Ca(r)veat Emptor: Crowdsourcing Data to Challenge the Testimony of In-Car 
Technology

Gless, Sabine; Di, Xuan; Silverman, Emily

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Ca(r)veat Emptor: Crowdsourcing Data to Challenge the Testimony of In-Car Technology

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Silverman, Emily
Criminal Law, Max Planck Institute for the Study of Crime, Security and Law, Max Planck Society;

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引用

Gless, S., Di, X., & Silverman, E. (2022). Ca(r)veat Emptor: Crowdsourcing Data to Challenge the Testimony of In-Car Technology. Jurimetrics, 62(3), 285-302.

引用: https://hdl.handle.net/21.11116/0000-000A-F9BE-8

要旨

This Article addresses the situation in which a car acts as a witness against its human driver in a court of law. This possibility has become a reality due to technology embedded in modern-day vehicles that captures data prior to a crash event. The authors contend that it is becoming increasingly difficult for drivers to defend themselves in a meaningful way against the testimony of cars and suggest that crowdsourcing data could be a viable option for assessing the trustworthiness of such evidence. The Article further explores whether crowdsourced data could be used as an additional source of information in the fact-finding process and if such data could provide a counterbalance to the prevailing tendency to fault human drivers rather than their vehicles or the manufactures of their vehicles. The practical importance of this issue in the age of driving automation is highlighted, and lawyers, judges, and lawmakers are urged to remain open-minded regarding the use of this new strategy.