RoboTED: a case study in Ethical Risk Assessment

A few weeks ago I gave a short paper* at the excellent International Conference on Robot Ethics and Standards (ICRES 2020), outlining a case study in Ethical Risk Assessment - see our paper here. Our chosen case study is a robot teddy bear, inspired by one of my favourite movie robots: Teddy, in A.I. Artificial Intelligence.

Although Ethical Risk Assessment (ERA) is not new - it is after all what research ethics committees do - the idea of extending traditional risk assessment, as practised by safety engineers, to cover ethical risks is new. ERA is I believe one of the most powerful tools available to the responsible roboticist, and happily we already have a published standard setting out a guideline on ERA for robotics in BS 8611, published in 2016.

Before looking at the ERA, we need to summarise the specification of our fictional robot teddy bear: RoboTed. First, RoboTed is based on the following technology:

• RoboTed is an Internet (WiFi) connected device, 
• RoboTed has cloud-based speech recognition and conversational AI (chatbot) and local speech synthesis,
• RoboTed’s eyes are functional cameras allowing RoboTed to recognise faces,
• RoboTed has motorised arms and legs to provide it with limited baby-like movement and locomotion.

And second RoboTed is designed to:

• Recognise its owner, learning their face and name and turning its face toward the child.
• Respond to physical play such as hugs and tickles.
• Tell stories, while allowing a child to interrupt the story to ask questions or ask for sections to be repeated.
• Sing songs, while encouraging the child to sing along and learn the song.
• Act as a child minder, allowing parents to both remotely listen, watch and speak via RoboTed.

The tables below summarise the ERA of RoboTED for (1) psychological, (2) privacy & transparency and (3) environmental risks. Each table has 4 columns, for the hazard, risk, level of risk (high, medium or low) and actions to mitigate the risk. BS8611 defines an ethical risk as the “probability of ethical harm occurring from the frequency and severity of exposure to a hazard”; an ethical hazard as “a potential source of ethical harm”, and an ethical harm as “anything likely to compromise psychological and/or societal and environmental well-being".

(1) Psychological Risks

(2) Security and Transparency Risks

(3) Environmental Risks

For a more detailed commentary on each of these tables see our full paper - which also, for completeness, covers physical (safety) risks.

And here are the slides from my short ICRES 2020 presentation:

Through this fictional case study we argue we have demonstrated the value of ethical risk assessment. Our RoboTed ERA has shown that attention to ethical risks can

• suggest new functions, such as “RoboTed needs to sleep now”,
• draw attention to how designs can be modified to mitigate some risks, 
• highlight the need for user engagement, and
• reject some product functionality as too risky.

But ERA is not guaranteed to expose all ethical risks. It is a subjective process which will only be successful if the risk assessment team are prepared to think both critically and creatively about the question: what could go wrong? As Shannon Vallor and her colleagues write in their excellent Ethics in Tech Practice toolkit design teams must develop the “habit of exercising the skill of moral imagination to see how an ethical failure of the project might easily happen, and to understand the preventable causes so that they can be mitigated or avoided”.

 

*Which won the conference best paper prize!

Why ethical robots might not be such a good idea after all

This week my colleague Dieter Vanderelst presented our paper: The Dark Side of Ethical Robots at AIES 2018 in New Orleans.

I blogged about Dieter's very elegant experiment here, but let me summarise. With two NAO robots he set up a demonstration of an ethical robot helping another robot acting as a proxy human, then showed that with a very simple alteration of the ethical robot's logic it is transformed into a distinctly unethical robot - behaving either competitively or aggressively toward the proxy human.

Here are our paper's key conclusions:

The ease of transformation from ethical to unethical robot is hardly surprising. It is a straightforward consequence of the fact that both ethical and unethical behaviours require the same cognitive machinery with – in our implementation – only a subtle difference in the way a single value is calculated. In fact, the difference between an ethical (i.e. seeking the most desirable outcomes for the human) robot and an aggressive (i.e. seeking the least desirable outcomes for the human) robot is a simple negation of this value.

On the face of it, given that we can (at least in principle) build explicitly ethical machines* then it would seem that we have a moral imperative to do so; it would appear to be unethical not to build ethical machines when we have that option. But the findings of our paper call this assumption into serious doubt. Let us examine the risks associated with ethical robots and if, and how, they might be mitigated. There are three.

