Working Memory, Cognitive Miserliness and Logic As Predictors of Performance on the Cognitive Reflection Test
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Addressing Cognitive Biases in Augmented Business Decision Systems Human Performance Metrics for Generic AI-Assisted Decision Making
Addressing Cognitive Biases in Augmented Business Decision Systems Human performance metrics for generic AI-assisted decision making. THOMAS BAUDEL* IBM France Lab, Orsay, France MANON VERBOCKHAVEN IBM France Lab & ENSAE VICTOIRE COUSERGUE IBM France Lab, Université Paris-Dauphine & Mines ParisTech GUILLAUME ROY IBM France Lab & ENSAI RIDA LAARACH IBM France Lab, Telecom ParisTech & HEC How do algorithmic decision aids introduced in business decision processes affect task performance? In a first experiment, we study effective collaboration. Faced with a decision, subjects alone have a success rate of 72%; Aided by a recommender that has a 75% success rate, their success rate reaches 76%. The human-system collaboration had thus a greater success rate than each taken alone. However, we noted a complacency/authority bias that degraded the quality of decisions by 5% when the recommender was wrong. This suggests that any lingering algorithmic bias may be amplified by decision aids. In a second experiment, we evaluated the effectiveness of 5 presentation variants in reducing complacency bias. We found that optional presentation increases subjects’ resistance to wrong recommendations. We conclude by arguing that our metrics, in real usage scenarios, where decision aids are embedded as system-wide features in Business Process Management software, can lead to enhanced benefits. CCS CONCEPTS • Cross-computing tools and techniques: Empirical studies, Information Systems: Enterprise information systems, Decision support systems, Business Process Management, Human-centered computing, Human computer interaction (HCI), Visualization, Machine Learning, Automation Additional Keywords and Phrases: Business decision systems, Decision theory, Cognitive biases * [email protected]. 1 INTRODUCTION For the past 20 years, Business Process Management (BPM) [29] and related technologies such as Business Rules [10, 52] and Robotic Process Automation [36] have streamlined processes and operational decision- making in large enterprises, transforming work organization. -
2020 WGEA Regional Meeting Abstract Compendium
2020 WGEA Regional Meeting Abstract Compendium Table of Contents Message from WGEA Chair ........................................................................................................... 2 Message from WGEA Conference/ Host Chairs ............................................................................ 3 Special Thanks and Acknowledgments .......................................................................................... 4 WGEA Awards ............................................................................................................................... 5 Innovation Abstracts ....................................................................................................................... 6 Research Abstracts ........................................................................................................................ 85 Small Group, Workshop and Panel Discussion Abstracts .......................................................... 155 List of WGEA Steering Committee members ............................................................................ 273 List of WGEA Planning Committee and Subcommittees members ........................................... 274 2020 WGEA Reviewer List ........................................................................................................ 275 1 Message from WGEA Chair On behalf of the Western Group on Educational Affairs (WGEA) Steering Committee, I welcome you to the WGEA 2020 Annual Spring Meeting, Finding Common Ground. We will highlight the following -
The Status Quo Bias and Decisions to Withdraw Life-Sustaining Treatment
HUMANITIES | MEDICINE AND SOCIETY The status quo bias and decisions to withdraw life-sustaining treatment n Cite as: CMAJ 2018 March 5;190:E265-7. doi: 10.1503/cmaj.171005 t’s not uncommon for physicians and impasse. One factor that hasn’t been host of psychological phenomena that surrogate decision-makers to disagree studied yet is the role that cognitive cause people to make irrational deci- about life-sustaining treatment for biases might play in surrogate decision- sions, referred to as “cognitive biases.” Iincapacitated patients. Several studies making regarding withdrawal of life- One cognitive bias that is particularly show physicians perceive that nonbenefi- sustaining treatment. Understanding the worth exploring in the context of surrogate cial treatment is provided quite