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Algorithm aversion is defined as a "biased assessment of an algorithm which manifests in negative behaviors and attitudes towards the algorithm compared to a human agent." [ 1 ] This phenomenon describes the tendency of humans to reject advice or recommendations from an algorithm in situations where they would accept the same advice if it came ...
Connectionist Learning with Adaptive Rule Induction On-line (CLARION) is a computational cognitive architecture that has been used to simulate many domains and tasks in cognitive psychology and social psychology, as well as implementing intelligent systems in artificial intelligence applications.
The supervisory attentional system provides individuals with the ability to predict and prepare for situations mentally prior to any possible encounter. Many have argued about the specific roles of the SAS in survival situations; a general understanding is that it functions to increase the chance of survival and that it operates in conjunction ...
Regulation of algorithms, or algorithmic regulation, is the creation of laws, rules and public sector policies for promotion and regulation of algorithms, particularly in artificial intelligence and machine learning. [1] [2] [3] For the subset of AI algorithms, the term regulation of artificial intelligence is used.
Regulation is now generally considered necessary to both encourage AI and manage associated risks. [19] [20] [21] Public administration and policy considerations generally focus on the technical and economic implications and on trustworthy and human-centered AI systems, [22] although regulation of artificial superintelligences is also ...
Psi-theory, developed by Dietrich Dörner at the University of Bamberg, is a systemic psychological theory covering human action regulation, intention selection and emotion. [ 1 ] [ 2 ] It models the human mind as an information processing agent, controlled by a set of basic physiological, social and cognitive drives.
Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. [1]
Soar [1] is a cognitive architecture, [2] originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University.. The goal of the Soar project is to develop the fixed computational building blocks necessary for general intelligent agents – agents that can perform a wide range of tasks and encode, use, and learn all types of knowledge to realize the full range of ...