21 research outputs found

    A Voting-Based System for Ethical Decision Making

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    We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice. In a nutshell, we propose to learn a model of societal preferences, and, when faced with a specific ethical dilemma at runtime, efficiently aggregate those preferences to identify a desirable choice. We provide a concrete algorithm that instantiates our approach; some of its crucial steps are informed by a new theory of swap-dominance efficient voting rules. Finally, we implement and evaluate a system for ethical decision making in the autonomous vehicle domain, using preference data collected from 1.3 million people through the Moral Machine website.Comment: 25 pages; paper has been reorganized, related work and discussion sections have been expande

    A Computational Model of Commonsense Moral Decision Making

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    We introduce a new computational model of moral decision making, drawing on a recent theory of commonsense moral learning via social dynamics. Our model describes moral dilemmas as a utility function that computes trade-offs in values over abstract moral dimensions, which provide interpretable parameter values when implemented in machine-led ethical decision-making. Moreover, characterizing the social structures of individuals and groups as a hierarchical Bayesian model, we show that a useful description of an individual's moral values - as well as a group's shared values - can be inferred from a limited amount of observed data. Finally, we apply and evaluate our approach to data from the Moral Machine, a web application that collects human judgments on moral dilemmas involving autonomous vehicles

    Crowdsourcing moral psychology

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    Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February, 2021Cataloged from the official PDF version of thesis.Includes bibliographical references (pages 57-58).Ethical trade-off surveys have played a key role in building a data-driven understanding of human moral psychology. They have been conducted all over the world for decades, eliciting assessment of ethical dilemma outcomes from populations as diverse as those of rural, tribal settlements, and industrialized, information-age, cosmopolitan cities. While much data has been gathered through these surveys, attempts to compare what people across cultures consider ethically justifiable have been hindered by the fact that the surveys used have been reformulated for different cultures in the scenarios they depict, and in their framing. The objective of this thesis project is to build a survey tool with global reach and internationalized surveys, in order to collect survey data from around the world using consistent scenarios and framing. Building on the precedent and success of the Moral Machine tool for surveying people around the world regarding ethical dilemmas involving autonomous vehicles, I built and deployed a tool for conducting surveys with scenarios of the classic action/omission trolley problem, to collect ethical dilemma survey data internationally, in ten languages, for three variants of the trolley problem - one for remote action/omission with no double effect consideration, one for double effect consideration with direct action/omission, and one for double effect consideration with remote action/omission. Analyzing data from this experiment, I conclude that differences in preferences across the variants are confirmed across populations, and that they are universal across populations in order of preference.by Sohan Savio Dsouza.S.M.S.M. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Science

    Universals and variations in moral decisions made in 42 countries by 70,000 participants

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    International audienceWhen do people find it acceptable to sacrifice one life to save many? Cross-cultural studies suggested a complex pattern of universals and variations in the way people approach this question, but data were often based on small samples from a small number of countries outside of the Western world. Here we analyze responses to three sacrificial dilemmas by 70,000 participants in 10 languages and 42 countries. In every country, the three dilemmas displayed the same qualitative ordering of sacrifice acceptability, suggesting that this ordering is best explained by basic cognitive processes rather than cultural norms. The quantitative acceptability of each sacrifice, however, showed substantial country-level variations. We show that low relational mobility (where people are more cautious about not alienating their current social partners) is strongly associated with the rejection of sacrifices for the greater good (especially for Eastern countries), which may be explained by the signaling value of this rejection. We make our dataset fully available as a public resource for researchers studying universals and variations in human morality

    Crowdsourcing moral machines

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    International audienceA platform for creating a crowdsourced picture of human opinions on how machines should handle moral dilemmas


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    We present a novel approach to developing a vehicle communication platform consisting of a low-cost, open-source hardware for moving vehicle data to a secure server, a Web Application Programming Interface (API) for the provision of third-party services, and an intuitive user dashboard for access control and service distribution. The CloudThink infrastructure promotes the commoditization of vehicle telematics data by facilitating easier, flexible, and more secure access. It enables drivers to confidently share their vehicle information across multiple applications to improve the transportation experience for all stakeholders, as well as to potentially monetize their data. The foundations for an application ecosystem have been developed which, taken together with the fair value for driving data and low barriers to entry, will drive adoption of CloudThink as the standard method for projecting physical vehicles into the cloud. The application space initially consists of a few fundamental and important applications (vehicle tethering and remote diagnostics, road-safety monitoring, and fuel economy analysis) but as CloudThink begins to gain widespread adoption, the multiplexing of applications on the same data structure and set will accelerate its adoption. Keyword: cloud theory; eSafety; information system; intelligent transport system; data securit