104,429 research outputs found

    Scientific Models of Human Health Risk Analysis in Legal and Policy Decisions

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    The quality of scientific predictions of risk in the courtroom and policy arena rests in large measure on how the two differences between normal practice and the legal/policy practice of science are reconciled. This article considers a variety of issues that arise in reconciling these differences, and the problems that remain with scientific estimates of risk when these are used in decisions

    A Metacognitive Approach to Trust and a Case Study: Artificial Agency

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    Trust is defined as a belief of a human H (‘the trustor’) about the ability of an agent A (the ‘trustee’) to perform future action(s). We adopt here dispositionalism and internalism about trust: H trusts A iff A has some internal dispositions as competences. The dispositional competences of A are high-level metacognitive requirements, in the line of a naturalized virtue epistemology. (Sosa, Carter) We advance a Bayesian model of two (i) confidence in the decision and (ii) model uncertainty. To trust A, H demands A to be self-assertive about confidence and able to self-correct its own models. In the Bayesian approach trust can be applied not only to humans, but to artificial agents (e.g. Machine Learning algorithms). We explain the advantage the metacognitive trust when compared to mainstream approaches and how it relates to virtue epistemology. The metacognitive ethics of trust is swiftly discussed

    An Enactive-Ecological Approach to Information and Uncertainty

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    Information is a central notion for cognitive sciences and neurosciences, but there is no agreement on what it means for a cognitive system to acquire information about its surroundings. In this paper, we approximate three influential views on information: the one at play in ecological psychology, which is sometimes called information for action; the notion of information as covariance as developed by some enactivists, and the idea of information as minimization of uncertainty as presented by Shannon. Our main thesis is that information for action can be construed as covariant information, and that learning to perceive covariant information is a matter of minimizing uncertainty through skilled performance. We argue that the agent’s cognitive system conveys information for acting in an environment by minimizing uncertainty about how to achieve her intended goals in that environment. We conclude by reviewing empirical findings that support our view and by showing how direct learning, seen as instance of ecological rationality at work, is how mere possibilities for action are turned into embodied know-how. Finally, we indicate the affinity between direct learning and sense-making activity

    The issue of design in managerial decision making

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    It is argued that the design of decisions is a process that in many ways is shaped by social factors such as identities, values, and influences. To be able to understand how these factors impact organizational decisions, the focus must be set on the management level. It is the management that shoulders the chief responsibility for designing collective actions, such as decisions. Our propositions indicate that the following measures must be taken in order to improve the quality of organizational decisions: 1. The identity of the people, involved in organizational decision making, affects the quality of decisions and should be taken into account in the design of decisions. 2. The decision maker or designer of decisions should engage the members of an organization to create a shared vision. 3. Getting the members of an organization to express and share common values should improve the decision making process. 4. Being able to socially influence the members of an organization, or other stakeholders involved, as well as letting them participate in the process, should improve the quality of decisions

    Barriers to industrial energy efficiency: a literature review

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