1. First there is the risk that an unscrupulous manufacturer might insert some unethical behaviours into their robots in order to exploit naive or vulnerable users for financial gain, or perhaps to gain some market advantage (here the VW diesel emissions scandal of 2015 comes to mind). There are no technical steps that would mitigate this risk, but the reputational damage from being found out is undoubtedly a significant disincentive. Compliance with ethical standards such as BS 8611 guide to the ethical design and application of robots and robotic systems, or emerging new IEEE P700X ‘human’ standards would also support manufacturers in the ethical application of ethical robots. 
2. Perhaps more serious is the risk arising from robots that have user adjustable ethics settings. Here the danger arises from the possibility that either the user or a technical support engineer mistakenly, or deliberately, chooses settings that move the robot’s behaviours outside an ‘ethical envelope’. Much depends of course on how the robot’s ethics are coded, but one can imagine the robot’s ethical rules expressed in a user-accessible format, for example, an XML like script. No doubt the best way to guard against this risk is for robots to have no user adjustable ethics settings, so that the robot’s ethics are hard-coded and not accessible to either users or support engineers. 
3. But even hard-coded ethics would not guard against undoubtedly the most serious risk of all, which arises when those ethical rules are vulnerable to malicious hacking. Given that cases of white-hat hacking of cars have already been reported, it's not difficult to envisage a nightmare scenario in which the ethics settings for an entire fleet of driverless cars are hacked, transforming those vehicles into lethal weapons. Of course, driverless cars (or robots in general) without explicit ethics are also vulnerable to hacking, but weaponising such robots is far more challenging for the attacker. Explicitly ethical robots focus the robot’s behaviours to a small number of rules which make them, we think, uniquely vulnerable to cyber-attack.

Ok, taking the most serious of these risks: hacking, we can envisage several technical approaches to mitigating the risk of malicious hacking of a robot’s ethical rules. One would be to place those ethical rules behind strong encryption. Another would require a robot to authenticate its ethical rules by first connecting to a secure server. An authentication failure would disable those ethics, so that the robot defaults to operating without explicit ethical behaviours. Although feasible, these approaches would be unlikely to deter the most determined hackers, especially those who are prepared to resort to stealing encryption or authentication keys.

It is very clear that guaranteeing the security of ethical robots is beyond the scope of engineering and will need regulatory and legislative efforts. Considering the ethical, legal and societal implications of robots, it becomes obvious that robots themselves are not where responsibility lies. Robots are simply smart machines of various kinds and the responsibility to ensure they behave well must always lie with human beings. In other words, we require ethical governance, and this is equally true for robots with or without explicit ethical behaviours.

Two years ago I thought the benefits of ethical robots outweighed the risks. Now I'm not so sure. I now believe that - even with strong ethical governance - the risks that a robot’s ethics might be compromised by unscrupulous actors are so great as to raise very serious doubts over the wisdom of embedding ethical decision making in real-world safety critical robots, such as driverless cars. Ethical robots might not be such a good idea after all.

*As a footnote let me explain what I mean by explicitly ethical robots: these are robots that select behaviours on the basis of ethical rules - in a sense they can be said to reason about ethics (in our case by evaluating the ethical consequences of several possible actions). Here I'm using the terminology of James Moor, who proposed four kinds of ethical agents, as I explain here. Moor shows in his classification that all robots (and AIs) are ethical agents in the sense that they can all have an ethical impact.

Thus, even though we're calling into question the wisdom of explicitly ethical robots, that doesn't change the fact that we absolutely must design all robots to minimise the likelihood of ethical harms, in other words we should be designing implicitly ethical robots within Moor's schema.

Here is the full reference to our paper:

Vanderelst D and Winfield AFT (2018), The Dark Side of Ethical Robots, AAAI/ACM Conf. on AI Ethics and Society (AIES 2018), New Orleans.

---

Related blog posts:
The Dark side of Ethical Robots
Could we make a moral machine?
How ethical is your ethical robot?
Towards ethical robots: an update
Towards an Ethical Robot

Ethical Governance: what is it and who's doing it?

These days I often find myself talking about ethical governance. Not just talking about but advocating: for instance in written evidence to the 2016 parliamentary select committee on robots and AI I made the link between ethical governance and trust. I believe that without transparent ethical governance robotics and AI will not win public trust, and without trust we will not see the societal benefits of robots and AI that we all hope for.

