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{{Short description|Cognitive bias}} ...[[decision science]], '''conservatism''' or '''conservatism bias''' is a [[cognitive bias|bias]] which refers to the tendency to revise one's belief insufficie ...

{{Short description|Cognitive bias}} * [[List of cognitive biases]] ...

...to argue that these solutions will mitigate [[cognitive biases|predictable biases and errors]] in judges' reasoning, such as the [[hungry judge effect]] (the ...

===Biases in decision making=== It is possible to introduce biases in [[decision making]] in the 2AFC task. For example, if one [[Stimulus (ps ...

...ignificant amount of time. Commonly confused with [[belief perseverance]], cognitive inertia is the [[perseveration|perseverance]] of how one interprets informa ...ty, group brainstorming, and business strategies. In the clinical setting, cognitive inertia has been used as a diagnostic tool for neurodegenerative diseases, ...

...ly 2021 |title=The Psychology of (In)Effective Altruism |journal=Trends in Cognitive Sciences |volume=25 |issue=7 |pages=596–607 |doi=10.1016/j.tics.2021.03.015 While plenty of studies in the behavioral sciences have demonstrated the cognitive and emotional limitations in charitable giving, some argue that the reasons ...

...t1=Robert B.|last2=Markus|first2=Hazel|date=1982-09-01|title=Affective and Cognitive Factors in Preferences|url=http://jcr.oxfordjournals.org/content/9/2/123|jo ...mizing the expected value of a utility function.<ref>{{Cite book|title=The Cognitive Basis of Institutions: A Synthesis of Behavioral and Institutional Economic ...

...V.; Fontanari, J.F.; Hourdakis, E., Integrating Language and Cognition: A Cognitive Robotics Approach, Computational Intelligence Magazine, IEEE, Volume 2, Is ...oefficients r(m), called priors in probability theory, contain preliminary biases or expectations, expected objects m have relatively high r(m) values; their ...

...ics uncover patterns in decision-making and use them to identify potential biases in judgements that are passed. A synthesis of these fields is possible thro ...ructure for Legal Arguments About Evidence Using Bayesian Networks|journal=Cognitive Science|language=en|volume=37|issue=1|pages=61–102|doi=10.1111/cogs.12004|p ...

...denberg (1968) "Genetic and environmental components in the covariation of cognitive abilities: An additive model", in [https://www.dropbox.com/s/uwhcnw4m2p5hbf ...ite journal|doi=10.1038/mp.2015.225|title=Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 G ...

====Heuristics and biases==== ...=Kahneman |first2=Daniel |title=Judgment under Uncertainty: Heuristics and Biases |journal=Science |date=1974 |volume=185 |issue=4157 |pages=1124–1131|doi=10 ...

...c rationalized away, but nonetheless impact decision-making. To counteract biases, it is insufficient simply be aware of their characteristics, but necessary ...

...siveness to naturally occurring positive stimuli is a crucial element that biases the individual towards the use of substances or behaviours and away from no ...vulnerability or resilience to substance use disorders|journal = Trends in Cognitive Sciences|volume = 18|issue = 4|pages = 211–217|year = 2014|last1 = Belcher| ...

...anguage corpora, but they also inherit inaccuracies and [[Algorithmic bias|biases]] present in the [[Training, validation, and test data sets|data]] they are ...(i.e. amount of neurons in its layers, amount of weights between them and biases), ...

...of extreme events, due to ignorance, misaligned incentives, and cognitive biases, there is often a failure to adequately anticipate them. Technically speaki ...

...hanging [[Parameters (computer science)|parameters]] (e.g. the weights and biases of a deep neural network) between these local nodes at some frequency to ge * Lack of access to global training data makes it harder to identify unwanted biases entering the training e.g. age, gender, sexual orientation; ...

...failure that is due to asymmetric information or the borrowers' cognitive biases or limitations.<ref>{{Cite journal|last=Bhutta|first=Neil|date=June 2012|ti ...

...rk]]s, [[computer network]]s, [[biological network]]s, [[Cognitive network|cognitive]] and [[semantic network]]s, and [[social network]]s, considering distinct ...fy the main themes and topics (e.g., of [[social media]] posts), to reveal biases (e.g., in news coverage), or even to map an entire research field.<ref>{{ci ...

...tps://www.sciencedirect.com/science/article/pii/S0364021382800013 |journal=Cognitive Science |volume=6 |issue=3 |pages=205–254 |doi=10.1016/S0364-0213(82)80001- ...hip.org/uc/item/0570j1dp |journal=Proceedings of the Annual Meeting of the Cognitive Science Society |language=en |volume=9}}</ref> A slow neural network learns ...

...e generalized principles that characterize a given dataset rather than the biases of a poorly-populated set.<ref>{{Cite journal |last=Kurtzman |first=Thomas ...(typically real numbers). Learning consists of iteratively adjusting these biases and weights. ...