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Blaming Automated Vehicles in Difficult Situations
2021
iScience
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Awad, and David Lagnado
Supplemental Data Items
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ll
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8
iScience 24, 102252, April 23, 2021
iScience
Article
iScience, Volume 24
Supplemental information
Blaming automated vehicles in difficult situations
Matija Franklin, Edmond ...
doi:10.1016/j.isci.2021.102252
pmid:33796841
pmcid:PMC7995526
fatcat:7h37l2i3qrcwxbkqkjbnawghdy
Blaming Automated Vehicles in Difficult Situations
2020
Social Science Research Network
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Awad, and David Lagnado
Supplemental Data Items
b. ...
ll
OPEN ACCESS
8
iScience 24, 102252, April 23, 2021
iScience
Article
iScience, Volume 24
Supplemental information
Blaming automated vehicles in difficult situations
Matija Franklin, Edmond ...
doi:10.2139/ssrn.3701256
fatcat:54fpuu6xj5autitejyce5jkpv4
Crowdsourcing moral machines
2020
Communications of the ACM
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A Computational Model of Commonsense Moral Decision Making
[article]
2018
arXiv
pre-print
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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
arXiv:1801.04346v1
fatcat:lkakszmxwvejbeptk2m3kxylc4
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... scription 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.
The Moral Machine experiment
2018
Nature
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With the rapid development of artificial intelligence have come concerns about how machines will make moral decisions, and the major challenge of quantifying societal expectations about the ethical principles that should guide machine behaviour. To address this challenge, we deployed the Moral Machine, an online experimental platform designed to explore the moral dilemmas faced by autonomous vehicles. This platform gathered 40 million decisions in ten languages from millions of people in 233
doi:10.1038/s41586-018-0637-6
pmid:30356211
fatcat:i7di65ycrvhibkt5ka3mkot7ue
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... ntries and territories. Here we describe the results of this experiment. First, we summarize global moral preferences. Second, we document individual variations in preferences, based on respondents' demographics. Third, we report cross-cultural ethical variation, and uncover three major clusters of countries. Fourth, we show that these differences correlate with modern institutions and deep cultural traits. We discuss how these preferences can contribute to developing global, socially acceptable principles for machine ethics. All data used in this article are publicly available.
Algorithmic and human prediction of success in human collaboration from visual features
2021
Scientific Reports
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AbstractAs groups are increasingly taking over individual experts in many tasks, it is ever more important to understand the determinants of group success. In this paper, we study the patterns of group success in Escape The Room, a physical adventure game in which a group is tasked with escaping a maze by collectively solving a series of puzzles. We investigate (1) the characteristics of successful groups, and (2) how accurately humans and machines can spot them from a group photo. The
doi:10.1038/s41598-021-81145-3
pmid:33531514
pmcid:PMC7854594
fatcat:zubozpq5njd7rn3x57na4r72oy
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... hip between these two questions is based on the hypothesis that the characteristics of successful groups are encoded by features that can be spotted in their photo. We analyze >43K group photos (one photo per group) taken after groups have completed the game—from which all explicit performance-signaling information has been removed. First, we find that groups that are larger, older and more gender but less age diverse are significantly more likely to escape. Second, we compare humans and off-the-shelf machine learning algorithms at predicting whether a group escaped or not based on the completion photo. We find that individual guesses by humans achieve 58.3% accuracy, better than random, but worse than machines which display 71.6% accuracy. When humans are trained to guess by observing only four labeled photos, their accuracy increases to 64%. However, training humans on more labeled examples (eight or twelve) leads to a slight, but statistically insignificant improvement in accuracy (67.4%). Humans in the best training condition perform on par with two, but worse than three out of the five machine learning algorithms we evaluated. Our work illustrates the potentials and the limitations of machine learning systems in evaluating group performance and identifying success factors based on sparse visual cues.
MOESM1 of Misery loves company: happiness and communication in the city
2017
Figshare
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Supporting information.
doi:10.6084/m9.figshare.c.3698755_d1
fatcat:v4vfl4zi3fgurb5axy2orby32e
A Voting-Based System for Ethical Decision Making
[article]
2018
arXiv
pre-print
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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
arXiv:1709.06692v2
fatcat:ztq5nkarcrcgfctcfla4weoomy
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... lement 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.