frequently role that these biases might play may decisions regarding life-sustaining treat- in their intensive care units. Palda and col- help improve communication between ment is the status quo bias. This bias, a leagues,1 for example, found that 87% of clinicians and surrogates when these con- decision-maker’s preference for the cur- physicians believed that futile treatment flicts arise. rent state of affairs,3 has been shown to had been provided in their ICU within the influence decision-making in a wide array previous year. (The authors in this study Status quo bias of contexts. For example, it has been cited equated “futile” with “nonbeneficial,” The classic model of human decision- as a mechanism to explain patient inertia defined as a treatment “that offers no rea- making is the rational choice or “rational (why patients have difficulty changing sonable hope of recovery or improvement, actor” model, the view that human beings their behaviour to improve their health), or because the patient is permanently will choose the option that has the best low organ-donation rates, low retirement- unable to experience any benefit.”) chance of satisfying their preferences. -
A Task-Based Taxonomy of Cognitive Biases for Information Visualization
A Task-based Taxonomy of Cognitive Biases for Information Visualization Evanthia Dimara, Steven Franconeri, Catherine Plaisant, Anastasia Bezerianos, and Pierre Dragicevic Three kinds of limitations The Computer The Display 2 Three kinds of limitations The Computer The Display The Human 3 Three kinds of limitations: humans • Human vision ️ has limitations • Human reasoning 易 has limitations The Human 4 ️Perceptual bias Magnitude estimation 5 ️Perceptual bias Magnitude estimation Color perception 6 易 Cognitive bias Behaviors when humans consistently behave irrationally Pohl’s criteria distilled: • Are predictable and consistent • People are unaware they’re doing them • Are not misunderstandings 7 Ambiguity effect, Anchoring or focalism, Anthropocentric thinking, Anthropomorphism or personification, Attentional bias, Attribute substitution, Automation bias, Availability heuristic, Availability cascade, Backfire effect, Bandwagon effect, Base rate fallacy or Base rate neglect, Belief bias, Ben Franklin effect, Berkson's paradox, Bias blind spot, Choice-supportive bias, Clustering illusion, Compassion fade, Confirmation bias, Congruence bias, Conjunction fallacy, Conservatism (belief revision), Continued influence effect, Contrast effect, Courtesy bias, Curse of knowledge, Declinism, Decoy effect, Default effect, Denomination effect, Disposition effect, Distinction bias, Dread aversion, Dunning–Kruger effect, Duration neglect, Empathy gap, End-of-history illusion, Endowment effect, Exaggerated expectation, Experimenter's or expectation bias, -
Avoiding the Conjunction Fallacy: Who Can Take a Hint?
Avoiding the conjunction fallacy: Who can take a hint? Simon Klein Spring 2017 Master’s thesis, 30 ECTS Master’s programme in Cognitive Science, 120 ECTS Supervisor: Linnea Karlsson Wirebring Acknowledgments: The author would like to thank the participants for enduring the test session with challenging questions and thereby making the study possible, his supervisor Linnea Karlsson Wirebring for invaluable guidance and good questions during the thesis work, and his fiancée Amanda Arnö for much needed mental support during the entire process. 2 AVOIDING THE CONJUNCTION FALLACY: WHO CAN TAKE A HINT? Simon Klein Humans repeatedly commit the so called “conjunction fallacy”, erroneously judging the probability of two events occurring together as higher than the probability of one of the events. Certain hints have been shown to mitigate this tendency. The present thesis investigated the relations between three psychological factors and performance on conjunction tasks after reading such a hint. The factors represent the understanding of probability and statistics (statistical numeracy), the ability to resist intuitive but incorrect conclusions (cognitive reflection), and the willingness to engage in, and enjoyment of, analytical thinking (need-for-cognition). Participants (n = 50) answered 30 short conjunction tasks and three psychological scales. A bimodal response distribution motivated dichotomization of performance scores. Need-for-cognition was significantly, positively correlated with performance, while numeracy and cognitive reflection were not. The results suggest that the willingness to engage in, and enjoyment of, analytical thinking plays an important role for the capacity to avoid the conjunction fallacy after taking a hint. The hint further seems to neutralize differences in performance otherwise predicted by statistical numeracy and cognitive reflection. -
Cognitive Bias Mitigation: How to Make Decision-Making More Rational?
