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Can You Program Ethics Into a Self-Driving Car?

When self-driving cars kill, it’s the code (and the coders) that will be put on trial

9 min read
An illustration of a stylized robotic foot on a pedal.
Illustration: Carl De Torres

It’s 2034. A drunken man walking along a sidewalk at night trips and falls directly in front of a driverless car, which strikes him square on, killing him instantly. Had a human been at the wheel, the death would have been considered an accident because the pedestrian was clearly at fault and no reasonable person could have swerved in time. But the “reasonable person” legal standard for driver negligence disappeared back in the 2020s, when the proliferation of driverless cars reduced crash rates by 90 percent. Now the standard is that of the reasonable robot. The victim’s family sues the vehicle manufacturer on that ground, claiming that, although the car didn’t have time to brake, it could have swerved around the pedestrian, crossing the double yellow line and colliding with the empty driverless vehicle in the next lane. A reconstruction of the crash using data from the vehicle’s own sensors confirms this. The plaintiff’s attorney, deposing the car’s lead software designer, asks: “Why didn’t the car swerve?”

Today no court ever asks why a driver does anything in particular in the critical moments before a crash. The question is moot as to liability—the driver panicked, he wasn’t thinking, he acted on instinct. But when robots are doing the driving, “Why?” becomes a valid question. Human ethical standards, imperfectly codified in law, make all kinds of assumptions that engineers have not yet dared to make. The most important such assumption is that a person of good judgment will know when to disregard the letter of the law in order to honor the spirit of the law. What engineers must now do is teach the elements of good judgment to cars and other self-guided machines—that is, to robots.

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Video Friday: Humanoid Soccer

Your weekly selection of awesome robot videos

4 min read
Humans and human-size humanoid robots stand together on an indoor soccer field at the beginning of a game

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

CoRL 2022: 14–18 December 2022, AUCKLAND, NEW ZEALAND
ICRA 2023: 29 May–2 June 2023, LONDON

Enjoy today’s videos!

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Computing With Chemicals Makes Faster, Leaner AI

Battery-inspired artificial synapses are gaining ground

5 min read
Array of devices on a chip

This analog electrochemical memory (ECRAM) array provides a prototype for artificial synapses in AI training.

IBM research

How far away could an artificial brain be? Perhaps a very long way off still, but a working analogue to the essential element of the brain’s networks, the synapse, appears closer at hand now.

That’s because a device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is giving traditional transistor-based AI an unexpected run for its money—and is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse. Researchers recently reported a string of advances at this week’s IEEE International Electron Device Meeting (IEDM 2022) and elsewhere, including ECRAM devices that use less energy, hold memory longer, and take up less space.

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Solving Automotive Design Challenges With Simulation

Learn about low-frequency electromagnetic simulations and see a live demonstration of COMSOL Multiphysics software

1 min read

The development of new hybrid and battery electric vehicles introduces numerous design challenges. Many of these challenges are static or low-frequency electromagnetic by nature, as the devices involved in such designs are much smaller than the operating wavelength. Examples include sensors (such as MEMS sensors), transformers, and motors. Many of these challenges include multiple physics. For instance, sensors activated by acoustic energy as well as heat transfer in electric motors and power electronics combine low-frequency electromagnetic simulations with acoustic and heat transfer simulations, respectively.

Multiphysics simulation makes it possible to account for such phenomena in designs and can provide design engineers with the tools needed for developing products more effectively and optimizing device performance.

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