Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles

Download or Read eBook Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles PDF written by Jennifer Dukarski and published by SAE International. This book was released on 2021-09-13 with total page 42 pages. Available in PDF, EPUB and Kindle.
Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles
Author :
Publisher : SAE International
Total Pages : 42
Release :
ISBN-10 : 9781468603668
ISBN-13 : 1468603663
Rating : 4/5 (68 Downloads)

Book Synopsis Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles by : Jennifer Dukarski

Book excerpt: Modern automobiles collect around 25 gigabytes of data per hour and autonomous vehicles are expected to generate more than 100 times that number. In comparison, the Apollo Guidance Computer assisting in the moon launches had only a 32-kilobtye hard disk. Without question, the breadth of in-vehicle data has opened new possibilities and challenges. The potential for accessing this data has led many entrepreneurs to claim that data is more valuable than even the vehicle itself. These intrepid data-miners seek to explore business opportunities in predictive maintenance, pay-as-you-drive features, and infrastructure services. Yet, the use of data comes with inherent challenges: accessibility, ownership, security, and privacy. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles examines some of the pressing questions on the minds of both industry and consumers. Who owns the data and how can it be used? What are the regulatory regimes that impact vehicular data use? Is the US close to harmonizing with other nations in the automotive data privacy? And will the risks of hackers lead to the “zombie car apocalypse” or to another avenue for ransomware? This report explores a number of these legal challenges and the unsettled aspects that arise in the world of automotive data. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2021019


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