Cognitive Bias Mitigation: How to make decision-making more rational? Abstract Cognitive biases distort judgement and adversely impact decision-making, which results in economic inefficiencies. Initial attempts to mitigate these biases met with little success. However, recent studies which used computer games and educational videos to train people to avoid biases (Clegg et al., 2014; Morewedge et al., 2015) showed that this form of training reduced selected cognitive biases by 30 %. In this work I report results of an experiment which investigated the debiasing effects of training on confirmation bias. The debiasing training took the form of a short video which contained information about confirmation bias, its impact on judgement, and mitigation strategies. The results show that participants exhibited confirmation bias both in the selection and processing of information, and that debiasing training effectively decreased the level of confirmation bias by 33 % at the 5% significance level. Key words: Behavioural economics, cognitive bias, confirmation bias, cognitive bias mitigation, confirmation bias mitigation, debiasing JEL classification: D03, D81, Y80 1 Introduction Empirical research has documented a panoply of cognitive biases which impair human judgement and make people depart systematically from models of rational behaviour (Gilovich et al., 2002; Kahneman, 2011; Kahneman & Tversky, 1979; Pohl, 2004). Besides distorted decision-making and judgement in the areas of medicine, law, and military (Nickerson, 1998), cognitive biases can also lead to economic inefficiencies. Slovic et al. (1977) point out how they distort insurance purchases, Hyman Minsky (1982) partly blames psychological factors for economic cycles. Shefrin (2010) argues that confirmation bias and some other cognitive biases were among the significant factors leading to the global financial crisis which broke out in 2008. -
Critical Thinking Education and Debiasing
Critical Thinking Education and Debiasing TIM KENYON University of Waterloo Department of Philosophy 200 University Avenue West Waterloo, ON N2L 3G1 Canada [email protected] GUILLAUME BEAULAC Yale University Department of Philosophy 344 College St. New Haven, CT. 06511-6629 USA [email protected] Abstract: There are empirical Résumé: Des données empiriques grounds to doubt the effectiveness of nous permettent de douter de a common and intuitive approach to l'efficacité d'une approche commune teaching debiasing strategies in et intuitive pour enseigner des critical thinking courses. We stratégies de correction de biais summarize some of the grounds cognitifs dans les cours de pensée before suggesting a broader critique. Nous résumons certains de taxonomy of debiasing strategies. ces résultats empiriques avant de This four-level taxonomy enables a suggérer une taxonomie plus useful diagnosis of biasing factors étendue de ces stratégies de and situations, and illuminates more correction de biais. Cette taxonomie strategies for more effective bias à quatre niveaux permet un mitigation located in the shaping of diagnostic utile de facteurs causant situational factors and reasoning les biais et elle met en évidence infrastructure—sometimes called davantage de stratégies permettant la “nudges” in the literature. The correction plus efficace de biais, question, we contend, then becomes stratégies situées dans des mesures how best to teach the construction modifiant les infrastructures et les and use of such infrastructures. environnements cognitifs ("nudge" dans la littérature). Nous soutenons que la question porte dès lors sur les meilleures façons d'enseigner la construction et l'utilisation de ces infrastructures. Keywords: Critical thinking, biases, debiasing, education, nudges © Tim Kenyon and Guillaume Beaulac, Informal Logic, Vol. -
Graphical Techniques in Debiasing: an Exploratory Study
