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Normalcy bias, or normality bias, is a cognitive bias which leads people to disbelieve or minimize threat warnings. [1] Consequently, individuals underestimate the likelihood of a disaster, when it might affect them, and its potential adverse effects. [ 2 ]
Normalcy bias, a form of cognitive dissonance, is the refusal to plan for, or react to, a disaster which has never happened before. Effort justification is a person's tendency to attribute greater value to an outcome if they had to put effort into achieving it.
Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).
The Cognitive Bias Codex. A cognitive bias is a systematic pattern of deviation from norm or rationality in judgment. [1] Individuals create their own "subjective reality" from their perception of the input. An individual's construction of reality, not the objective input, may dictate their behavior in the world.
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Normalization of deviance, according to American sociologist Diane Vaughan, is the process in which deviance from correct or proper behavior or rule becomes culturally normalized.
Growing fears over liberal bias embedded in artificial intelligence (AI) services such as ChatGPT led TUSK CEO Jeff Bermant to unveil the creation of a new conservative chatbot known as GIPPR in ...
It is difficult for people to determine if such decisions are fair and trustworthy, leading potentially to bias in AI systems going undetected, or people rejecting the use of such systems. This has led to advocacy and in some jurisdictions legal requirements for explainable artificial intelligence. [68]