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A precautionary approach to autonomous vehicles

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Abstract

In this article, we defend an approach to autonomous vehicle ethics and policy based on the precautionary principle. We argue that a precautionary approach is warranted, given the significant scientific and moral uncertainties related to autonomous vehicles, especially higher-level ones. While higher-level autonomous vehicles may offer many important benefits to society, they also pose significant risks, which are not fully understood at this juncture. Risk management strategies traditionally used by government officials to make decisions about new technologies cannot be applied to higher-level autonomous vehicles because these strategies require accurate and reliable probability estimates concerning the outcomes of different policy options and extensive agreement about values, which are not currently available for autonomous vehicles. Although we describe our approach as precautionary, that does not mean that we are opposed to autonomous vehicle development and deployment, because autonomous vehicles offer benefits that should be pursued. The optimal approach to managing the risks of autonomous vehicles is to take reasonable precautions; that is, to adopt policies that attempt to deal with serious risks in a responsible way without depriving society of important benefits.

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Notes

  1. Since scientific knowledge depends on evidence from observation, experimentations, and other inductive methods, it is never absolutely certain. By “scientific certainty” we therefore mean that scientists have enough evidence to form a rational consensus concerning a hypothesis or theory [34].

  2. In this paper, we will focus on autonomous motor vehicles, such as cars and trucks, but we recognize that autonomous vehicles encompass all kinds of transportation, including trains, airplanes, drones and boats.

  3. The NHTSA scale is similar to the scales developed by Wiseman and the Society of Automotive Engineers (SAE) [37].

  4. Minimization and mitigation are different concepts. Minimization involves taking steps to reduce the probability that a harm will occur, whereas mitigation involves taking steps to minimize the damage from the harm if (or when) it occurs. For example, keeping a car’s tires properly inflated minimizes the risk of having a flat tire and carrying a spare tire mitigates the inconvenience that can result from a flat tire.

  5. Some writers use the term “harm prevention” but this term is ambiguous because there are different ways of preventing a harm. For example, one could try to avoid it or one could minimize the chance that it will occur.

  6. Cost–benefit analysis is a form of quantitative risk/benefit assessment [34]. In cost–benefit analysis, one assigns different probabilities to various outcomes and multiplies that value to create an expected value (or utility).

  7. While some technologies can be enveloped successfully, others are so all-encompassing and powerful that they are difficult to keep within proper boundaries. For example, society has not successfully enveloped social media, which continues to create many problems that were not anticipated initially. It remains to be seen whether AVs can be successfully enveloped, but hopefully they can be.

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Acknowledgements

This research was supported, in part, by the Intramural Program of the National Institute for Environmental Health Sciences (NIEHS), National Institutes of Health (NIH). It does not represent the views of the NIEHS, NIH, or US federal government.

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David Resnik: National Institute of Environmental Health Sciences, ziaes102646-10.

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  1. National Institute of Environmental Health Sciences, National Institutes of Health, 111 TW Alexander Drive, Mail Drop E1-06, PO Box 12233, Research Triangle Park, NC, 27709, USA

    David B. Resnik

  2. Master of Science in Bioethics Student, Columbia University, 203 Lewisohn Hall, 2970 Broadway, Mail Code 4119, New York, NY, 10027-6902, USA

    Suzanne L. Andrews

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  1. David B. Resnik
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Correspondence to David B. Resnik.

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Resnik, D.B., Andrews, S.L. A precautionary approach to autonomous vehicles. AI Ethics 4, 403–418 (2024). https://doi.org/10.1007/s43681-023-00277-6

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