Misery loves company: happiness and communication in the city
2015
EPJ Data Science
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The high population density in cities confers many advantages, including improved social interaction and information exchange. However, it is often argued that urban living comes at the expense of reducing happiness. The goal of this research is to shed light on the relationship between urban communication and urban happiness. We analyze geo-located social media posts (tweets) within a major urban center (Milan) to produce a detailed spatial map of urban sentiments. We combine this data with
doi:10.1140/epjds/s13688-015-0044-2
fatcat:my6u2s5ehja5xfwhbeadf3h2m4
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... h-resolution mobile communication intensity data among different urban areas. Our results reveal that happy (respectively unhappy) areas preferentially communicate with other areas of their type. This observation constitutes evidence of homophilous communities at the scale of an entire city (Milan), and has implications on interventions that aim to improve urban well-being.
The Thorny Challenge of Making Moral Machines: Ethical Dilemmas with Self-Driving Cars
2019
NIM Marketing Intelligence Review
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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
doi:10.2478/nimmir-2019-0015
fatcat:jqn5dimnevf5bp5q25vlcgsor4
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... 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.
When Is It Acceptable to Break the Rules? Knowledge Representation of Moral Judgement Based on Empirical Data
[article]
2022
arXiv
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., a runaway trolley headed towards innocents (Awad et al., 2018) , and we rather probe people's moral intuitions in a very common everyday scenarios: standing in line to receive a service. ...
arXiv:2201.07763v1
fatcat:rkbo22mxtfa4pnadndbrmtfoey
Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation
[article]
2018
arXiv
pre-print
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Awad, Levine et al.Figure 13: Vignette for Human-Machine with Bad Intervention.
Figure 14: Vignette for Machine-Human with Missed Intervention. ...
arXiv:1803.07170v2
fatcat:fkqkz77w7nhnjdhczc5dqghmcy
Judgement aggregation in multi-agent argumentation
2015
Journal of Logic and Computation
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Much of this article was written during a visit of Edmond Awad to the University of Luxembourg which was generously supported by SINTELNET. ...
doi:10.1093/logcom/exv055
fatcat:kcbg7s5joncr5bwcp3wkrngfli
The Role of Heparanase in the Pathogenesis of Acute Pancreatitis: A Potential Therapeutic Target
2017
Scientific Reports
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Acute pancreatitis (AP) is one of the most common diseases in gastroenterology. However, neither the etiology nor the pathophysiology of the disease is fully understood and no specific or effective treatment has been developed. Heparanase is an endoglycosidase that cleaves heparan sulfate (HS) side chains of HS sulfate proteoglycans into shorter oligosaccharides, activity that is highly implicated in cellular invasion associated with cancer metastasis and inflammation. Given that AP involves a
doi:10.1038/s41598-017-00715-6
pmid:28386074
pmcid:PMC5429646
fatcat:ian674dri5a4lfvmbdgh3x7d7i
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... trong inflammatory aspect, we examined whether heparanase plays a role in AP. Here, we provide evidence that pancreatic heparanase expression and activity are significantly increased following cerulein treatment. Moreover, pancreas edema and inflammation, as well as the induction of cytokines and signaling molecules following cerulein treatment were attenuated markedly by heparanase inhibitors, implying that heparanase plays a significant role in AP. Notably, all the above features appear even more pronounced in transgenic mice over expressing heparanase, suggesting that these mice can be utilized as a sensitive model system to reveal the molecular mechanism by which heparanase functions in AP. Heparanase, therefore, emerges as a potential new target in AP, and heparanase inhibitors, now in phase I/II clinical trials in cancer patients, are hoped to prove beneficial also in AP. Published: xx xx xxxx OPEN www.nature.com/scientificreports/ 2 Scientific RepoRts | 7: 715 |
sj-pdf-1-mpp-10.1177_23814683221113573 – Supplemental material for Polarized Citizen Preferences for the Ethical Allocation of Scarce Medical Resources in 20 Countries
2022
Figshare
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Supplemental material, sj-pdf-1-mpp-10.1177_23814683221113573 for Polarized Citizen Preferences for the Ethical Allocation of Scarce Medical Resources in 20 Countries by Edmond Awad, Bence Bago, Jean-François ...
doi:10.25384/sage.20372384.v1
fatcat:eog3d5pebncnxprvzoalwjeifi
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