Mismatched: What's Wrong With the Way We Recognize Patterns

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Information about Mismatched: What's Wrong With the Way We Recognize Patterns
Design

Published on March 9, 2014

Author: stribs

Source: slideshare.net

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Every day we are overwhelmed with a barrage of information in the world around us. To make sense of this onslaught of data, we look for patterns, and we make decisions every moment based on the patterns we recognize.
Of course, that skill saves us an enormous amount of time and energy and really helps us make sense of the world, organizing and packaging it, as tidily as possible. But what can go wrong with the way we identify these patterns? What impact does forcing everything into a pattern have upon us a human beings? More specifically, too, how can imposing patterns upon user experiences actually undermine their efficacy - unless they're designed in a careful, thoughtful way?

Mismatched What’s wrong with the way we recognize patterns? Robert Stribley Associate Experience Director, Razorfish #patterns

How many political parties are there in the United States?

How many political parties are there in the United States? How many colors are there? How many genders are there? How many forms of sexual orientation are there? How many races are there? How many states are there?

We’re poor tolerators of ambiguity

We live in an incredibly complex environment We’re constantly bombarded by stimuli How do we process all this information?

Pattern Recognition The ability to identify familiar forms within a complex arrangement of sensory stimuli Butterfly on the New York City Highline

Butterflies Labeled by Species

Some examples of pattern recognition

Scientists note patterns in attempts to understand the natural world

Facebook recognizes faces and even suggests names

Researchers use Twitter to track and forecast flu outbreaks

The games we play invariably require pattern recognition

We can recognize when one game design is based on another November 2010 November 2010 April 2012 April 2012

Or when one design has likely influenced another

We can recognize when designs follow trends

Pattern recognition helps us recognize the same person, despite changes to their appearance over time.

We might see people and conclude they look alike, which can lead to cases of mistaken identity

Bees mistake flowers for sexual partners

But humans wouldn’t mistake a facsimile for the real thing like that, would we?

So recognizing patterns is tremendously useful. But sometimes in seeing patterns, we arrive at conclusions, which aren’t correct.

Just a few of the problems we encounter when recognizing patterns: •Apophenia •Pareidolia •Post hoc ergo propter hoc •Confirmation bias, selection bias •Binary thinking •Tribalism •Categorical thinking

Categorical thinking? What’s wrong with categorical thinking?

Robert Sapolsky Professor of Biology, Neurology, Neurological Sciences, Neurosurgery, Stanford University

“We think in categories. We take things that are in continua and we break them into categories. And we label those categories. And we do that in various settings because it could be extremely useful.” – Sapolsky UX people: Think card sort, think taxonomy, think site map

"Fall into categorical thinking and you can do unspeakable damage in the realm of science that makes difference." – Sapolsky *and in life and in design

1. Focus on categories and we can overlook distinctions within categories.

2. Focus on boundaries and we can overlook similarities between items.

Man V. Ape Focus on differences between species and you may overlook many obvious similarities

Color Spectrum

3. Focus on boundaries and we can miss the big picture. All we see are categories.

cho-pho-use

chophouse

What are some solutions?

1. Spectrums can be more accurate than limited categories.

Alfred Kinsey

Human Sexuality and the Kinsey scale

Prof. Michael Storms – The Storms Model

Takeaway: Spectrums offer more nuance. But beware of artificial boundaries within a spectrum, too.

2. It’s OK to classify things in multiple categories.

Employ flexible categorization systems 1.Flexible taxonomies 2.Crowd-sourced tagging 3.Machine-based tagging

Takeaway: Recognize and highlight connections between things in different categories

3. Stay alert to field bias to see the full picture

• We tend to categorize in ways which reflect our training or background • A biologist, a geneticist, and an endocrinologist might answer the same question in different ways • They present categorical solutions which reflect their language and cultural differences

We encounter the same issue when working with different departments within an organization

Takeaway: Encourage communication among departments, between users and stakeholders.

• We can’t operate as human beings without recognizing patterns. • Categorization can be a helpful thing. • Until it isn’t. Then it can be damaging. • Or it can make information difficult to process and navigate. • So approach recognizing patterns with nuance.

Enjoy ambiguity

Thank you Robert Stribley @stribs This presentation on Slideshare: www.slideshare.com/stribs My tumblr about pattern recognition: stribs.tumblr.com

For Further Study •Biology & Human Behavior: The Neurological Origins of Individuality – Professor Robert Sapolsky, The Great Courses •Chaos – James Gleick •First Principle: Disambiguation – Rachel Lovinger, Contents Magazine •Stochasticity – Radio Lab, WNYC, Season 6, Episode 1 Special thanks to Amy Stack, Rachel Lovinger and Jason Scott for their feedback on this presentation. Dedicated to my wife, Amy Stack.

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