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The social process of peer review aims to mitigate the effect of individual scientists' biases, even though the peer review process itself may be susceptible to such biases [99] [100] [93] [101] [102] Confirmation bias may thus be especially harmful to objective evaluations regarding nonconforming results since biased individuals may regard ...
Explanations include information-processing rules (i.e., mental shortcuts), called heuristics, that the brain uses to produce decisions or judgments. Biases have a variety of forms and appear as cognitive ("cold") bias, such as mental noise, [5] or motivational ("hot") bias, such as when beliefs are distorted by wishful thinking. Both effects ...
Status quo bias should be distinguished from a rational preference for the status quo ante, as when the current state of affairs is objectively superior to the available alternatives, or when imperfect information is a significant problem. A large body of evidence, however, shows that status quo bias frequently affects human decision-making. [63]
Motivated reasoning (motivational bias) is an unconscious or conscious process by which personal emotions control the evidence that is supported or dismissed. However, confirmation bias is mainly an unconscious (innate, implicit) cognitive bias, and the evidence or arguments utilised can be logical as well as emotional.
The availability heuristic, also known as availability bias, is a mental shortcut that relies on immediate examples that come to a given person's mind when evaluating a specific topic, concept, method, or decision.
“Even anecdotal evidence of supposed bias tends to crumble under close examination.” In fact, the report, produced by the NYU Stern Center for Business and Human Rights, cited evidence that ...
Statistical bias exists in numerous stages of the data collection and analysis process, including: the source of the data, the methods used to collect the data, the estimator chosen, and the methods used to analyze the data. Data analysts can take various measures at each stage of the process to reduce the impact of statistical bias in their ...
“If bias encoding cannot be avoided at the algorithm stage, its identification enables a range of stakeholders relevant to the AI health technology's use (developers, regulators, health policy ...