Affinity Bias
The tendency to favor people who are similar to oneself in terms of background, beliefs, or interests. Important for recognizing and mitigating bias in user research and team dynamics.
164 topics found for:
“design biases”
Assumed Similarity Bias
A cognitive bias where people assume others share the same beliefs, values, or preferences as themselves. Important for helping designers avoid projecting their own biases and assumptions onto users during research and design.
Framing Bias
A cognitive bias where people's decisions are influenced by how information is presented rather than just the information itself. Crucial for designers to minimize bias in how information is presented to users.
Similar To Me Bias
A cognitive bias where individuals favor others who are perceived to be similar to themselves, affecting judgments and decision-making. Crucial for understanding biases in team dynamics and decision-making processes among designers.
Confirmation Bias
The tendency to search for, interpret, and remember information in a way that confirms one's preexisting beliefs or hypotheses. Crucial for understanding cognitive biases that affect user decision-making and designing interventions to mitigate them.
Social Desirability Bias
The tendency for individuals to present themselves in a favorable light by overreporting good behavior and underreporting bad behavior in surveys or research. Crucial for designing research methods that mitigate biases and obtain accurate data.
Mood-Congruent Memory Bias
The tendency for individuals to recall information that is consistent with their current mood. Important for understanding how mood affects memory and designing experiences that account for emotional states.
Illusion of Transparency
A cognitive bias where individuals overestimate how well their thoughts, feelings, and emotions are understood by others. Crucial for designing communication and user interfaces that account for and mitigate this bias.
Horn Effect
A cognitive bias where one negative trait of a person or thing influences the perception of other traits. Important for designing experiences that counteract or mitigate negative biases in user perception.
Functional Fixedness
A cognitive bias that limits a person to using an object only in the way it is traditionally used. Important for designers to foster creative problem-solving and innovation.
Halo Effect
A cognitive bias where the perception of one positive trait influences the perception of other unrelated traits. Important for designers to manage and utilize this bias effectively in user experience design.
Worse-Than-Average Effect
A cognitive bias where individuals underestimate their own abilities and performance relative to others, believing they are worse than average. Important for understanding self-perception biases among designers and designing systems that support accurate self-assessment.
Curse Of Knowledge
A cognitive bias where someone mistakenly assumes that others have the same background knowledge they do. Essential for designers to ensure communications and products are clear and accessible to all users, regardless of their background knowledge.
Third-Person Effect
A cognitive bias where people tend to believe that others are more affected by media messages and persuasive communications than they are themselves. Important for understanding media influence and designing communications that account for this bias in user perception.
Berkson’s Paradox
A statistical phenomenon where two independent events appear to be correlated due to a selection bias. Important for accurately interpreting data and avoiding misleading conclusions.
Perky Effect
A phenomenon where vivid mental images can interfere with actual perception, causing individuals to mistake imagined experiences for real ones. Important for ensuring that marketing and product design set realistic user expectations to avoid disappointment and maintain brand integrity.
Bizarreness Effect
A cognitive bias where bizarre or unusual information is better remembered than common information. Useful for designers to create memorable and engaging user experiences by incorporating unique elements.
Placement Bias
A cognitive bias where people overemphasize information that is placed prominently or in a way that catches their attention first. Crucial for designing interfaces and information displays that manage user attention effectively.
Omission Bias
A cognitive bias where people judge harmful actions as worse, or less moral, than equally harmful omissions (inactions). Important for understanding user decision-making and designing systems that mitigate this bias.
Ratio Bias
A cognitive bias where people judge the likelihood of an event based on its relative size rather than absolute probability. Important for understanding user decision-making biases and designing systems that present information accurately.
Truth Bias
The tendency for people to believe that others are telling the truth, leading to a general assumption of honesty in communication. Important for understanding communication dynamics and designing systems that account for this bias.
Egocentric Bias
A cognitive bias where people rely too heavily on their own perspective and experiences when making decisions. Important for designers to recognize and mitigate their own perspectives influencing design decisions.
Observer Bias
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes. Essential for ensuring the accuracy and reliability of research and data collection.
Proportionality Bias
The tendency to believe that large or significant events must have large or significant causes. Important for understanding cognitive biases in decision-making and designing systems that present accurate causal relationships.
Survivorship Bias
A cognitive bias that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
Courtesy Bias
The tendency for individuals to give positive responses or feedback out of politeness, regardless of their true feelings. Crucial for obtaining honest and accurate user feedback.
Projection Bias
The tendency to overestimate how much our future preferences and behaviors will align with our current preferences and behaviors. Important for understanding user behavior and designing experiences that account for changes over time.
Experimenter Bias
A bias that occurs when researchers' expectations influence the outcome of a study. Crucial for designing research methods that ensure objectivity and reliability.
Ingroup Bias
A cognitive bias where people favor members of their own group over those in other groups. Important for designing inclusive and equitable experiences for users.
Information Bias
A cognitive bias where people seek out more information than is needed to make a decision, often leading to analysis paralysis. Crucial for designing decision-making processes that avoid information overload for users.
Impact Bias
The tendency to overestimate the duration or intensity of the emotional impact of future events. Important for understanding user expectations and satisfaction.
