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Moving towards safe autonomous systems

Data that reflects the intended functionality

This is my final article in this series; a great way to start the New Year! This article, in a way, is the practical conclusion of my research and so I will discuss my recommendations for law, policy and ethics for the United Arab Emirates (UAE).

The role of human factors in the safe design and use of AI in healthcare

Products, systems and organisations are increasingly dependent on data. In today’s Data-Centric Systems (DCS) data is no longer inert and passive. Its many active roles demand that data is treated as a separate system component.

I will compare the UAE liability regime to others, in particular the European Union regime and its approach to the liability of autonomous systems.

In this second post, I discuss the remedies available to a person who has suffered harm by an autonomous system.

The main point of law is the following: Who is liable when an autonomous system causes injury or death to a person or damage to property?

The term “AI safety” means different things to different people. Alongside the general community of AI and ML researchers and engineers, there are two different research communities working on AI safety.

This is the last in a series of blog posts exploring the safety assurance of highly automated driving to accompany a new AAIP report which is free to download on the website.

This is the fifth in a series of blog posts exploring the safety assurance of highly automated driving to accompany a new AAIP report which is free to download on the website.

This is the fourth in a series of blog posts exploring the safety assurance of highly automated driving to accompany a new AAIP report which is free to download on the website.

The idea that the driver is integral to vehicle control is fundamental to the automotive functional safety risk model. So what happens when we introduce autonomy?

This is the third in a series of blog posts exploring the safety assurance of highly automated driving to accompany a new AAIP report which is free to download on the website.

This is the second in a series of blog posts exploring the safety assurance of highly automated driving to accompany a new AAIP report which is free to download on the website.

This is the first in a series of blog posts exploring the safety assurance of highly automated driving to accompany a new AAIP report which is free to download on the website.

The societal benefits of autonomous vehicles (AVs) — those that operate fully without a driver — have never been clearer than they are right now. The delivery of essential items, such as medical supplies and food, with limited human contact, would serve us well in the current Coronavirus climate. While the development of AV performance is key, we must not neglect the assurance of their safety.

Consider an intensive care unit (ICU) where clinicians are treating patients for sepsis. They must review multiple informational inputs (patient factors, disease stage, bacteria, and other influences) in their diagnosis and treatment. If the patient is treated incorrectly who do you hold responsible? The clinician? The hospital? What if an aspect of the treatment was undertaken by a system using Artificial Intelligence (AI)? Who (or what) is responsible then?

Boeing may never have conceived the Boeing 737 's Manoeuvring Characteristics Augmentation System as an autonomous system. In effect, however, it was autonomous: it took decisions about stall without involving the pilots.

Human control of artificial intelligence (AI) and autonomous systems (AS) is always possible — but the questions are: what form of control is possible, and how is control assured?

Safety and security are two fundamental properties for achieving trustworthy cyber physical systems (CPS). It is generally agreed that the gap between the two has become less clear, but the relationship between them is still inadequately understood.

The recent news that Uber isn’t criminally liable for the fatal crash in Tempe raises interesting questions. Read our blog post of two halves – ethical and legal.

Considering the intent of requirements in machine learning.

Does machine learning give us super-human powers when it comes to perception in autonomous driving?

Do advanced driver assistance systems (ADAS) that perform too well become dangerous by giving us a false sense of security?