But what exactly is ethical governance and who is doing it, and perhaps more importantly, who in robotics and AI is doing it well?

In a draft paper on the subject I define ethical governance as

a set of processes, procedures, cultures and values designed to ensure the highest standards of behaviour. Ethical governance thus goes beyond simply good (i.e. effective) governance, in that it inculcates ethical behaviours. Normative ethical governance is seen as an important pillar of responsible research and innovation (RRI), which “entails an approach, rather than a mechanism, so it seeks to deal with ethical issues as or before they arise in a principled manner rather than waiting until a problem surfaces and dealing with it in an ad hoc way [1]” 

The link I make here between ethical governance and responsible research and innovation is I think really important. Ethical governance is a key part of RRI. They are not the same thing but it would be hard to imagine good ethical governance without RRI, and vice versa.

So what would I expect of companies or organisations who claim to be ethical? As a starting point for discussion here are five things that ethical companies should do:

• Have an ethical code of conduct, so that everyone in the company understands what is expected of them. This should sit alongside a mechanism which allows employees to be able to raise ethical concerns, if necessary in confidence, without fear of displeasing a manager.
• Provide ethics training for everyone, without exception. Ethics, like quality, is not something you can do as as add-on; simply appointing an ethics manager, while not a bad idea, is not enough. Ethical governance needs to become part of a company's culture and DNA, not just in product development but in management, finance, HR and marketing too.
• Undertake ethical risk assessments of all new products, and act upon the findings of those assessments. A toolkit, or method, for ethical risk assessment of robots and robotic systems exists in British Standard BS 8611, which - alongside much else - sets out 20 ethical risks and hazards together with recommendations on how to mitigate these and verify that they have been addressed.
• Be transparent about your ethical governance. Of course your robots and AIs must be transparent too, but here I mean transparency of process, not product. It's not enough to claim to be ethical, you need to show how you are ethical. That means publishing your ethical code of conduct, membership of your ethics board if you have one (and its terms of reference), and ideally case studies showing how you have conducted ethical risk assessments.
• Really value ethical governance.  Even if you have the four processes above in place you also needs to be sincere about ethical governance; that ethical governance is one of your core values, and just not a smokescreen for what you really value, like maximising shareholder returns.

My final point about really valuing ethical governance is of course hard to evidence. But, like trust, confidence in a company's claim to be ethical has to be earned and - as we've seen - can easily be damaged.

This brings me to my second question: who is doing ethical governance? And are there any examples of best practice? A week or so ago I asked Twitter this question. I've had quite a few nominations but haven't yet looked into them all. When I have, I will complete this blog post.

---

[1] Rainey, S., and Goujon, P. (2011). Toward a Normative Ethical of Governance of Technology. Contextual Pragmatism and Ethical Governance. In Ren von Schomberg (ed.) Towards Responsible Research and Innovation in the Information and Communication Technologies and Security Technologies Fields, Report of the European Commission-DG Research and Innovation.

Does AI pose a threat to society?

Last week I had the pleasure of debating the question "does AI pose a threat to society?" with friends and colleagues Christian List, Maja Pantic and Samantha Payne. The event was organised by the British Academy and brilliantly chaired by the Royal Society's director of science policy Claire Craig.

Here is my opening statement:

One Friday afternoon in 2009 I was called by a science journalist at, I recall, the Sunday Times. He asked me if I knew that there was to be a meeting of the AAAI to discuss robot ethics. I said no I don’t know of this meeting. He then asked “are you surprised they are meeting to discuss robot ethics” and my answer was no. We talked some more and agreed it was actually a rather dull story: a case of scientists behaving responsibly. I really didn’t expect the story to appear but checked the Sunday paper anyway, and there in the science section was the headline Scientists fear revolt of killer robots. (I then spent the next couple of days on the radio explaining that no, scientists do not fear a revolt of killer robots.)

So, fears of future super intelligence - robots taking over the world - are greatly exaggerated: the threat of an out-of-control super intelligence is a fantasy - interesting for a pub conversation perhaps. It’s true we should be careful and innovate responsibly, but that’s equally true for any new area of science and technology. The benefits of robotics and AI are so significant, the potential so great, that we should be optimistic rather than fearful. Of course robots and intelligent systems must be engineered to very high standards of safety for exactly the same reasons that we need our washing machines, cars and airplanes to be safe. If robots are not safe people will not trust them. To reach it’s full potential what robotics and AI needs is a dose of good old fashioned (and rather dull) safety engineering.

