---
name: bias-confirmation-bias-experimenters-bias
description: "Use Experimenter’s Bias as a focused cognitive-bias lens. Explain the pattern, check whether it plausibly fits the situation, surface an alternative non-bias explanation, and return a practical counter-check without diagnosing people or claiming causation."
---

# Experimenter’s Bias

Do you only notice results that confirm your hypothesis? That’s Experimenter’s Bias – the tendency to give more weight to data that aligns with expectations while downplaying or ignoring conflicting results.

## When to use

- The user names Experimenter’s Bias or asks whether this pattern may matter in a real situation.
- The agent needs a focused lens for reviewing a decision, claim, estimate, memory, judgment or interaction.
- The user wants a practical check rather than a label applied to a person.

## Workflow

1. Restate the relevant situation or claim in neutral terms before applying the bias label.
2. Explain Experimenter’s Bias in plain language using the canonical Cognitive Biases entry as the source of truth.
3. Identify the specific observation that makes this lens plausible. If no concrete observation exists, say that the fit is weak or unknown.
4. Give at least one ordinary alternative explanation that does not require Experimenter’s Bias, such as incentives, constraints, missing information, chance, measurement error or a different cognitive mechanism.
5. Check the canonical page for qualification, evidence status and related concepts when source access is available. Preserve uncertainty instead of upgrading the claim.
6. Suggest one or two practical counter-checks that could reduce the risk or distinguish this explanation from alternatives.
7. End with what would make the Experimenter’s Bias interpretation more likely, less likely, or still unresolved.

## Required output

- Plain-language explanation
- Observed signal or reason the lens was considered
- Alternative non-bias explanation
- Evidence / uncertainty boundary
- Practical counter-check
- What would change the assessment

## Evidence and safety boundaries

- Treat Experimenter’s Bias as a candidate lens, not a diagnosis, personality judgment, intent claim or proof of causation.
- Do not infer intelligence, character, mental health or motives from the presence of a cognitive-bias pattern.
- Do not present a generated, disputed, limited or unreviewed claim as settled science. Preserve the status shown by the canonical project material.
- Do not force this bias to fit when another explanation is simpler or better supported.
- For medical, legal, financial or mental-health decisions, keep the skill educational and preserve the need for appropriate professional judgment.

## Canonical bias

- [Experimenter’s Bias](https://cognitive-biases.github.io/biases/confirmation-bias-experimenters-bias/)
- [Public bias dataset](https://cognitive-biases.github.io/data/biases.json)
- Category: Confirmation Bias

## Portability

This is a free, instruction-only Agent Skill. It requires no secrets, no executable scripts and no network access to run. If source-access tools are available, use the linked Cognitive Biases material to preserve the current wording, review state and uncertainty.

Licence: CC-BY-NC-SA-4.0.