── ── Cognitive bias

Halo Effect

A single positive or negative impression biases judgments of all unrelated attributes. A "great" CEO is assumed to have great strategy, vision, and execution; a beloved brand's features are rated higher than equivalent features from less-loved brands. Documented by Thorndike (1920), formalized by Nisbett & Wilson (1977), applied to business analysis by Rosenzweig (2007) — who showed business books overclaim…

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How it works

Composes with fundamental-attribution-error, narrative-fallacy, confirmation-bias, hindsight-bias, survivorship-bias.

When to use it

  • user is conducting a performance review or hiring interview
  • someone says 'she's great across the board' or 'everything they do is excellent'
  • user is evaluating a vendor, CEO, or investment and all attributes look uniformly positive or negative
  • user is reading business books or analyst reports and wants to assess whether the lessons generalize
  • user suspects their overall impression of a person or brand is distorting specific judgments

When not to use it

When the decision is routine and reversible, applying a formal method costs more than it returns.

Worked example

The "AI" Halo — Builder.ai and the AI-Washing Wave (2023–2026)

Between 2023 and 2026, the two letters "AI" functioned as the strongest halo in business evaluation: a single glowing attribute ("they're an AI company") that silently inflated investors' ratings of every other attribute — revenue quality, technology depth, management integrity, even audit reliability. The cleanest documented case is Builder.ai, a Microsoft-backed "AI-powered app development" unicorn once valued around $1.5 billion, which filed for insolvency in May 2025 after its revenue and its "AI" both turned out to be substantially less than the halo suggested. Regulators…

Install this skill (free, MIT)

$npx skills add deciqAI/knowledge-skills
View Halo Effect source on GitHub →

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