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11.22.21

The need for speed—understanding the next generation of AI-automobiles

By Daniel J. Schwartz

Artificial Intelligence (AI) in automobiles has become commonplace and even expected in today's newest car models.  Automakers now routinely include "driver assistance technologies" such as self-driving modes, assistance in maintaining lanes and auto-parallel park technologies.  The next generation of automobiles will include even further AI, but this time directed to monitoring and sensing the behavior, potential impairment and mood of the driver and its occupants.  (See The Next Generation of AI-Enabled Cars Will Understand You, IEEE Spectrum, November 8, 2011).

Examples of new technologies presently under development include cameras/sensors throughout the cabin to detect the occupants' emotions, cognitive states, behaviors, activities and interactions among each other and objects in the car.  Particular examples of these new technologies include detection of driver drowsiness (before it is too late to prevent an accident) or detection of an infant or pet has been left in an automobile. These examples require further nuanced, yet powerful, technology to understand human behavior and cognitive states.

Regulatory entities around the globe are beginning to take notice.  In Europe, the safety rating system known as European New Car Assessment Program (Euro NCAP) updated its protocols in 2020 to begin rating cars based on advanced occupant-status monitoring criteria, including the ability to detect fatigue and distraction.  In 2020, Euro NCAP will further award ratings based on the ability to the presence of infants left unattended in a car.  The push for similar ratings will likely emerge in the U.S. shortly as well.

However, while these new technologies enhance both safety and the driving experience, they also raise many privacy and regulatory issues that will demand the attention of both automakers and the relevant regulatory bodies.  The increased collection of data for vehicle occupants (including passengers in ride-share vehicles such as Ubers and Lyfts) raise obvious privacy concerns such as data storage, data lifespan, data location, data rights and access and the option to "opt-out" from having such information collected.  Similarly, to the extent behaviors and social states are monitored, the technology must account for diverse populations, including age, gender, race and ethnicity.

Nixon Peabody continues to track these developments in both the AI and data privacy space and will continue to provide these timely updates.

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Daniel J. Schwartz

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