Overconfidence

As explained in Collaborative Software Design: How to facilitate domain modeling decisions

Excessive confidence in one's abilities, judgment, or correctness relative to available evidence.

Overconfidence is the tendency to trust one’s abilities or judgments more than available evidence justifies. In collaborative refinement, prior success can make facilitators stop listening to participants’ concerns and overlook confirmation bias or status quo bias. section 7.3.1

A refinement session repeats old failures

A team experiencing production bugs from misunderstood rules hoped to find new ideas during refinement but feared repeating earlier outcomes. Because facilitators had run similar sessions before, they expected success and failed to fully hear that warning. Example Mapping then exposed the group’s difficulty generating new scenarios. section 7.3.1

Figure 7.4 An example of how an Example Mapping looked at BigScreen. The groups are divided and are using index cards on the table to collaboratively model and discover new scenarios and acceptance criteria.

Use the Example Mapping view to inspect how collaborative examples and acceptance criteria reveal gaps that confidence may conceal. section 7.3.1

How Collaborative Software Design: How to facilitate domain modeling decisions covers it

How deep it goes

Defines the bias and demonstrates its effect in a refinement failure, without detailing measurement or psychological mechanisms.

Examples

Uses a troubled refinement session, production bugs, participant warnings, and an Example Mapping exercise.

What it assumes

Assumes collaborative refinement experience and teaches the bias through a concrete facilitation failure.

What you can do after

Diagnose/debug with it by questioning facilitator confidence and listening for evidence that a familiar session is failing.

How it connects

Links overconfidence to false-consensus effect, confirmation bias, status quo bias, availability bias, anchoring effect, and Example Mapping.

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Related concepts

• cognitive biaskind of · A cognitive bias is a systematic tendency in human perception, judgment, or reasoning that can distort how information is evaluated and decisions are made.
• label smoothingaddressed by · Label smoothing is a regularization technique that replaces hard target labels with softened probability distributions during model training.
• hallucinationproduced by · A hallucination is model-generated content that is false, fabricated, or unsupported by relevant evidence but presented as plausible or factual.
• confirmation biascontrasts with · Confirmation bias is the tendency to seek, favor, interpret, or recall information that supports existing beliefs or expectations while discounting conflicting evidence.
• explainable outputproduced by · An explainable output is a result accompanied by an intelligible account of the factors, reasoning, or decision logic underlying it.

This explainer was generated by Manning's knowledge graph from the text of Collaborative Software Design: How to facilitate domain modeling decisions. The section links point to the parts of the book it draws on.