In 2011 I was invited to join a British Standards Institute working group on robot ethics, which drafted a new standard BS 8611 Guide to the ethical design of robots and robotic systems, published in April 2016. I believe this to be the world’s first standard on ethical robots.

Also in 2016 the very well regarded IEEE standards association – the same organization that gave us WiFi - launched a Global initiative on Ethical Considerations in AI and Autonomous Systems. The purpose of this Initiative is to ensure every technologist is educated and empowered to prioritize ethical considerations in the design and development of autonomous and intelligent systems; in a nutshell, to ensure ethics are baked in. In December we published Ethically Aligned Design: A Vision for Prioritizing Human Well Being with AI and Autonomous Systems. Within that initiative I'm also leading a new standard on transparency in autonomous systems, based on the simple principle that it should always be possible to find out why an AI or robot made a particular decision.

We need to agree ethical principles, because they are needed to underpin standards – ways of assessing and mitigating the ethical risks of robotics and AI. But standards needs teeth and in turn underpin regulation. Why do we need regulation? Think of passenger airplanes; the reason we trust them is because it's a highly regulated industry with an amazing safety record, and robust, transparent processes of air accident investigation when things do go wrong. Take one example of a robot that we read a lot about in the news – the Driverless Car. I think there's a strong case for a driverless car equivalent of the CAA, with a driverless car accident investigation branch. Without this it's hard to see how driverless car technology will win public trust.

Does AI pose a threat to society? No. But we do need to worry about the down to earth questions of present day rather unintelligent AIs; the ones that are deciding our loan applications, piloting our driverless cars or controlling our central heating. Are those AIs respecting our rights, freedoms and privacy? Are they safe? When AIs make bad decisions, can we find out why? And I worry too about the wider societal and economic impacts of AI. I worry about jobs of course, but actually I think there is a bigger question: how can we ensure that the wealth created by robotics and AI is shared by all in society?

Thank you.

This image was used to advertise the BA's series of events on the theme Robotics, AI and Society. The reason I reproduce it here is that one of the many interesting questions to the panel was about the way that AI tends to be visualised in the media. This kind of human face coalescing (or perhaps emerging) from the atomic parts of the AI seems to have become a trope for AI. Is it a helpful visualisation of the human face of AI, or does it mislead to an impression that AI has human characteristics?

Thoughts on the EU's draft report on robotics

A few weeks ago I was asked to write a short op-ed on the European Parliament Law Committee's recommendations on civil law rules for robotics.

In the end the piece didn't get published, so I am posting it here.

It is a great shame that most reports of the European Parliament’s Committee for Legal Affairs’ vote last week on its Draft Report on Civil Law Rules on Robotics headlined on ‘personhood’ for robots, because the report has much else to commend it. Most important among its several recommendations is a proposed code of ethical conduct for roboticists, which explicitly asks designers to research and innovate responsibly. Some may wonder why such an invitation even needs to be made but, given that engineering and computer science education rarely includes classes on ethics (it should), it is really important that robotics engineers reflect on their ethical responsibilities to society – especially given how disruptive robot technologies are. This is not new – great frameworks for responsible research and innovation already exist. One such is the 2014 Rome Declaration on RRI, and in 2015 the Foundation for Responsible Robotics was launched.

Within the report’s draft Code of Conduct is a call for robotics funding proposals to include a risk assessment. This too is a very good idea and guidance already exists in British Standard BS 8611, published in April 2016. BS 8611 sets out a comprehensive set of ethical risks and offers guidance on how to mitigate them. It is very good also to see that the Code stresses that humans, not robots, are the responsible agents; this is something we regarded as fundamental when we drafted the Principles of Robotics in 2010.

For me transparency (or the lack of it) is an increasing worry in both robots and AI systems. Labour’s industry spokesperson Chi Onwurah is right to say, “Algorithms are part of our world, so they are subject to regulation, but because they are not transparent, it’s difficult to regulate them effectively” (and don’t forget that it is algorithms that make intelligent robots intelligent). So it is very good to see the draft Code call for robotics engineers to “guarantee transparency … and right of access to information by all stakeholders”, and then in the draft ‘Licence for Designers’: you should ensure “maximal transparency” and even more welcome “you should develop tracing tools that … facilitate accounting and explanation of robotic behaviour… for experts, operators and users”.  Within the IEEE Standards Association Global Initiative on Ethics in AI and Autonomous Systems, launched in 2016, we are working on a new standard on Transparency in Autonomous Systems.

