Suchergebnisse

Intro -- Contents -- List of Figures -- List of Tables -- 1 Introduction -- 2 Is Reasoning Useful? -- 2.1 Outreach Publications -- 2.1.1 Trends in Cognitive Sciences -- 2.1.2 Psychological Science in the Public Interest -- 2.2 Policymaking -- 2.2.1 The Credibility Problem -- 2.2.2 Behaviorally Informed Policies -- 2.3 Making Reasoning Relevant -- 2.3.1 A New Language -- 2.3.2 A New Toolbox -- References -- 3 What Is Special About Human Reasoning? -- 3.1 Protoreasoning Among Nonhuman Primates -- 3.1.1 Causality -- 3.1.2 Logic -- 3.1.3 Comparative Ontogeny -- 3.2 Our Uniquely Cooperative Mind -- 3.2.1 Coordination -- 3.2.2 Division of Labor -- 3.2.3 Cumulative Culture -- 3.3 Our Special Powers of Reasoning -- 3.3.1 More Than Social Context -- 3.3.2 More Than (One) Social Function -- References -- 4 Decisions -- 4.1 The Rationality Assumption -- 4.2 Rational Doers -- 4.2.1 The Naïve Utility Calculus Model -- 4.2.2 Reasoning About What People Do -- 4.3 Rational Talkers -- 4.3.1 The Rational Speech Act Model -- 4.3.2 Reasoning About What People Say -- 4.4 Do We Intuit Utility Maximization? -- 4.4.1 Intuitions About Doers -- 4.4.2 Intuitions About Talkers -- References -- 5 Morality -- 5.1 Moral Character and Its Components -- 5.2 Other-Regarding Preferences -- 5.2.1 Inferences from Behavior -- 5.2.2 Inferences from Processing -- 5.3 Doing Culture Right -- 5.3.1 The Impure and the Bizarre -- 5.3.2 From Conformity to Morality -- References -- 6 Delusions -- 6.1 Motivated Beliefs -- 6.1.1 Feeling and Doing Better -- 6.1.2 Cooperation-Motivated Beliefs -- 6.2 Self-Deluded Reasoning -- 6.2.1 Biased Evaluations -- 6.2.2 Conjuring Premises -- 6.3 Reasoning About Delusions -- 6.3.1 How Hard Should It Be to Detect Self-Deceivers? -- 6.3.2 What Counts as Detecting Self-Deceivers? -- References -- 7 Democracy -- 7.1 Reasoning About Issues

Moral Inferences" draws on the expertise of world-leading researchers to provide a ground-breaking exploration of reasoning and morality. Historically, these two areas of research have largely been conducted in isolation, which has resulted in a lack of integration between the latest morality research and current theories in reasoning, despite the prominent role reasoning plays in morality. This volume will explore the relationship between the two, emphasising the importance of synthesising work from both morality and reasoning researchers in order to see the bigger picture. It will appeal to researchers from both fields, acting as a springboard for future research

Abstract
Artificial intelligence (AI) can be harnessed to create sophisticated social and moral scoring systems—enabling people and organizations to form judgments of others at scale. However, it also poses significant ethical challenges and is, subsequently, the subject of wide debate. As these technologies are developed and governing bodies face regulatory decisions, it is crucial that we understand the attraction or resistance that people have for AI moral scoring. Across four experiments, we show that the acceptability of moral scoring by AI is related to expectations about the quality of those scores, but that expectations about quality are compromised by people's tendency to see themselves as morally peculiar. We demonstrate that people overestimate the peculiarity of their moral profile, believe that AI will neglect this peculiarity, and resist for this reason the introduction of moral scoring by AI.

