From Trolley to Autonomous Vehicle: Perceptions of Responsibility and Moral Norms in Traffic Accidents with Self-Driving Cars

Li, Jamy; Zhao, Xuan; Cho, Mu Jung; Ju, Wendy; Malle, Bertram F.

doi:10.4271/2016-01-0164

Cited by 68 publications

(64 citation statements)

References 20 publications

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“…Participants had to judge the decision of either a human driver in a dilemma situation, or an autonomous car deciding on its own. In contrast to human drivers, where utilitarian decisions were most favorable, participants expected ADVs to behave in a utilitarian manner under all circumstances (Li, Zhao, Cho, Ju, & Malle, 2016;Malle et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles

et al. 2018

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Ethical thought experiments such as the trolley dilemma have been investigated extensively in the past, showing that humans act in utilitarian ways, trying to cause as little overall damage as possible. These trolley dilemmas have gained renewed attention over the past few years, especially due to the necessity of implementing moral decisions in autonomous driving vehicles (ADVs). We conducted a set of experiments in which participants experienced modified trolley dilemmas as drivers in virtual reality environments. Participants had to make decisions between driving in one of two lanes where different obstacles came into view. Eventually, the participants had to decide which of the objects they would crash into. Obstacles included a variety of human-like avatars of different ages and group sizes. Furthermore, the influence of sidewalks as potential safe harbors and a condition implicating self-sacrifice were tested. Results showed that participants, in general, decided in a utilitarian manner, sparing the highest number of avatars possible with a limited influence by the other variables. Derived from these findings, which are in line with the utilitarian approach in moral decision making, it will be argued for an obligatory ethics setting implemented in ADVs.

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Section: Discussionmentioning

confidence: 99%

Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles

et al. 2018

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“…Rather than offering an immersive experience, the goal of using simplified animations was to illustrate the scenarios while prompting participants to evaluate them from a particular perspective. We consider the use of animations to be a natural extension of the combination of simplified images and textual vignettes, as used in previous studies (Bonnefon et al, 2016;Li et al, 2016;Awad et al, 2018). As such a combination has been shown by Sachdeva et al (2015) to sufficiently manipulate perspective in moral dilemmas, simplified animations should similarly prompt participants to consider situations from the presented perspective.…”

Section: Study 2-moral Judgements On Simplified Animationsmentioning

confidence: 99%

“…An analysis of more than 40 million judgements on vignettes describing hypothetical dilemma situations concluded that people generally prefer self-driving cars to endanger fewer lives, endanger animals over people and endanger older people over younger people (Awad et al, 2018). Other moral judgement studies include simulation studies by Wintersberger et al (2017) and Wilson et al (2019) and vignette-based studies by Bonnefon et al (2016), Li et al (2016), Meder et al (2018, Smith (2019), and Rhim et al (2020). Importantly, Bonnefon et al (2016) found a discrepancy between what people deemed acceptable for selfdriving cars to do in dilemma situations and their willingness to purchase cars that would act accordingly.…”

Section: Introductionmentioning

confidence: 99%

Moral Judgements on the Actions of Self-driving Cars and Human Drivers in Dilemma Situations from Different Perspectives

Kallioinen¹,

Pershina²,

Zeiser³

et al. 2019

Preprint

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Self-driving cars have the potential to greatly improve public safety. However, their introduction onto public roads must overcome both ethical and technical challenges. To further understand the ethical issues of introducing self-driving cars, we conducted two moral judgement studies investigating potential differences in the moral norms applied to human drivers and self-driving cars. In the experiments, participants made judgements on a series of dilemma situations involving human drivers or self-driving cars. We manipulated which perspective situations were presented from in order to ascertain the effect of perspective on moral judgements. Two main findings were apparent from the results of the experiments. First, human drivers and self-driving cars were largely judged similarly. However, there was a stronger tendency to prefer self-driving cars to act in ways to minimize harm, compared to human drivers. Second, there was an indication that perspective influences judgements in some situations. Specifically, when considering situations from the perspective of a pedestrian, people preferred actions that would endanger car occupants instead of themselves. However, they did not show such a self-preservation tendency when the alternative was to endanger other pedestrians to save themselves. This effect was more prevalent for judgements on human drivers than self-driving cars. Overall, the results extend and agree with previous research, again contradicting existing ethical guidelines for self-driving car decision making and highlighting the difficulties with adapting public opinion to decision making algorithms.

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“…We label this prediction the algorithm outrage asymmetry, and suggest it stems from people's perceptions of the mental states of those perpetrating discrimination as guiding moral judgments. Synthesizing the work emphasizing the role of perceived intentions (Alicke, 2000;Cushman, 2008;Malle et al, 2014;Malle & Knobe, 1997;Pizarro & Tannenbaum, 2011) and perceived motivation (Bigman & Tamir, 2016;Levine & Schweitzer, 2014;Reeder, Kumar, Hesson-McInnis, & Trafimow, 2002) with the work showing that people ascribe different mental states to robots (K. Gray & Wegner, 2012;Li, Zhao, Cho, Ju, & Malle, 2016;Waytz, Heafner, & Epley, 2014;Young & Monroe, 2019), we propose that as people are less likely to attribute negative motivations (i.e., prejudice) to an algorithm, they would be less outraged when algorithms discriminate.…”

mentioning

confidence: 99%

Algorithmic Discrimination Causes Less Moral Outrage than Human Discrimination

Bigman¹,

Waytz²,

Arnestad³

et al. 2020

Preprint

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The use of algorithms hold promise for overcoming human biases in decision making.Companies and governments are using algorithms to improve decision-making for hiring, medical treatments, and parole. Unfortunately, as with humans, some of these algorithms make persistently biased decisions, functionally discriminating people based on their race and gender.Media coverage suggests that people are morally outraged by algorithmic discrimination, but here we examine whether people are less outraged by algorithmic discrimination than by human discrimination. Six studies test this algorithmic outrage asymmetry hypothesis across diverse discrimination in hiring practices (sexism, ageism, racism) and across diverse participant groups (online samples, a quasi-representative sample, and a sample of tech workers). As predicted, people are less morally outraged by algorithmic discrimination. The studies further reveal that this algorithmic outrage asymmetry is driven by the reduced attribution of prejudicial motivation to machines. We also reveal a downstream consequence of algorithmic outrage asymmetrypeople are more likely to endorse racial stereotypes after algorithmic discrimination versus human discrimination. We discuss the theoretical and practical implications of these results, including the potential weakening of collective action to address systemic discrimination.

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From Trolley to Autonomous Vehicle: Perceptions of Responsibility and Moral Norms in Traffic Accidents with Self-Driving Cars

Cited by 68 publications

References 20 publications

Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles

Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles

Moral Judgements on the Actions of Self-driving Cars and Human Drivers in Dilemma Situations from Different Perspectives

Algorithmic Discrimination Causes Less Moral Outrage than Human Discrimination

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