Top Cognitive Biases, Effects & Paradoxes for IT Leaders

40 vocabulary flashcards summarizing the most relevant cognitive biases, effects, and paradoxes for software engineers and managers.

Dunning–Kruger Effect

People with low skill over-estimate their ability while experts under-estimate theirs; affects mentoring and task delegation.

Jevons Paradox

Efficiency gains lower costs and can raise total resource consumption; explains rising cloud usage after optimization.

Confirmation Bias

Favoring information that supports existing beliefs; skews debugging, architecture choices and hiring.

Availability Heuristic

Judging likelihood by how easily examples come to mind; recent outages feel more probable than they are.

Anchoring Bias

Relying too heavily on initial information (the anchor); distorts estimates, salary talks and budgets.

Sunk Cost Fallacy

Continuing a losing course because of past investment; keeps failing projects alive.

Hindsight Bias

After events, believing they were predictable (“I knew it”); hampers objective post-mortems.

Framing Effect

Choices change when the same facts are cast as gains vs. losses; critical in risk communication and feature pitches.

Bystander Effect

People hesitate to help when others are present; no one claims ownership of issues in a group.

Parkinson’s Law

Work expands to fill the time allotted; loose deadlines invite slower progress.

Hofstadter’s Law

“It always takes longer than you expect, even when you expect it to.” Highlights chronic under-estimation in software.

Bus Factor

Number of people who can vanish before a project stalls; lower numbers signal knowledge silos.

Imposter Syndrome

High achievers doubt their competence and fear exposure as frauds; affects morale and retention.

Curse of Knowledge

Experts assume others share their background; causes communication gaps with juniors or non-tech stakeholders.

Overconfidence Bias

Over-estimating one’s abilities or judgments; breeds risky decisions and unrealistic timelines.

Planning Fallacy

Underestimating task duration despite past evidence; plagues project schedules.

Groupthink

Desire for harmony suppresses dissent, leading to poor collective decisions; diversity of opinion is stifled.

Halo Effect

Positive impression in one area spills into others; a strong interview answer colors overall hiring judgment.

Recency Bias

Recent information outweighs older data; latest project dominates performance reviews.

Self-Serving Bias

Success credited to self, failure blamed on externals; obstructs honest retrospectives.

Optimism Bias

Believing negative events are less likely for oneself; underestimates security or schedule risks.

Mere-Exposure Effect

Preference grows with familiarity; teams cling to legacy tech they know best.

Not Invented Here (NIH) Syndrome

Rejecting external solutions in favor of in-house ones, even if inferior; hampers adoption of open source.

Goodhart’s Law

When a measure becomes a target, it stops being a good measure; metric gaming replaces real value.

Pareto Principle (80/20 Rule)

Roughly 80 % of outcomes stem from 20 % of causes; guides prioritization of features and bug fixes.

Zeigarnik Effect

Unfinished tasks stay prominent in memory; too many open items increase mental fatigue.

Cognitive Load

Total mental effort in working memory; drives need for clear UI, code and documentation.

Parkinson’s Law of Triviality (Bike-shedding)

Groups spend disproportionate time on minor issues, ignoring big ones.

Law of Diminishing Returns

Adding resources eventually yields smaller output gains; more engineers won’t always speed a late project.

Diffusion of Responsibility

Individuals feel less accountable when others share the task; broader form of the Bystander Effect.

Default Effect

People favor the preset option; default configs steer user and team choices.

Endowment Effect

Valuing something more simply because one owns it; reluctance to scrap in-house tools.

Loss Aversion

Pain of loss outweighs pleasure of equal gain; fuels resistance to change and risk-averse decisions.

Mere Urgency Effect

Prioritizing urgent over important tasks even when returns are lower; leads to firefighting culture.

Survivorship Bias

Focusing on visible successes and overlooking failures; misleads tech or startup lessons.

Peak-End Rule

Experiences judged by their most intense point and ending; guides UX design and project memories.

Ikea Effect

Overvaluing what one helped build; strengthens attachment to self-written code.

Blinkered Thinking (Narrow Framing)

Fixating on a limited view of the problem; ignores broader context or alternatives.

Ladder of Inference

Unconscious steps from data to action—select, interpret, assume, conclude, believe; probing data prevents snap judgments.

Fundamental Attribution Error

Over-crediting personal traits and under-valuing situational factors when explaining others’ behavior; hinders empathetic leadership.