18,870 research outputs found

    On the rationality of decision aiding processes

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    Does modularity undermine the pro‐emotion consensus?

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    There is a growing consensus that emotions contribute positively to human practical rationality. While arguments that defend this position often appeal to the modularity of emotion-generation mechanisms, these arguments are also susceptible to the criticism, e.g. by Jones (2006), that emotional modularity supports pessimism about the prospects of emotions contributing positively to practical rationality here and now. This paper aims to respond to this criticism by demonstrating how models of emotion processing can accommodate the sorts of cognitive influence required to make the pro-emotion position plausible whilst exhibiting key elements of modularity

    Current Concepts and Trends in Human-Automation Interaction

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    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugÀnglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The purpose of this panel was to provide a general overview and discussion of some of the most current and controversial concepts and trends in human-automation interaction. The panel was composed of eight researchers and practitioners. The panelists are well-known experts in the area and offered differing views on a variety of different human-automation topics. The range of concepts and trends discussed in this panel include: general taxonomies regarding stages and levels of automation and function allocation, individualized adaptive automation, automation-induced complacency, economic rationality and the use of automation, the potential utility of false alarms, the influence of different types of false alarms on trust and reliance, and a system-wide theory of trust in multiple automated aids

    Similarity and the trustworthiness of distributive judgements

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    When people must either save a greater number of people from a smaller harm or a smaller number from a greater harm, do their choices reflect a reasonable moral outlook? We pursue this question with the help of an experiment. In our experiment, two-fifths of subjects employ a similarity heuristic. When alternatives appear dissimilar in terms of the number saved but similar in terms of the magnitude of harm prevented, this heuristic mandates saving the greater number. In our experiment, this leads to choices that are inconsistent with all standard theories of justice. We argue that this demonstrates the untrustworthiness of distributive judgments in cases that elicit similarity-based choice

    Reasons and Means to Model Preferences as Incomplete

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    Literature involving preferences of artificial agents or human beings often assume their preferences can be represented using a complete transitive binary relation. Much has been written however on different models of preferences. We review some of the reasons that have been put forward to justify more complex modeling, and review some of the techniques that have been proposed to obtain models of such preferences

    Borgs in the Org? Organizational Decision Making and Technology

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    Data warehousing and the development of the World Wide Web both augment information gathering (search) processes in individual decision making by increasing the availability of required information. Imagine, for example, that one wanted to buy new golf clubs. Thirty years ago, the cost of information gathering would likely have limited an individual\u27s search process to geographically proximal vendors and the golf clubs they stocked. Today, a prospective purchaser can log onto the World Wide Web to find out what types of golf clubs are available anywhere; consult databases, chat rooms, and bulletin boards (e.g., epinions.com) to gather product information and user opinions; and compare prices across vendors around the world

    A review of cost–benefit analysis and multicriteria decision analysis from the perspective of sustainable transport in project evaluation

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    Transport decision processes have traditionally applied cost-benefit analysis (CBA) with benefits mainly relating to time savings, and costs relating to infrastructure and maintenance costs. However, a shift toward more sustainable practices was initiated over the last decades to remedy the many negative impacts of automobility. As a result, decision processes related to transport projects have become more complex due to the multidimensional aspects and to the variety of stakeholders involved, often with conflicting points of view. To support rigorous decision making, multicriteria decision analysis (MCDA) is, in addition to CBA, often used by governments and cities. However, there is still no consensus in the transport field regarding a preferred method that can integrate sustainability principles. This paper presents a descriptive literature review related to MCDA and CBA in the field of transport. Among the 66 considered papers, we identified the perceived strengths and weaknesses of CBA and MCDA, the different ways to combine them and the ability of each method to support sustainable transport decision processes. We further analysed the results based on four types of rationality (objectivist, conformist, adjustive and reflexive). Our results show that both methods can help improve the decision processes and that, depending on the rationality adopted, the perceived strengths and weaknesses of MCDA and CBA can vary. Nonetheless, we observe that by adopting a more global and holistic perspective and by facilitating the inclusion of a participative process, MCDA, or a combination of both methods, emerge as the more promising appraisal methods for sustainable transport

    Robustness - a challenge also for the 21st century: A review of robustness phenomena in technical, biological and social systems as well as robust approaches in engineering, computer science, operations research and decision aiding

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    Notions on robustness exist in many facets. They come from different disciplines and reflect different worldviews. Consequently, they contradict each other very often, which makes the term less applicable in a general context. Robustness approaches are often limited to specific problems for which they have been developed. This means, notions and definitions might reveal to be wrong if put into another domain of validity, i.e. context. A definition might be correct in a specific context but need not hold in another. Therefore, in order to be able to speak of robustness we need to specify the domain of validity, i.e. system, property and uncertainty of interest. As proofed by Ho et al. in an optimization context with finite and discrete domains, without prior knowledge about the problem there exists no solution what so ever which is more robust than any other. Similar to the results of the No Free Lunch Theorems of Optimization (NLFTs) we have to exploit the problem structure in order to make a solution more robust. This optimization problem is directly linked to a robustness/fragility tradeoff which has been observed in many contexts, e.g. 'robust, yet fragile' property of HOT (Highly Optimized Tolerance) systems. Another issue is that robustness is tightly bounded to other phenomena like complexity for which themselves exist no clear definition or theoretical framework. Consequently, this review rather tries to find common aspects within many different approaches and phenomena than to build a general theorem for robustness, which anyhow might not exist because complex phenomena often need to be described from a pluralistic view to address as many aspects of a phenomenon as possible. First, many different robustness problems have been reviewed from many different disciplines. Second, different common aspects will be discussed, in particular the relationship of functional and structural properties. This paper argues that robustness phenomena are also a challenge for the 21st century. It is a useful quality of a model or system in terms of the 'maintenance of some desired system characteristics despite fluctuations in the behaviour of its component parts or its environment' (s. [Carlson and Doyle, 2002], p. 2). We define robustness phenomena as solution with balanced tradeoffs and robust design principles and robustness measures as means to balance tradeoffs. --

    Using a group decision support system to make investment prioritisation decisions

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