The Study of Human Decision-Making: A Cautionary Tale from the World of Experimental Gaming

1981 ◽  
Vol 32 (3) ◽  
pp. 173 ◽  
Author(s):  
C. S. Huxham ◽  
P. G. Bennett ◽  
M. V. Lozowski ◽  
M. R. Dando
1981 ◽  
Vol 32 (3) ◽  
pp. 173-185 ◽  
Author(s):  
C. S. Huxham ◽  
P. G. Bennett ◽  
M. V. Lozowski ◽  
M. R. Dando

2018 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Thais Spiegel ◽  
Ana Carolina P V Silva

In the study of decision-making, the classical view of behavioral appropriateness or rationality was challenged by neuro and psychological reasons. The “bounded rationality” theory proposed that cognitive limitations lead decision-makers to construct simplified models for dealing with the world. Doctors' decisions, for example, are made under uncertain conditions, as without knowing precisely whether a diagnosis is correct or whether a treatment will actually cure a patient, and often under time constraints. Using cognitive heuristics are neither good nor bad per se, if applied in situations to which they have been adapted to be helpful. Therefore, this text contextualizes the human decision-making perspective to find descriptions that adhere more closely to the human decision-making process. Then, based on a literature review of cognition during decision-making, particularly in healthcare context, it addresses a model that identifies the roles of attention, categorization, memory, emotion, and their inter-relations, during the decision-making process.


2021 ◽  
pp. 1-23
Author(s):  
Lisa Herzog

Abstract More and more decisions in our societies are made by algorithms. What are such decisions like, and how do they compare to human decision-making? I contrast central features of algorithmic decision-making with three key elements—plurality, natality, and judgment—of Hannah Arendt's political thought. In “Arendtian practices,” human beings come together as equals, exchange arguments, and make joint decisions, sometimes bringing something new into the world. With algorithmic decision-making taking over more and more areas of life, opportunities for “Arendtian practices” are under threat. Moreover, there is the danger that algorithms are tasked with decisions for which they are ill-suited. Analyzing the contrast with Arendt's thinking can be a starting point for delineating realms in which algorithmic decision-making should or should not be welcomed.


2020 ◽  
Vol 9 (1) ◽  
pp. 54-68
Author(s):  
Linda Kronman

The urgency of environmental, security, economic and political crises in the early twenty-first century has propelled the use of machine vision to aid human decision-making. These developments have led to strategies in which functions of human intuitive processing have been externalized to ‘vision machines’ in the hope of optimized and objective insights. I argue that we should approach these replacements of human nonconscious functions as ‘intuition machines.’ I apply this approach through a close reading of artworks which expose the hid- den labour required to train a machine. These artworks demonstrate how human agency shapes the ways that machines perceive the world and reveal how values and biases are hardcoded into nonconscious cognitive machine vision systems. Thus, my analysis suggests that decisions made by such systems cannot be considered fundamentally objective or true. Nevertheless, artworks also exemplify how externalized intuitive processing can still be helpful as long as we refrain from blindly taking the results as a go-signal to take immediate action.


2021 ◽  
pp. 381-390
Author(s):  
Alison Buttenheim ◽  
Harsha Thirumurthy

Human behaviour is an important determinant of health outcomes around the world. Understanding how people make health-related decisions is therefore essential for explaining health outcomes globally and for developing solutions to leading challenges in global health. Behavioural economics blends theories from economics and psychology to uncover key insights about human decision-making. This chapter describes several prominent theories from behavioural economics and reviews examples of how these theories can be useful in efforts to improve global health outcomes. We begin by reviewing the theory of rational decision-making that features prominently in economics and discuss important policy implications that follow from this theory. We then turn to theories and principles from behavioural economics and draw upon empirical evidence from around the world to highlight actionable behaviour change interventions that can be useful for students of global health and practitioners alike.


2018 ◽  
Author(s):  
Siyu Wang ◽  
Robert C Wilson

Human decision making is inherently variable. While this variability is often seen as a sign of suboptimality in human behavior, recent work suggests that randomness can actually be adaptive. An example arises when we must choose between exploring unknown options or exploiting options we know well. A little randomness in these `explore-exploit' decisions is remarkably effective as it encourages us to explore options we might otherwise ignore. Moreover, people actually use such `random exploration' in practice, increasing their behavioral variability when it is more valuable to explore. Despite this progress, the nature of adaptive `decision noise' for exploration is unknown -- specifically whether it is generated internally, from stochastic processes in the brain, or externally, from stochastic stimuli in the world. Here we show that, while both internal and external noise drive variability in behavior, the noise driving random exploration is predominantly internal. This suggests that random exploration depends on adaptive noise processes in the brain which are subject to cognitive control.


2021 ◽  
Vol 3 ◽  
Author(s):  
James Ming Chen

This article explores instinctive frames of human decision-making in environmental and resource economics. Higher-moment asset pricing combines rational, mathematically informed economic reasoning with psychological and biological insights. Leptokurtic blindness and skewness preference combine in particularly challenging ways for carbon mitigation. At their worst, human heuristics may generate perverse decisions. Information uncertainty and the innate preference for bonds-and-bullets portfolios may impair responses to catastrophic climate change.


2013 ◽  
Author(s):  
Scott D. Brown ◽  
Pete Cassey ◽  
Andrew Heathcote ◽  
Roger Ratcliff

1978 ◽  
Vol 17 (01) ◽  
pp. 28-35
Author(s):  
F. T. De Dombal

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.


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