It is not just smart phone – smart science, it is smart phone – smart cognitive design research.

I am interested in hearing from readers that have used smart phones or the internet (custom websites, communities, twitter, etc.) to conduct design research, prototype or otherwise empirically drive design thinking.

Hunger is a powerful biological and psychological state.  And we can “hunger” for things other than food. As the saying goes,  some people  hunger for power and possessions.

Recent research at  Northwestern University tested what we can hunger for in the broader sense by measuring salivation.  The idea is when we are really hungry for food we salivate so we might also drool when we hunger for other things. And we do!

“Results of an experiment show that individuals salivate to money when induced to feel a low power state but not when induced to feel a high power states.  A second experiment showed that men salivate to sports cars when primed with a mating goal but not a control condition.”

Designers interested in creating “objects of desire” should pay special attention to the role of  priming in the experiments. Priming means stimulating subjects to create a specific frame of mind before presenting the test stimulus.  Money by itself won’t cause me to salivate but if I am primed to perceive it as a way to increase power it might. Likewise a sports car by itself will not cause me to salivate unless I am primed to see it as a means to mate.

Inventions like everything in nature exhibit patterns. Finding and leveraging the patterns of innovation is the thrust of TRIZ and related methodologies such as Structured Inventive Thinking (SIT). For a brief but meaningful introduction to SIT check out the LAB.  It illustrates the method on everything from corporate training to drugs, office chairs and software.

SIT starts by deconstructing an existing artifact into its components. You then apply a pattern or innovation heuristic to a component to generate compelling possibilities fast and systematically.  Example patterns include subtraction where you take a component away and work with what is left. Another is task unification where you assign a new function or task to an existing component.  You can apply multiple patterns to one component to think divergently.

Image Source: Animated GIF of Kaleidoscope

In cognitive design we seek to understand deeply felt but unmet psychological needs and then create or remake artifacts to meet them.  The TQM journal has an interesting article on Affective Design of Waiting Areas in Primary Healthcare that presents a good example. The researchers used the Kansei engineering method to uncover the psychology need to “feel calm” and…

“The core design attributes contributing to this feeling are privacy, colours, child play-areas and green plants. Good design of lighting, seating arrangements and a low sound level are also important design attributes to give a more complete design solution.”

A useful finding for cognitive designers working on servicecapes that call for calm.

Placebos, or rituals dressed up as medical treatments that lack any active ingredients, definitely abate symptoms in many circumstances.  They can change how we think-and-feel about our illness or disease. Indeed, they are so effective at moving our hearts and minds we have explored their implications as a more general tool for organizational and individual change here on the cognitive design blog.

But an important question remains, do they go beyond heart-and-mind impact to create the underlying physiological changes that drugs with active ingredients do? Is belief somehow altering biology? The answer appears to be no, at least within the scope of a recent clinical study of placebos reported by Beth Israel Deaconess Medical Center.  They studied the physiological impacts of placebos on Asthma patients and found:

 ”while placebos had no effect on lung function (one of the key objective measures that physicians depend on in treating asthma patients) when it came to patient-reported outcomes, placebos were equally as effective as albuterol in helping to relieve patients’ discomfort and their self-described asthma symptoms.”

Abating symptoms and relieving discomfort is a significant psychological impact.

This is a very important finding for cognitive designers. It demonstrates that designs (in this case a placebo) that create distinct think-and-feel effects deliver significant value even if they do not produce underlying changes in physiology. Placebos as “pure play” cognitive designs create real value!

New York Times has an excellent article, Brain Calisthenics for Abstract Ideas, that describes successful application of perceptual learning to teaching K-12 math and science.

Our minds work best and learn automatically from rich sensory information. Perceptual learning  typically involves the modification of one or more of our five senses through practice to discriminate specific sounds, detect particular patterns, feel subtle changes in texture and so on. Perceptual learning is inductive learning and results from lots of exposure and practice. It can evolve into expertise such as music appreciation, wine tasting, judging the quality of fabric by touch and so on.

Our minds struggle with abstract ideas and concepts such as equations, fractions and the notion of truth.  Such things seems far from the rich sensory experience we are geared to process and are often taught in a top down fashion. Learn the abstract idea and then apply it to examples. Abstract learning is often deductive learning.

Ideally (at least from a cognitive design perspective), we would develop ways to teach and learn abstractions based on how our minds actually work best.  That is exactly what the NYT article reports. Here is one example for learning fractions:

“On the computer module, a fraction appeared as a block. The students used a “slicer” to cut that block into fractions and a “cloner” to copy those slices. They used these pieces to build a new block from the original one — for example, cutting a block that represented the fraction 4/3 into four equal slices, then making three more copies to produce a block that represented 7/3. The program immediately displayed an ‘X’ next to wrong answers and “Correct!” next to correct ones, then moved to the next problem. It automatically adjusted to each student’s ability, advancing slowly for some and quickly for others. The students worked with the modules individually, for 15- to 30-minute intervals during the spring term, until they could perform most of the fraction exercises correctly.”

By using the slicer and cloner to manipulate embodied fractions on the computer students engage in perceptual learning but end up understanding fractions as an abstract concept. They learn to perceive fractions not reason about them conceptually.

Students that used this method tested 3 times better than a control group and demonstrated retention over 5 months.

Care must be taken to design modules to stimulate our built in perceptual learning abilities (e.g. tuning perceptual abilities based on patterns in sensory experience) rather than just show random examples or visually illustrate the abstract concept.  A subtle difference and one that requires some skill in cognitive engineering and design.