So thank you so much for inviting me to this. And thank you, Sandra, for giving great introduction of of our research programme.
So what I'm going to talk about a bit is I'm going to talk about one of my most recent pieces of work,
which I think speaks to the question of the relationship between law and ethics in the space of air and particularly talks about the the frameworks,
the initiatives that we now have. Over 100 of that are in some way trying to define the right sort of high level concepts or principles or
values or tenets to in some way guide the development of the government's ban on the use of AI to do.
The talk is going to be based on this paper, which just came out about a week ago,
where I look at the role the principles can and perhaps should play in the governance of A.I. of ethically.
I know my paper, despite having come out a week ago, is apparently already out of date.
I thought we only had eighty four initiatives from across the world,
but we have over 100 now and I hope this gets across the gravity of the situation.
And I suppose my my main concern is that if we have all these initiatives,
you're essentially creating a market where developers can pick and choose the set of principles that works best for them.
Chris Russell was joking the other day that he said, Here are my principles and if you don't like them, I have a bunch of others.
But to me, the risk there is, it gives the impression that there's sort of one way to do ethics that you have a high level
set of principles that you were then going to specify into a set of practical requirements.
And unsurprisingly, you should expect that if you have both lots of different sets principles, but also leave it up to say,
individual development teams or individual companies to choose how to specify those principles on the ground,
you're going to get requirements that don't match with each other, requirements that may be contradictory.
And essentially, you can end up in a situation of extreme moral relativism.
And to me, that that that thought that sort of ethics or at least ethical frameworks are there as something to let's
see workplace regulation or at least self-regulation can be seen as a way to replace hard regulation.
And that's me sort of does a disservice to the actual value that ethics can have and in particular,
the value, the ethics and the law when working together in a good way can have.
So what I'm interested in is basically, how can we make these ethics frameworks actually work within a,
you know, an approach where we're open to hard regulation?
Now, I'm happy that this has come up already, but it's just to say there is a clear connexion between ethics and medical ethics.
So I don't have to make the case. That's it. So thank you. A number of people mentioned, actually,
but just to say that there was some work done recently as papers done recently that was trying to look
for some sort of consensus across all these different different frameworks and initiatives that we have.
And what in particular,
this piece of work from the Air People project and also it was adopted by the High-Level Expert Group on Artificial Intelligence,
is that there's a set of principles and very closely mimic the classic principles of medical ethics.
And that's really interesting because I think actually looking at medical ethics and looking how A.I. development compares to it can tell you a
lot about whether we should expect this in a principal form of self-governance to work in a similar way in AI development as it does in medicine.
And it's not to say that medical ethics is without its values, and that principled approach is going to solve everything.
It's just to say it's definitely a case where the use of principles for ethical governance, for ethical decision making is very clear.
It's very prominent, and it has had impact in practise.
So I'm going to do it in the remainder of my few minutes is just to look at those two professions a little bit closer and see, well,
how exactly does A.I. development compare to this profession where we've seen a principled approach emerge and have some success?
And so there's four different characteristics I want to look at here. The first is the existence of common ends.
And what I mean by that is that medicine has doctors have fiduciary duties towards their patients.
The practise is broadly guided by a common set of aims, which is to benefit the health and well-being of the patient.
And of course, we will disagree about how to do that best in practise,
at the very least talking about, say, public interest versus the interests of individual patient.
But there is this sort of commonality. There is this common ground from which ethical decision making can actually proceed.
And that is reflected in the fact that you have very strong fiduciary duties between professionals and patients.
What that allows for is basically. Co-operative approach, difficult decision making to specifying these principles,
and I'm not sure that that level of cooperation can be taken for granted in the space of aid development.
At the very least, if you're talking about privately developed the guy,
the initial fiduciary duties owed by the development team will be to the shareholders of the company,
rather than the users of the people affected by the system.
And so my concern is if you don't have this sort of common grounding of the direction we're all travelling,
I'm not sure that you actually can have that,
that you're going to end up with ethical decision making that's fundamentally competitive rather than co-operative.
And clearly, that's that's not something that's conducive to finding an appropriate balance between different interests in practise.