GRAPHICAL TECHNIQUES IN DEBIASING: AN EXPLORATORY STUDY by S. Bhasker Information Systems Department Leonard N. Stern School of Business New York University New York, New York 10006 and A. Kumaraswamy Management Department Leonard N. Stern School of Business New York University New York, NY 10006 October, 1990 Center for Research on Information Systems Information Systems Department Leonard N. Stern School of Business New York University Working Paper Series STERN IS-90-19 Forthcoming in the Proceedings of the 1991 Hawaii International Conference on System Sciences Center for Digital Economy Research Stem School of Business IVorking Paper IS-90-19 Center for Digital Economy Research Stem School of Business IVorking Paper IS-90-19 2 Abstract Base rate and conjunction fallacies are consistent biases that influence decision making involving probability judgments. We develop simple graphical techniques and test their eflcacy in correcting for these biases. Preliminary results suggest that graphical techniques help to overcome these biases and improve decision making. We examine the implications of incorporating these simple techniques in Executive Information Systems. Introduction Today, senior executives operate in highly uncertain environments. They have to collect, process and analyze a deluge of information - most of it ambiguous. But, their limited information acquiring and processing capabilities constrain them in this task [25]. Increasingly, executives rely on executive information/support systems for various purposes like strategic scanning of their business environments, internal monitoring of their businesses, analysis of data available from various internal and external sources, and communications [5,19,32]. However, executive information systems are, at best, support tools. Executives still rely on their mental or cognitive models of their businesses and environments and develop heuristics to simplify decision problems [10,16,25]. -
Can Animal Data Translate to Innovations Necessary for a New
Green BMC Medical Ethics (2015) 16:53 DOI 10.1186/s12910-015-0043-7 DEBATE Open Access Can animal data translate to innovations necessary for a new era of patient-centred and individualised healthcare? Bias in preclinical animal research Susan Bridgwood Green Abstract Background: The public and healthcare workers have a high expectation of animal research which they perceive as necessary to predict the safety and efficacy of drugs before testing in clinical trials. However, the expectation is not always realised and there is evidence that the research often fails to stand up to scientific scrutiny and its 'predictive value' is either weak or absent. Discussion: Problems with the use of animals as models of humans arise from a variety of biases and systemic failures including: 1) bias and poor practice in research methodology and data analysis; 2) lack of transparency in scientific assessment and regulation of the research; 3) long-term denial of weaknesses in cross-species translation; 4) profit-driven motives overriding patient interests; 5) lack of accountability of expenditure on animal research; 6) reductionist-materialism in science which tends to dictate scientific inquiry and control the direction of funding in biomedical research. Summary: Bias in animal research needs to be addressed before medical research and healthcare decision-making can be more evidence-based. Research funding may be misdirected on studying 'disease mechanisms' in animals that cannot be replicated outside tightly controlled laboratory conditions, and without sufficient critical evaluation animal research may divert attention away from avenues of research that hold promise for human health. The potential for harm to patients and trial volunteers from reliance on biased animal data1 requires measures to improve its conduct, regulation and analysis. -
Higher Education Reform: Getting the Incentives Right
Higher Education Reform: Getting the Incentives Right CPB Netherlands Bureau for Economic Policy Analysis CHEPS Van Stolkweg 14 University of Twente P.O. Box 80510 P.O. Box 217 2508 GM The Hague, The Netherlands 7500 AE Enschede, the Netherlands ISBN 90 5833 065 6 2 Contents Contents Preface 9 Introduction 11 1 The Dutch higher education system 15 1.1 Binary system 15 1.2 Formal tasks 16 1.3Types of institutions 16 1.4 Funding structure 17 1.5 Public expenditures on higher education 19 1.6 Tuition fee policies 21 1.7 Student support system 23 1.8 Admission policies 24 1.9 Quality control 25 1.10 Enrollment 26 Annex:Public funding of higher education in the Netherlands, performance-based models 29 2 Economics of higher education 35 2.1 Why do people attend higher education? 35 2.1.1 The human capital approach 35 2.1.2 The signalling approach 36 2.1.3How high are the financial and non-financial returns to higher education? 