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You are here: Home / AI / Who Is Accountable When the Robot Decides?

June 23, 2026 by David Such Leave a Comment

Who Is Accountable When the Robot Decides?

On the night of 18 March 2018, an Uber test car in Tempe, Arizona, struck and killed Elaine Herzberg as she wheeled a bicycle across an unlit road. The car had detected her 5.6 seconds before impact. Its software could not work out what she was. It cycled through “unknown object,” then “vehicle,” then “bicycle,” and never settled in time to brake. About 1.3 seconds before the collision the system concluded it needed to stop. It did not stop, because Uber had switched off the car’s automatic emergency braking during testing and was relying on the human in the seat to intervene.

The human in the seat was a safety operator named Rafaela Vasquez. She was watching a television show on her phone. She did not touch the brake until after the car had hit.

When the courts went looking for someone to hold responsible, they found her. Vasquez was charged with negligent homicide, later pleaded guilty to endangerment, and was sentenced to three years of probation. Uber faced no criminal charges. The federal investigators were blunt about the design: the company had removed the car’s ability to brake for itself and left a distracted person as the last line of defence. The system was built so that the only party who could stop the car was the one least equipped to.

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Filed Under: AI, Embedded, IoT, Robotics, Title Post Tagged With: embedded AI

About David Such

David Such is an embedded systems engineer and Director of Reefwing Software, based in Sydney, Australia. He develops IoT devices, robotics platforms, and drone flight control systems, with a focus on deploying intelligence on resource-constrained hardware.

David has over 30 years of industry experience spanning embedded development, systems engineering, and senior leadership. He has held executive roles including Managing Director of Serco Australia and senior management positions at Honeywell and Tyco. He was an Honorary Associate at the University of Sydney, where he mentored aspiring entrepreneurs through the Business Industry Mentoring Program and the Lean Startup course in the Faculty of Business.

His open-source sensor fusion and flight controller libraries, published under the Reefwing Software organisation on GitHub, are used by embedded developers and robotics hobbyists worldwide. He writes extensively on embedded AI, sensor systems, and edge computing across several publications on Medium, where his technical articles have built a substantial following among hardware engineers working at the edge.

David holds a BE in Electrical Engineering, a BSc in Computing Science and Physics, a BAppSc, and an MBA in Strategy.

Embedded AI: A Practical Guide to Building Intelligence on Microcontrollers is his first book with No Starch Press.

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