Public Health, Ethics, and Autonomous Vehicles

Fleetwood, Janet

doi:10.2105/ajph.2016.303628

Cited by 158 publications

(79 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Manufacturers are increasingly vulnerable to reputational risks imposed by accidents associated with failures in design and manufacturing (Hevelke & Nida-Rümelin, 2015;Tien, 2017). The current legal frameworks also do not define the practical and moral responsibilities of software programmers in designing "crash algorithms" that determine life or death decisions, raising numerous concerns over AVs' implications on public ethics (Fleetwood, 2017;Pinsent Masons, 2016). Governments have yet to address whether algorithms' decision-making criteria during accidents should be standardised.…”

Section: Liabilitymentioning

confidence: 99%

Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

2018

View full text Add to dashboard Cite

The benefits of autonomous vehicles (AVs) are widely acknowledged, but there are concerns about the extent of these benefits and AV risks and unintended consequences. In this article, we first examine AVs and different categories of the technological risks associated with them. We then explore strategies that can be adopted to address these risks, and explore emerging responses by governments for addressing AV risks. Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications. The US has been active in introducing legislations to address issues related to privacy and cybersecurity. The UK and Germany, in particular, have enacted laws to address liability issues; other countries mostly acknowledge these issues, but have yet to implement specific strategies. To address privacy and cybersecurity risks strategies ranging from introduction or amendment of non-AV specific legislation to creating working groups have been adopted. Much less attention has been paid to issues such as environmental and employment risks, although a few governments have begun programmes to retrain workers who might be negatively affected. ARTICLE HISTORY

show abstract

Section: Liabilitymentioning

confidence: 99%

Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

2018

View full text Add to dashboard Cite

show abstract

“…Economic incentives of AV purchasers may also motivate manufacturers to design algorithms that discriminate between passengers of publicly-owned AVs and those of privately-owned AVs. Unlike publicly-owned AVs, private AV purchasers may expect their AVs to prioritise their safety over all others [89,92] and thus, AV manufacturers could program their algorithms according to these customer preferences to maximise profits. While doing so ensures AVs' commercial success, as it has been shown that consumers do prefer riding in AVs that prioritise passenger safety [108,109], safety risks would be transferred from users of privately-owned AVs, who benefit from their use, to individuals who cannot afford to purchase AVs.…”

Section: Perverse Incentivesmentioning

confidence: 99%

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Lim

Taeihagh

2019

Sustainability

View full text Add to dashboard Cite

Autonomous Vehicles (AVs) are increasingly embraced around the world to advance smart mobility and more broadly, smart, and sustainable cities. Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently, and more safely than human drivers and offering various economic, social, and environmental benefits. However, algorithmic decision-making in AVs can also introduce new issues that create new safety risks and perpetuate discrimination. We identify bias, ethics, and perverse incentives as key ethical issues in the AV algorithms' decision-making that can create new safety risks and discriminatory outcomes. Technical issues in the AVs' perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance of the AV system. This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public. We discuss steps taken to address these issues, highlight the existing research gaps and the need to mitigate these issues through the design of AV's algorithms and of policies and regulations to fully realise AVs' benefits for smart and sustainable cities.Sustainability 2019, 11, 5791 2 of 28 surroundings and algorithms that process the data, make, and execute driving decisions through the vehicle's actuators. The quality of data retrieved by the AV's sensors is critical for decision-making [21], and the efficiency, precision and reliability of decision-making algorithms allows AVs to surpass the typical human driver in performing driving tasks [22]. A major component in AVs is machine-learning (ML) [23] algorithms that continuously learn and adapt to new information, which is essential for responding to unexpected situations and providing on-demand transportation services [24]. Algorithms' independence from human input and ML's data-driven nature allows AVs to significantly reduce or eliminate human errors that have been responsible for 90% of road fatalities, such as speeding, alcohol impairment, distractions and induced fear [25,26].However, an overemphasis on technological solutions alone for economic development could risk neglecting social and environmental considerations and thus hinder true "smartness" [27]. Scholars have cautioned against rushing to develop smart mobility solutions such as AVs without being prepared to manage their potential "negative externalities" [1,28]. In particular, issues in algorithmic decision-making in AVs can have undesirable effects on safety and equity. Firstly, data mining processes in AVs are susceptible to biases that lead algorithms to prioritise the safety of certain groups of road users over others and thus, perpetuate discrimination [29,30]. Secondly, many scholars stress the need to design algorithms with ethical considerations to ensure that AVs make ethical driving dec...

show abstract

“…Moreover, the same general type of argument has also been made within the domain of public health research, by Janet Fleetwood. She writes that automated driving is an “incredible invention” likely to “transform transportation” while “saving lives.” For this reason, public health leaders “should welcome” this development (Fleetwood, , p. 536).…”

Section: Part Iii: Crash‐avoidance Strategiesmentioning

confidence: 99%

The ethics of crashes with self‐driving cars: A roadmap, II

Nyholm

2018

Philosophy Compass

View full text Add to dashboard Cite

Self-driving cars hold out the promise of being much safer than regular cars. Yet they cannot be 100% safe. Accordingly, we need to think about who should be held responsible when self-driving cars crash and people are injured or killed. | INTRODUCTIONSome major car manufacturers have recently promised that when the fully self-driving cars that they are developing are ready to go on the market, they will take responsibility in case any crashes occur. Volvo and Audi are among theThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

show abstract

Public Health, Ethics, and Autonomous Vehicles

Abstract: ). Reprints can be ordered at http://www.ajph.org by clicking the "Reprints" link.

Cited by 158 publications

References 15 publications

Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

The ethics of crashes with self‐driving cars: A roadmap, II

Contact Info

Product

Resources

About