Automated vehicles, big data and public health
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4524540
Author(s) Shaw, David; Favrat, Bernard; Elger, Bernice
Author(s) at UniBasel Shaw, David
Elger, Bernice Simone
Year 2019
Title Automated vehicles, big data and public health
Journal Medicine, health care, and philosophy
Pages / Article-Number 1-8
Keywords Autonomous cars; Big data; Ethics; Public health
Abstract In this paper we focus on how automated vehicles can reduce the number of deaths and injuries in accident situations in order to protect public health. This is actually a problem not only of public health and ethics, but also of big data-not only in terms of all the different data that could be used to inform such decisions, but also in the sense of deciding how wide the scope of data should be. We identify three key different types of data, including basic data, advanced data and preference data, provide an ethical analysis of the use of these different types of data and of different ways of prioritizing between pedestrians and passengers, and propose four rules that can help set ethical priorities for ethical data use and decision making by automated vehicles.
Publisher Springer
ISSN/ISBN 1386-7423 ; 1572-8633
edoc-URL https://edoc.unibas.ch/74100/
Full Text on edoc No
Digital Object Identifier DOI 10.1007/s11019-019-09903-9
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/31065857
ISI-Number MEDLINE:31065857
Document type (ISI) Journal Article
 
   

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23/05/2022