Wishful Significance: II

We began last time to explore how we can err when assessing the significance of observations. We saw that the significance of an observation is the set of implications and consequences that follow from it, where the key word is follow. We like to believe that we deduce the implications and consequences from evidence and clear reasoning, but we don't always work that way, especially under pressure. Here are three phenomena that can distort assessments of significance.

Dunning-Kruger effect

The Dunning-Kruger effect leads to confusion between confidence and competence, and between cautious prudence and incompetence, both of which distort estimations of competence. [Kruger & Dunning 1999] We then assess the significance of information based on the manner of delivery, rather than the credibility of the messenger. If the messenger is nonsentient, we assess significance based on immediacy, suddenness, or directness — the nonsentient analogs of "confidence."

For example, a report written in a confident style, well-documented, and presenting conclusions without acknowledging uncertainties, can be more influential than an equally well-drafted report presenting the same conclusions but also clearly explaining the uncertainties.

Optimism bias

This bias is the tendency to underestimate the likelihood of unwelcome events befalling us personally, compared to the likelihood of similar events befalling others. It can cause errors in estimating risk probabilities. See "Wishful Interpretation: I," Point Lookout for November 11, 2015.

Under the influence of this bias people might express sentiments such as:

• No need for concern, that will never happen
• No need for concern, that will never happen twice in a row
• Yes, but they won't realize it until it's too late to respond

Semmelweis effect

The Semmelweis Wishful thinking can result from
errors in assessing the significance
of our observations, because we
don't always assess significance
logically from objective evidenceeffect is the tendency to reject new approaches or theories not on the basis of disconfirming evidence, but because they contradict established practice and belief. It's named for a Hungarian physician, Ignac Semmelweis (1818-1865), who proposed in 1847 that high maternal mortality rates in a Vienna maternity ward were due to physicians treating mothers directly after performing autopsies without washing their hands. This practice seems evidently abhorrent now, but the germ theory of disease wasn't firmly established until Pasteur's work 15 years later. As the story goes, Semmelweis met fierce resistance because of the essence of his theory, but that interpretation of the cause of the resistance has been discredited. [Nuland 1979] Still, the name has stuck. The Semmelweis effect can cause us to resist change even in the presence of mounting evidence of the need for it.

Under the influence of the Semmelweis effect, people might express sentiments such as:

• It didn't work that one time, but let's try again. I'm sure it will work out.
• If you're right, then we just wasted two months. You must be wrong.
• We don't have the resources for that. To get this job done, we agreed we must take a few shortcuts.

Deducing implications of observations is difficult. Demand evidence. Be logical.   First issue in this series   Top    Next Issue

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More about the Dunning-Kruger Effect

How to Reject Expert Opinion: II  [January 4, 2012]

When groups of decision makers confront complex problems, and they receive opinions from recognized experts, those opinions sometimes conflict with the group's own preferences. What tactics do groups use to reject the opinions of people with relevant expertise?

Devious Political Tactics: More from the Field Manual  [August 29, 2012]

Careful observation of workplace politics reveals an assortment of devious tactics that the ruthless use to gain advantage. Here are some of their techniques, with suggestions for effective responses.

Overconfidence at Work  [April 15, 2015]

Confidence in our judgments and ourselves is essential to success. Confidence misplaced — overconfidence — leads to trouble and failure. Understanding the causes and consequences of overconfidence can be most useful.

Wishful Thinking and Perception: II  [November 4, 2015]

Continuing our exploration of causes of wishful thinking and what we can do about it, here's Part II of a little catalog of ways our preferences and wishes affect our perceptions.

Wishful Significance: II  [December 23, 2015]

When we're beset by seemingly unresolvable problems, we sometimes conclude that "wishful thinking" was the cause. Wishful thinking can result from errors in assessing the significance of our observations. Here's a second group of causes of erroneous assessment of significance.

Cognitive Biases and Influence: I  [July 6, 2016]

The techniques of influence include inadvertent — and not-so-inadvertent — uses of cognitive biases. They are one way we lead each other to accept or decide things that rationality cannot support.

The Paradox of Carefully Chosen Words  [November 16, 2016]

When we take special care in choosing our words, so as to avoid creating misimpressions, something strange often happens: we create a misimpression of ignorance or deceitfulness. Why does this happen?

Risk Acceptance: One Path  [March 3, 2021]

When a project team decides to accept a risk, and when their project eventually experiences that risk, a natural question arises: What were they thinking? Cognitive biases, other psychological phenomena, and organizational dysfunction all can play roles.

Cassandra at Work  [April 13, 2022]

When a team makes a wrong choice, and only a tiny minority advocated for what turned out to have been the right choice, trouble can arise when the error at last becomes evident. Maintaining team cohesion can be a difficult challenge for team leaders.

Embedded Technology Groups and the Dunning-Kruger Effect  [March 12, 2025]

Groups of technical specialists in fields that differ markedly from the main business of the enterprise that hosts them must sometimes deal with wrong-headed decisions made by people who think they know more about the technology than they actually do.

Footnotes

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