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Medical Ethics
Published in Howard Winet, Ethics for Bioengineering Scientists, 2021
In the Rationalist model, rationality is paramount. The individual’s choice has to reflect his real rational interests, regardless of his impulse. If his impulse leads him in another direction, he is being deceived by himself or others, his freedom is an illusion. Paternalism may thus be justified. The forces compelling an individual to make an irrational choice may come from the person’s personal or family or societal background. Karl Marx points out that society may promulgate deceptions useful to the ruling class, and thus the person may not have a true disinterested choice. A patient refusing a life-saving medical procedure would be viewed as being deceived and would be overruled. The rational viewpoint is characteristic of European ethical tradition and was espoused by Kant and Rousseau who, it may be recalled, also espoused non-consequential moral theories, and by Karl Marx.
Shingo Model: Continuous Improvement Principles
Published in Rick L. Edgeman, Complex Management Systems and the Shingo Model, 2019
Critical thinking is the ability to think clearly and rationally about what to do or not do, or what to believe or disbelieve. This involves the ability to engage in reflective and independent thinking, and hence to successfully accomplish the following: Understand logical connections between ideas;Identify, form, and assess arguments;Detect common mistakes and inconsistencies in reasoning;Systematically solve problems;Identify the relevance and importance of ideas; andScrutinize and reflect on the justification of one’s own beliefs and values.
The Rational Diagnostician
Published in Pat Croskerry, Karen S. Cosby, Mark L. Graber, Hardeep Singh, Diagnosis, 2017
Rationality is defined as “the quality or state of being reasonable, based on facts or reason” and implies conformity of one’s beliefs with one’s reasons to believe, or of one’s actions with one’s reasons for action. “Rationality” has different specialized meanings in economics, sociology, psychology, evolutionary biology, and political science [11]. In medicine, Hippocrates was responsible for the early transition away from the divine toward “rational” decision making, and over the ensuing two millennia, we have gradually moved closer toward a secular understanding of what it is to make rational medical decisions. But the understanding of “medical rationality” varies considerably within medicine, and many researchers and educators still have differing views of the concept.
The Doubly-Bounded Rationality of an Artificial Agent and its Ability to Represent the Bounded Rationality of a Human Decision-Maker in Policy-Relevant Situations
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2020
In the context of decision-making, rationality is the quality of deciding logically in a decision situation, in the sense of making decisions that are in accordance with one’s goal(s) in that situation; where a decision situation is a time-sensitive decision-specific context within which a decision-maker wants/needs to decide (on their own or in coordination with others). A decision-maker’s ability to make rational decisions in a situation relies on their ability to acquire, store, organise, learn from, and decide based on knowledge relevant to that situation. This ability is made possible by what Lake, Ullman, Tenenbaum, and Gershman (2017) referred to as the core set of ingredients for human intelligence, which from childhood is rooted in intuitive physics and psychology and includes the ability to compose, establish causality, learn to learn, approximate inference, and reinforce learning. Such or some other set of ingredients allows humans to re-engineer prior experience and apply it within an open and novel world (Chater, 2018).
Effects of user cognitive biases on platform competition
Published in Journal of Decision Systems, 2019
Evangelos Katsamakas, Heba Madany
Cognitive bias is a systematic tendency to deviate from the norms of rationality in judgment by relying on heuristics in making decisions (Tversky & Kahneman, 1974). There is a large body of research exploring how cognitive bias affects individual decision-making (Kahneman, 2011). Cognitive biases have been studied in a variety of domains such as finance and sports (Thaler, 2018), consumer decision-making (Stango, Yoong, & Zinman, 2017) and industrial organisation (Stone and Wood 2018). The significance of cognitive biases is also highlighted by the fact that Kahneman and Thaler were awarded the Nobel Prize in Economic Sciences in 2002 and 2017 respectively. In business contexts, consumers and managers may suffer from cognitive biases. Entrepreneurship studies show that overconfidence bias, confirmation bias and hindsight bias are the most common biases entrepreneurs tend to fall into (Busenitz & Barney, 1997). In his latest book, Thaler (2015) notes that education, development economics and finance are the fields most impacted by behavioural economics. He also calls for the development of ‘evidence-based theory’, which is a key motivation of this article.
Analytics, bias, and evidence: the quest for rational decision making
Published in Journal of Decision Systems, 2019
Daniel J. Power, Dale Cyphert, Roberta M. Roth
First, since the traditional understanding of reason and rationality might no longer represent an appropriate or exclusive goal for decision making behavior, we might redefine good decision making to focus on concrete results rather than idealistic prescriptions of how rational thinking ought or should look to an observer. Data Scientists and decision support builders should try to reinforce the intended rationality of the targeted user and must also work to avoid introducing ‘irrationality’ into the analysis and decision process. Technologists may rarely dwell in the depths of the philosophical foundations of decision support, analytics and decision making, but any presumptions we make about the rationality of decision makers affects the degree to which people will be assisted by our data, tools and reports. Decision support designers might focus on imitating decision-making processes that yield a desired result rather than presupposing that a specific process will yield effective decision making. Even within this limited scope, there are caveats. Choosing a goal necessarily involves making a decision, and a decision support builder must carefully define a specific system’s scope and purpose. Further, effectiveness itself must be contextually understood.