This brings me to standards and regulation.  I am absolutely convinced that regulation, together with transparency and public engagement, builds public trust. Why is it that we trust our tech? Not just because it’s cool and convenient, but also because it’s safe (and we assume that the disgracefully maligned experts will take care of assuring that safety). One of the reasons we trust airliners is that we know they are part of a highly regulated industry with an amazing safety record. The reason commercial aircraft are so safe is not just good design, it is also the tough safety certification processes and, when things do go wrong, robust processes of air accident investigation. So the Report’s call for a European Agency for Robotics and AI to recommend standards and regulatory framework is, as far as I’m concerned, not a moment too soon. We urgently need standards for safety certification of a wide range of robots, from drones and driverless cars to robots for care and assisted living.

Like many of my robotics colleagues I am deeply worried by the potential for robotics and AI to increase levels of economic inequality in the world. Winnie Byanyima, executive director of Oxfam writes for the WEF, “We need fundamental change to our economic model. Governments must stop hiding behind ideas of market forces and technological change. They … need to steer the direction of technological development”. I think she is right – we need a serious public conversation about technological unemployment and how we ensure that the wealth created by AI and Automonous Systems is shared by all. A Universal Basic Income may or may not be the best way to do this – but it is very encouraging to see this question raised in the draft Report.

I cannot close the piece without at least mentioning artificial personhood. My own view is that personhood is the solution to a problem that doesn’t exist. I can understand why, in the context of liability, the Report raises this question for discussion, but – as the report itself later asserts in the Code of Conduct: humans, not robots are the responsible agents. Robots are, and should remain, artefacts.

From ethics to regulation and governance

The following text was drafted in response to question 4 of the Parliamentary Science and Technology Committee Inquiry on Robotics and Artificial Intelligence on The social, legal and ethical issues raised by developments in robotics and artificial intelligence technologies, and how they should be addressed.

---

From Ethics to Regulation and Governance

1. Public attitudes. It is well understood that there are public fears around robotics and artificial intelligence. Many of these fears are undoubtedly misplaced, fuelled perhaps by press and media hype, but some are grounded in genuine worries over how the technology might impact, for instance, jobs or privacy. The most recent Eurobarometer survey on autonomous systems showed that the proportion of respondents with an overall positive attitude has declined from 70% in the 2012 survey to 64% in 2014. Notably the 2014 survey showed that the more personal experience people have with robots, the more favourably they tend to think of them; 82% of respondents have a positive view of robots if they have experience with them, whereas only 60% of respondents have a positive view if they lack robot experience. Also important is that a significant majority (89%) believe that autonomous systems are a form of technology that requires careful management.

2. Building trust in robotics and artificial intelligence requires a multi-faceted approach. The ethics roadmap here illustrates the key elements that contribute to building public trust. The core idea of the roadmap is that ethics inform standards, which in turn underpin regulation.

3. Ethics are the foundation of trust, and underpin good practice. Principles of good practice can be found in Responsible Research and Innovation (RRI). Examples include the 2014 Rome Declaration on RRI; the six pillars of the Rome declaration on RRI are: Engagement, Gender equality, Education, Ethics, Open Access and Governance. The EPSRC framework for responsible innovation incorporates the AREA (Anticipate, Reflect, Engage and Act) approach.

4. The first European work to articulate ethical considerations for robotics was the EURON Roboethics Roadmap.

5. In 2010 a joint AHRC/EPSRC workshop drafted and published the Principles of Robotics for designers, builders and users of robots. The principles are:

• Robots are multi-use tools. Robots should not be designed solely or primarily to kill or harm humans, except in the interests of national security;
• Humans, not robots, are responsible agents. Robots should be designed; operated as far as is practicable to comply with existing laws & fundamental rights & freedoms, including privacy.
• Robots are products. They should be designed using processes which assure their safety and security.
• Robots are manufactured artefacts. They should not be designed in a deceptive way to exploit vulnerable users; instead their machine nature should be transparent.
• The person with legal responsibility for a robot should be attributed.

