Illusions – Optical and Other

Posted on February 12, 2007  Comments (8)

Checkerbox Graphic If the output for working for the year is a square. And the job is to produce dark squares who do you pay more A or B? Of course it is a trick question, the squares are the same color. But it doesn’t look that way at first does it? Optical illusions provide evidence that you cannot always trust what seems obvious.

Dr. Deming’s red bead experiment provides some additional insight into the idea that our management systems often use “evidence” to support our believes when in fact the “evidence” does not mean what we think it does. Dr. Deming included the theory of knowledge (how do we know what we know) as one of the four areas of his management system. It is the areas of his work that is least appreciated and understood by managers today. Optical illusions provide a simple reminder of how easily we can think we know things that are not so.

Just as Toyota is always dissatisfied and looking for how to improve, it is important to question what you believe. Even when it is as obvious as the A square being darker than the B square. Understanding the ease with which we can reach false conclusions can be a powerful aid in improving management decision making.

Related: The Illusion of UnderstandingChange is not ImprovementPerformance Appraisal ProblemsDr. Deming on Performance Appraisal: “The fact is that the system that people work in and the interaction with people may account for 90 or 95 percent of performance” (from the introduction to the Team Handbook) – It is a mistake to think improving the figures is the goal

Optical illusion by Edward H. Adelson

8 Responses to “Illusions – Optical and Other”

  1. Curious Cat Science and Engineering Blog
    March 13th, 2007 @ 10:10 am

    Seeing Patterns Where None Exists
    “I call data dredge studies the ‘Rorschach tests’ of epidemiology, because researchers can pull out characteristics about people in almost unlimited combinations to find all sorts of correlations and conclude just a…”

  2. Curious Cat Science and Engineering Blog » Mistakes in Experimental Design and Interpretation
    June 19th, 2007 @ 8:59 am

    This is an excellent article discussing very common errors in how people use data. We have tendencies that lead us to draw faulty conclusions from data. Given that it is important to understand what common mistakes are made to help us counter the natural tendencies…

  3. Curious Cat Science Blog » Poor Reporting and Unfounded Implications
    January 1st, 2009 @ 8:31 am

    “Correlation is not causation. And reporting of the form, “1 time this happened” and so I report it as though it is some relevant fact, is sad…”

  4. Curious Cat Science Blog » Magenta is a Color
    February 18th, 2009 @ 8:46 am

    This is a great article that uses science to explain interesting details about our brains and how we perceive the external world…

  5. Curious Cat Science and Engineering Blog » Albert Einstein, Marylin Monroe Hybrid Image
    June 15th, 2009 @ 10:16 am

    “Hybrid images are based on the multiscale processing of images by the human visual system and are motivated by masking studies in visual perception…”

  6. Curious Cat Science and Engineering Blog: Anscombe's Quartet
    September 1st, 2009 @ 12:20 pm

    Anscombe’s quartet comprises four datasets that have identical simple statistical properties, yet are revealed to be very different when inspected graphically…

  7. Curious Cat Management Improvement Blog » Communicating with the Visual Display of Data
    October 26th, 2009 @ 8:36 am

    [...] Of course we also have to be careful of drawing incorrect conclusions from visual displays. [...]

  8. Curious Cat Science and Engineering Blog » Science and Optical Illusions
    October 19th, 2010 @ 12:14 am

    Studying illusions can teach us several things. We can learn that it is easy for our senses to be fooled. We can learn about how the brain works…

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