The second characteristic want to look at is the role of professional history,
and this is just to say that medicine has obviously an impression for a very long time.
We have codes of conduct. We have accounts of what it means to be a good doctor.
These are captured in things like credit growth or more recently, became a code of medical ethics.
These are documents that have been revised over time. The very long standing, the very detailed they give opinions on, you know,
particular types of interventions and the fact that they have been sort of tested over time and revised
is one of the reasons that they continue to actually be useful in day-to-day professional practise.
Now, if you compare that to the state of development, I'm going to use software engineering here as the analogue to to AI development.
We do have professional bodies see ACM in the I believe it's been two of the biggest ones and we do have codes of ethics.
But in comparison to medicine, they're the relatively short comparison, relatively abstract.
The ACM one was revised recently, but still remains comparatively abstract when compared to, say, the inmate code of Ethics.
And there's research on the recent research that suggests that the codes of ethics
actually have very little influence on day to day decision making of engineers,
which is clearly a problem because if you hadn't have a code of ethics but isn't shown
to be particularly effective in the sense of influencing the behaviour of engineers,
then you have to question what is the actual value?
The third characteristic I want to briefly touch on is just the methods that we have for translating principles into practise.
The fundamental problem that we have here in the air it's frameworks is that they're
they're based on or they rely on what can be called essentially contested concepts,
essentially very abstract concepts that can have lots of different meanings in practise.
I mean, if I asked you if I took a survey of this room and who thinks that air system should treat people fairly,
I imagine pretty much everybody would raise their hand.
And yet everybody may have a completely different sense of what fairness would actually mean in practise.
And the point is that those different means of fairness can be rationally held.
They can be genuine. They can be defended. We shouldn't expect a single correct meaning of any of these terms.
The problem that you have is that we've reached consensus on what the correct.
Essentially contested concepts are. We've reached this high level consensus.
And to me,
that doesn't actually reflect any sort of true consensus emerges is a way to mask sort of really important normative and political disagreements.
The framework we reached the framework. We certainly don't agree to what it means in practise.
And of course, the other problem is that those sorts of concepts don't translate automatically into practical requirements.
That is a very difficult process. Medicine has things like professional societies and boards, ethics review committees,
accreditation and licencing schemes, pure self-governance standards.
All these things help you actually do that translation in practise. Software engineering does have some of these things, but it's lacking.
It's lacking mechanisms that are of similar stature, similar importance.
I think one of the reasons for that is that the profession would not be legally
recognised in legally recognised as a profession in the same way that medicine is.
What I mean by that is doctors require a licence to practise software engineers, in some cases in limited contexts.
Do you need a licence to practise? But it's in no way of the same importance or the same sort of same coverage as as medical licences.
And so this lack of sort of legal recognition of the profession is a serious problem because ethics tends
to professional ethics at least really has teeth when it actually has legal mechanisms to back it up.
When doing something unethical in your day to day behaviour as a as a professional
could actually lead to you saying losing the ability to practise your profession.
And so just to conclude here, I think we have a number of sort of legal gaps within escalating AI.
One is really important ones that there is not this legal recognition of AI development as professions and a lot of the initiatives
we have are based on human rights frameworks or other sorts of frameworks are not directly legally binding in the same way and say,
Gee, DPR would be. And so to move forward, I think we can do a couple of things.
One is to start thinking about air ethics more in the sense of a business or organisational ethics and less as a professional ethics.
Both sides are important, but I think there's too much emphasis placed on individuals doing wrong things, software engineering,
individual developers doing wrong things and less about the same business model that they're
working within or the organisational practises themselves being unethical in some way.
We had a chance to do that with the High-Level Expert Group.
There were red lines initially supposed to be draughted to basically set out types of A.I. that should not be developed in Europe.
In the end, those red lines were taken out. To me, these would have been a very strong signal of AI.
Ethics is also business ethics. And then just finally, I think we may need to revisit the idea of licencing developers of high risk A.I. applications.
And we I think more than anything,
we just need to develop much stronger empirical evidence base that's based on case studies on specific specific ethical challenges.
So we can really start to understand how we disagree and agree with each other
in practise about what these different concepts and principles are in there.
Thank you very much. Thanks for.