Results 101 to 110 of about 6,437 (212)
Policy Studies Journal, Volume 54, Issue 4, November 2026.ABSTRACT Artificial intelligence (AI) has gained much interest in public administration and public policy fields in recent years. Research on and that uses AI has so far treated it as an object or context within the broader administrative and governance discourse.
Yanto Chandra, Jianxiang Tan
wiley +1 more source
Leveraging AI for improving student writing in MBA case analyses: The MBABot initiative
Decision Sciences Journal of Innovative Education, Volume 24, Issue 4, October 2026.Abstract This teaching brief discusses the development and implementation of MBABot, a custom GPT‐based AI tool designed to support writing‐intensive decision sciences course titled Delivering Business Value Through Information Systems. This MBA‐level course examines the role of business leaders in evaluating information systems and information ...
Craig Geter, John R. Drake
wiley +1 more source
Medical Education, Volume 60, Issue 10, Page 1102-1109, October 2026.Abstract Objective The purpose of the study reported in this article was to shed light on the cognitive mechanism mediating between biasing information and diagnostic error. The literature suggests at least two different hypotheses: premature closure leading biased participants to spend less time on diagnosis or increased competition between diagnostic
Awad Al Essa +5 more
wiley +1 more source
Debiasing framing effects through counterexplanation
, 2000 This paper reports the results of an experiment examining the framing bias in going concern context and counterexplanation as a potentail debiasing technique. Results indicate that without the debiasing technique, significant framing effects were present.
Tan, Ming Peng +2 more
core
Data linked to the paper "Debiasing in motion: Boosting sound intuiting through animated video training" in Acta Psychologica, 2025.
Wim De Neys +2 more
core +1 more source
Biases and debiasing in human and artificial intelligence
Oñati Socio-Legal SeriesWhen we make decisions or argue, cognitive, emotional, and motivational factors often lead us to use mental shortcuts. These can speed up reasoning but can also lead to systematic biases.
Patrizia Catellani, Marco Piastra
doaj +1 more source
Debiased Recommendation with Noisy Feedback
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data MiningRatings of a user to most items in recommender systems are usually missing not at random (MNAR), largely because users are free to choose which items to rate. To achieve unbiased learning of the prediction model under MNAR data, three typical solutions have been proposed, including error-imputation-based (EIB), inverse-propensity-scoring (IPS), and ...
Haoxuan Li 0001 +5 more
openaire +3 more sources
Debiasing Health-Related Judgments and Decision Making: A Systematic Review
, 2017 Background. Being confronted with uncertainty in the context of health-related judgments and decision making can give rise to the occurrence of systematic biases. These biases may detrimentally affect lay persons and health experts alike. Debiasing aims
Ramona Ludolph, Peter J. Schulz
core +1 more source
Critical Thinking Education and Debiasing (AILACT Essay Prize Winner 2013)
Informal Logic, 2014 There are empirical grounds to doubt the effectiveness of a common and intuitive approach to teaching debiasing strategies in critical thinking courses. We summarize some of the grounds before suggesting a broader taxonomy of debiasing strategies.
Guillaume Beaulac, Tim Kenyon
doaj
Debiasing Recommendation with Personal Popularity
Proceedings of the ACM Web Conference 2024Global popularity (GP) bias is the phenomenon that popular items are recommended much more frequently than they should be, which goes against the goal of providing personalized recommendations and harms user experience and recommendation accuracy. Many methods have been proposed to reduce GP bias but they fail to notice the fundamental problem of GP, i.
Wentao Ning +6 more
openaire +2 more sources