PurposeThe purpose of this paper is to show how overall performance can help foster trust in financial institutions. While a climate of mistrust amongst investors and the general public toward financial institutions has developed since the recent turmoil in the financial markets, it is believed that mutual funds adopting the overall performance approach can help recover a climate of trust owing to the implied balance between economic, social and environmental performance. More specifically, overall performance promotes values that are similar to investors' values and could be used by responsible investment funds if they want to contribute to the restoration of trust in investment funds.Design/methodology/approachThis paper uses an innovative, experimental design to test the effect of value similarity on the trust that investors have in the investment fund. This effect cannot be studied in isolation, which is why it is compared with the effects of financial performance and ethical labeling on trust.FindingsThe authors find that funds with similar values are perceived as more trustworthy by investors. Consequently, overall performance should be added to fund managers' toolbox if they want to foster trust in their fund. The effect of financial performance on trust applies only when the investor has no other information regarding the fund. As for the ethical labeling of funds, it has no effect on trust.Research limitations/implicationsThe findings encourage research that aims to develop a comprehensive approach of integrated overall performance focusing on financial and extra-financial values. Bonnetet al.'s (2016) fieldwork on socio-economic management and Naro and Travaillé©'s (2016) work on management controllers provide promising examples in this regard.Practical implicationsInvestment funds can acquire an edge by communicating on overall performance and specific values of their target investors. Merely labeling funds as ethical is not sufficient to increase trust.Social implicationsIncreasing similarity in values to investors and adopting the overall performance approach in investment funds will increase investors' trust. Trust contributes to social capital and allows societies to create flexible large-scale businesses needed to be competitive in a global environment.Originality/valueUsing an innovative experimental methodology, this paper shows that the underlying factor of overall performance on trust in investment funds is value similarity. It provides researchers and practitioners with insight about the underlying mechanisms of the effect of overall performance on trust.

Abstract
The algorithms that control AVs will need to embed moral principles guiding their decisions in situations of unavoidable harm. Manufacturers and regulators are confronted with three potentially incompatible objectives: being consistent, not causing public outrage, and not discouraging buyers. The presented moral machine study is a step towards solving this problem as it tries to learn how people all over the world feel about the alternative decisions the AI of self-driving vehicles might have to make. The global study displayed broad agreement across regions regarding how to handle unavoidable accidents. To master the moral challenges, all stakeholders should embrace the topic of machine ethics: this is a unique opportunity to decide as a community what we believe to be right or wrong, and to make sure that machines, unlike humans, unerringly follow the agreed-upon moral preferences. The integration of autonomous cars will require a new social contract that provides clear guidelines about who is responsible for different kinds of accidents, how monitoring and enforcement will be performed, and how trust among all stakeholders can be engendered.

On the Web, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.). Different mechanisms have been implemented to capture these opinions such as Like in Facebook, Favorite in Twitter, thumbs-up/-down, flagging, and so on. However, in more contested domains (e.g., Wikipedia, political discussion, and climate change discussion), these mechanisms are not sufficient, since they only deal with each issue independently without considering the relationships between different claims. We can view a set of conflicting arguments as a graph in which the nodes represent arguments and the arcs between these nodes represent the defeat relation. A group of people can then collectively evaluate such graphs. To do this, the group must use a rule to aggregate their individual opinions about the entire argument graph. Here we present the first experimental evaluation of different principles commonly employed by aggregation rules presented in the literature. We use randomized controlled experiments to investigate which principles people consider better at aggregating opinions under different conditions. Our analysis reveals a number of factors, not captured by traditional formal models, that play an important role in determining the efficacy of aggregation. These results help bring formal models of argumentation closer to real-world application.

National audience ; How does the public want a COVID-19 vaccine to be allocated? We conducted a conjoint experiment asking 15,536 adults in 13 countries to evaluate 248,576 profiles of potential vaccine recipients that varied randomly on five attributes. Our sample includes diverse countries from all continents. The results suggest that in addition to giving priority to health workers and to those at high risk, the public favours giving priority to a broad range of key workers and to those on lower incomes. These preferences are similar across respondents of different education levels, incomes, and political ideologies, as well as across most surveyed countries. The public favoured COVID-19 vaccines being allocated solely via government programs, but were highly polarized in some developed countries on whether taking a vaccine should be mandatory. There is a consensus among the public on many aspects of COVID-19 vaccination which needs to be taken into account when developing and communicating roll-out strategies.

National audience ; How does the public want a COVID-19 vaccine to be allocated? We conducted a conjoint experiment asking 15,536 adults in 13 countries to evaluate 248,576 profiles of potential vaccine recipients that varied randomly on five attributes. Our sample includes diverse countries from all continents. The results suggest that in addition to giving priority to health workers and to those at high risk, the public favours giving priority to a broad range of key workers and to those on lower incomes. These preferences are similar across respondents of different education levels, incomes, and political ideologies, as well as across most surveyed countries. The public favoured COVID-19 vaccines being allocated solely via government programs, but were highly polarized in some developed countries on whether taking a vaccine should be mandatory. There is a consensus among the public on many aspects of COVID-19 vaccination which needs to be taken into account when developing and communicating roll-out strategies.