Normalcy Bias
The tendency to believe that things will always function the way they normally have, often leading to underestimation of disaster risks. Important for understanding risk perception and designing systems that effectively communicate potential changes.
Familiarity Bias
A cognitive bias where people prefer familiar things over unfamiliar ones, even if the unfamiliar options are objectively better. Useful for designing interfaces and products that leverage familiar elements to enhance user comfort.
Availability Bias
A cognitive bias where people overestimate the importance of information that is readily available. Essential for designers to understand and mitigate how easily accessible information can disproportionately influence decisions.
Salience Bias
A cognitive bias where people focus on the most noticeable or prominent information while ignoring less conspicuous details. Important for understanding user decision-making and ensuring balanced presentation of information.
Response Bias
A tendency for respondents to answer questions in a manner that is not truthful or accurate, often influenced by social desirability or survey design. Important for understanding and mitigating biases in survey and research data.
Negativity Bias
The tendency to give more weight to negative experiences or information than positive ones. Crucial for understanding user behavior and designing systems that balance positive and negative feedback.
Hostile Attribution Bias
A cognitive bias where individuals interpret others' behaviors as having hostile intent, even when the behavior is ambiguous or benign. Important for understanding user interactions and designing experiences that mitigate negative interpretations.
Status Quo Bias
A cognitive bias that leads individuals to prefer things to remain the same rather than change, often resisting new options or changes. Crucial for understanding resistance to change and designing strategies to overcome it among users.
Restraint Bias
A cognitive bias where individuals overestimate their ability to control impulsive behavior, leading to overexposure to temptations. Important for designing systems that help users manage self-control and avoid overexposure to temptations.
Hindsight Bias
A cognitive bias where people perceive past events as having been more predictable than they actually were. Important for understanding and mitigating biases in user feedback and decision-making.
Shared Information Bias
A cognitive bias where group members tend to discuss information that everyone already knows rather than sharing unique information, leading to less effective decision-making. Important for understanding group dynamics and improving the quality of collaborative decision-making among designers.
Regressive Bias
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean. Crucial for understanding decision-making and judgment under uncertainty.
Selection Bias
A bias that occurs when the sample chosen for a study or survey is not representative of the population being studied, affecting the validity of the results. Important for ensuring the accuracy and reliability of research findings and avoiding skewed data.
Illusory Superiority
A cognitive bias where individuals overestimate their own abilities, qualities, or performance relative to others. Important for understanding user self-perception and designing systems that account for inflated self-assessments.
Gambler’s Fallacy
A cognitive bias where individuals believe that past random events affect the probabilities of future random events. Important for designers to understand user decision-making biases related to randomness.
Hard-Easy Effect
A cognitive bias where people overestimate the probability of success for difficult tasks and underestimate it for easy tasks. Useful for designers to understand user confidence and design
Law of the Instrument
Also known as "Maslow's Hammer," a cognitive bias where people rely too heavily on a familiar tool or method, often summarized as "if all you have is a hammer, everything looks like a nail.". Important for designers to recognize and avoid over-reliance on familiar methods in problem-solving and design.
Illusory Truth Effect
A cognitive bias where repeated statements are more likely to be perceived as true, regardless of their actual accuracy. Crucial for understanding how repetition influences beliefs and designing communication strategies for users.
Perceptual Set
The tendency to perceive and interpret information based on prior experiences and expectations, influencing how different users perceive design differently. Important for designing interfaces that meet user expectations, improving usability and intuitive navigation.
Less Is Better Effect
A cognitive bias where people prefer a smaller set of higher-quality options over a larger set with lower overall quality. Useful for designing product offerings and experiences that emphasize quality over quantity for users.
Introspection Illusion
A cognitive bias where people wrongly believe they have direct insight into the origins of their mental states, while treating others' introspections as unreliable. Important for designing experiences that account for discrepancies between user self-perception and actual behavior.
Empathy Gap
A cognitive bias where people underestimate the influence of emotional states on their own and others' behavior. Crucial for designers to account for varying user emotional states in experience design.
Ambiguity Effect
A cognitive bias where decision-making is affected by the lack of information or uncertainty. Important for understanding and mitigating user decision-making biases due to uncertainty or lack of information.
Base Rate Fallacy
A cognitive bias where people ignore general statistical information in favor of specific information. Critical for designers to use general statistical information to improve decision-making accuracy and avoid bias.
Affective Forecasting
The process of predicting how one will feel in the future, which often involves biases and inaccuracies. Important for understanding user behavior and decision-making, aiding in the design of better user experiences.
Illusion of Completeness
A cognitive bias where users believe they have explored all available content, even when more is present. Important for designing interfaces that clearly indicate the presence of additional content.
Boundary Extension
A cognitive bias where people remember scenes as being more expansive than they actually were. Important for understanding how users perceive and recall visual information, aiding in better visual design decisions.
Positivity Effect
A cognitive bias where individuals tend to focus on positive information or events more than negative ones, especially as they age. Useful for understanding user preferences and designing experiences that emphasize positive outcomes.
Overconfidence Effect
A cognitive bias where a person's subjective confidence in their judgments is greater than their objective accuracy. Crucial for understanding user decision-making and designing systems that account for overconfidence.