36 2.2 Why public support of higher education? 38 2.2.1 Human capital spillovers 38 2.2.2 Capital market constraints 39 2.2.3Risk 40 2.2.4 Imperfect information and transparency 41 2.2.5 Income redistribution 42 2.2.6 Tax distortions 42 2.3How to fund higher education? 42 2.3.1 Student support 43 2.3.2 Funding of higher education institutions 43 2.4 Public versus private provision of higher education 44 2.5 Should the higher education sector be deregulated? 45 2.6 Why combine education and research in universities? 46 5 Higher Education Reform: Getting the Incentives Right 2.7 Why and when should research be publicly funded? -
Bias and Fairness in NLP
Bias and Fairness in NLP Margaret Mitchell Kai-Wei Chang Vicente Ordóñez Román Google Brain UCLA University of Virginia Vinodkumar Prabhakaran Google Brain Tutorial Outline ● Part 1: Cognitive Biases / Data Biases / Bias laundering ● Part 2: Bias in NLP and Mitigation Approaches ● Part 3: Building Fair and Robust Representations for Vision and Language ● Part 4: Conclusion and Discussion “Bias Laundering” Cognitive Biases, Data Biases, and ML Vinodkumar Prabhakaran Margaret Mitchell Google Brain Google Brain Andrew Emily Simone Parker Lucy Ben Elena Deb Timnit Gebru Zaldivar Denton Wu Barnes Vasserman Hutchinson Spitzer Raji Adrian Brian Dirk Josh Alex Blake Hee Jung Hartwig Blaise Benton Zhang Hovy Lovejoy Beutel Lemoine Ryu Adam Agüera y Arcas What’s in this tutorial ● Motivation for Fairness research in NLP ● How and why NLP models may be unfair ● Various types of NLP fairness issues and mitigation approaches ● What can/should we do? What’s NOT in this tutorial ● Definitive answers to fairness/ethical questions ● Prescriptive solutions to fix ML/NLP (un)fairness What do you see? What do you see? ● Bananas What do you see? ● Bananas ● Stickers What do you see? ● Bananas ● Stickers ● Dole Bananas What do you see? ● Bananas ● Stickers ● Dole Bananas ● Bananas at a store What do you see? ● Bananas ● Stickers ● Dole Bananas ● Bananas at a store ● Bananas on shelves What do you see? ● Bananas ● Stickers ● Dole Bananas ● Bananas at a store ● Bananas on shelves ● Bunches of bananas What do you see? ● Bananas ● Stickers ● Dole Bananas ● Bananas -
Curriculum Reform at Tertiary Level As Key to Graduate Employability and Entrepreneurship in Lesotho
Journal of US-China Public Administration, June 2017, Vol. 14, No. 6, 339-347 doi: 10.17265/1548-6591/2017.06.005 D DAVID PUBLISHING Curriculum Reform at Tertiary Level as Key to Graduate Employability and Entrepreneurship in Lesotho T. Mukurunge, N. Tlali Limkokwing University of Creative Technology, Maseru, Lesotho The curriculum in Lesotho at tertiary level does not adequately prepare graduates for the employment world, nor for self-made business people. The main emphasis is theoretical and academic excellence rather than for production in industry or for empowerment with entrepreneurial skills. This is a problem because Lesotho does not have an industrial power base for the economy to employ a big number of tertiary graduates. The industries that offer employment to citizens are mainly the Chinese-owned textile industries and taxi/transport industry, or the South African mines and farms which require cheap labour and not tertiary graduates. Lesotho therefore requires an education that produces graduates who can create employment for other primarily or highly skilled technocrats who will be able to be employed above the level of mere labourers in the sophisticated economy of South Africa. This study therefore sought to establish what the Ministry of Education and tertiary institutions are doing about this scenario, whether they have plans for curriculum review that will be aligned towards producing entrepreneurs and technocrats for the economic development of Lesotho. This research will benefit the authorities responsible for development through small businesses, the employment sector, as well as tertiary institutions in curriculum review. Keywords: curriculum, curriculum review, entrepreneurship, tertiary institutions, technocrats Curriculum is a planned and guided learning experiences carried out in the institution for the purpose of living a useful and productive life in our contemporary society today (Ogwu, Omeje, & Nwokenna, 2014, p.