6. Work by the British Standards Institute technical subcommittee on Robots and Robotic Devices led to publication – in April 2016 – of BS 8611: Guide to the ethical design and application of robots and robotic systems. BS8611 is not a code of practice; instead it gives “guidance on the identification of potential ethical harm and provides guidelines on safe design, protective measures and information for the design and application of robots”. BS8611 articulates a broad range of ethical hazards and their mitigation, including societal, application, commercial/financial and environmental risks, and provides designers with guidance on how to assess then reduce the risks associated with these ethical hazards. The societal hazards include, for example, loss of trust, deception, privacy & confidentiality, addiction and employment.

7. The IEEE has recently launched a global initiative on Ethical Considerations in the Design of Autonomous Systems, to encompass all intelligent technologies including robotics, AI, computational intelligence and deep learning.

8. Significant recent work towards regulation was undertaken by the EU project RoboLaw. The primary output of that project is a comprehensive report entitled Guidelines on Regulating Robotics. That report reviews both ethical and legal aspects; the legal analysis covers rights, liability & insurance, privacy and legal capacity. The report focuses on driverless cars, surgical robots, robot prostheses and care robots and concludes by stating: “The field of robotics is too broad, and the range of legislative domains affected by robotics too wide, to be able to say that robotics by and large can be accommodated within existing legal frameworks or rather require a lex robotica. For some types of applications and some regulatory domains, it might be useful to consider creating new, fine-grained rules that are specifically tailored to the robotics at issue, while for types of robotics, and for many regulatory fields, robotics can likely be regulated well by smart adaptation of existing laws”.

9. In general technology is trusted if it brings benefits while also safe, well regulated and, when accidents happen, subject to robust investigation. One of the reasons we trust airliners is that we know they are part of a highly regulated industry with an excellent safety record. The reason commercial aircraft are so safe is not just good design, it is also the tough safety certification processes and, when things do go wrong, robust processes of air accident investigation. Should driverless cars, for instance, be regulated through a body similar to the Civil Aviation Authority (CAA), with a driverless car equivalent of the Air Accident Investigation Branch?

10. The primary focus of paragraphs 1 – 9 above is robotics and autonomous systems, and not software artificial intelligence. This reflects the fact that most work toward ethics and regulation has focussed on robotics. Because robots are physical artefacts (which embody AI) they are undoubtedly more readily defined and hence regulated than distributed or cloud-based AIs. This and the already pervasive applications of AI (in search engines, machine translation systems or intelligent personal assistant AIs, for example) strongly suggest that greater urgency needs to be directed toward considering the societal and ethical impact of AI, including the governance and regulation of AI.

11. AI systems raise serious questions over trust and transparency:

• How can we trust the decisions made by AI systems, and – more generally – how can the public have confidence in the use of AI systems in decision making?
• If an AI system makes a decision that turns out to be disastrously wrong, how do we investigate the logic by which the decision was made?
• Of course much depends of the consequences of those decisions. Consider decisions that have real consequences to human safety or well being, such as those made by medical diagnosis AIs or driverless car autopilots. Systems that make such decisions are critical systems.

12. Existing critical software systems are not AI systems, nor do they incorporate AI systems. The reason is that AI systems (and more generally machine learning systems) are generally regarded as impossible to verify for safety critical applications - the reasons for this need to be understood.

• First is the problem of verification of systems that learn. Current verification approaches typically assume that the system being verified will never change its behaviour, but a system that learns does – by definition – change its behaviour, so any verification is likely to be rendered invalid after the system has learned.
• Second is the black box problem. Modern AI systems, and especially the ones receiving the greatest attention, so called Deep Learning systems, are based on Artificial Neural Networks (ANNs). A characteristic of ANNs is that after the ANN has been trained with data sets (which may be very large, so called “big data” sets – which itself poses another problem for verification), any attempt to examine the internal structure of the ANN in order to understand why and how the ANN makes a particular decision is impossible. The decision making process of an ANN is not transparent.
• The problem of verification and validation of systems that learn may not be intractable, but is the subject of current research, see for example work on verification and validation of autonomous systems. The black box problem may be intractable for ANNs, but could be avoided by using algorithmic approaches to AI (i.e. that do not use ANNs).

Recommendations

13. It is vital that we address public fears around robotics and artificial intelligence, through renewed public engagement and consultation.

14. Work is required to identify the kind of governance framework(s) and regulatory bodies needed to support Robotics and Artificial Intelligence in the UK. A group should be set up and charged with this work; perhaps a Royal Commission, as recently suggested by Tom Watson MP.