Robohub.org
 

Two New Year’s resolutions for developers of automated vehicles


by
12 January 2016



share this:

self_driving_Robocar_autonomous_car_spedometer_accelerate_needle_speedIn the spirit of the New Year, and especially in the wake of California’s draft rules for the (theoretical) operation of automated motor vehicles, I offer two resolutions for any serious developer of an automated driving (or flying) system.

Such a developer should:

1) Detail the specific changes to existing law, if any, that the developer needs in order to deploy its system in each jurisdiction of interest. Serious developers should already be conducting legal research and development commensurate with their technical research and development; sharing their legal conclusions (rather than merely making generalized statements about the need for uniformity or clarity) will complement the comprehensive legal audits that I have urged governments to conduct.

2) Make what I call a “public safety case” that candidly explains how the developer (a) defines reasonable safety, (b) will satisfy itself that its sytem is reasonably safe, and (c) will continue to do so over the lifetime of the system. This public safety case will be crucial to appropriately managing public expectations in both directions, to easing the concerns of regulators who are understandably wary about asserting the safety of novel systems, and to establishing norms against which amateur efforts at automation might be measured.

In many cases, an automated system may not be mature enough for its developer to understand the specific legal implications or to articulate a specific safety philosophy. If so, that is also a valuable message. As automated systems become more visible on public roads (and in public airspace), their developers should step more fully into the broader public sphere.



tags: , ,


Bryant Walker Smith is an expert on the legal aspects of autonomous driving and a fellow at Stanford Law School.
Bryant Walker Smith is an expert on the legal aspects of autonomous driving and a fellow at Stanford Law School.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Robot Talk Episode 170 – Robots in the real world, with Daniela Shchegelskaya

  13 Nov 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Daniela Shchegelskaya from the University of Twente about getting robots to operate reliably in safety-critical environments.

AI100 report released: embodied AI highlighted as grand challenge

  11 Nov 2026
Embodied AI is listed as one of the most inspiring open grand challenges.

AIhub coffee corner: Are humanoids the future of embodied AI?

  09 Nov 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.

Robot Talk Episode 169 – Robot sensing inspired by nature, with Dexter Shepherd

  06 Nov 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Dexter Shepherd from the University of Sussex about using artificial intelligence to help robots understand and adapt to their environment.

Robots in society, business and culture: October 2026

We showcase a selection of robotics stories from society, business, research and culture.

Muscle coordination can be mimicked by electric motors – it could lead to improved robots

  02 Nov 2026
Researchers built a physical model using ordinary electric motors to try and simulate how muscles may perform tasks.

Robot Talk Episode 168 – Advancing robotics with novel electronics, with Zlatka Stoeva

  30 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Zlatka Stoeva from DZP Technologies about flexible, stretchable and soft printed electronics for dexterous robots.

Competing in RoboCup@Home and winning the 2026 best paper award: an interview with Raphael Memmesheimer

and   28 Oct 2026
Hear more about Raphael's research and his involvement in the RoboCup@Home league.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence