In response to the debate
initiated by Ruairi concerning the fear of drones trying to take over the
world, I thought it could be interesting to write a post about artificial
intelligence and ways of simulating decision making. People usually think that
drones can actually think and pick their targets without any human
interventions. Despite the lack of information about the design of those drones
due to their confidential aspect, the advances in neural networks show that we
are still very far from creating machines which can embed large scale neural
network to treat a visual input (e.g. Google X’s neural network), so we can
easily guess that drones do not analyse and “understand” all the input data by
themselves.
Therefore, we can also suggest
that drones are only able to treat the input data to fly to a given location
but there is no proper decision making involved. Drones are simple
deterministic systems. Moreover, even if drones were implemented with large
scale neural networks, their reactions could be assessed during the testing
phase so no new behaviours could emerge from encountering new stimuli. Of
course, this would mean that their systems wouldn’t be able to learn anything
but it is the only safe way to keep machines predictable and so, under control.
The discussion about drones
reminds me of a paper that I read a while ago. Written by Matthijs Pontier and
Johan Hoorn, this paper presents a review of previous research in ethical
decision making in AI, and then develops a potential way of designing an
implementation of ethical decision making. Of course, their concept is not
perfect and can easily attract criticisms, but it is a very good start. Most of
the existing systems learn to resolve an ethical problem by looking at previously
similar problems, thanks to web-based technology. That is to say, the program
will look for information among millions of people instead of only getting
information from the developer. Some systems currently use neural networks to
be more flexible and learn from previous problems to treat new kind of issues.
The ethical decision making model
designed by Pontier and Hoorn is based on three factors which are autonomy, non-maleficence
and beneficence. The autonomy score defines the level of constraints applied
(by people, injuries…) to the subject and is more important than the
non-maleficence factor which is itself more important than the beneficence
score. For each problem, a group of solutions is presented with the values of
the three factors and the solution with the best overall score will represent the
morally superior path to engage in in order to solve the issue.
To check the reliability of the
moral reasoner, it was confronted with several ethical dilemmas in which a health
care worker has to help a patient to make a decision. For example, in a case
where a patient (=subject) has cancer and decides not to be treated with
chemotherapy, the health care worker (=contraint) can decide whether to accept
the patient’s decision or try to influence him into accepting the treatment. While
accepting the decision will be considered as not beneficent and quite maleficent
because the patient would die, the fact of influencing their decision will
reduce their autonomy in the decision making process. For this dilemma, it is
slightly better to try to make the patient change their decision, even though
the decision would not be fully independent. (All the simulations are fully
detailed with values in the paper.)
One of the quotes that I will
retain from this paper is that : “AI makes philosophy honest”. That is to say
that the way cognitive phenomena are decomposed in order to make them
computable allows us to have a better understanding of all the components of
reasoning. Then, it may seem strange to try to human moral reasoning when we
know all too well that humans are far from being angels. On the other hand,
when we consider the fact that machines are more rational than human beings, we
can expect machines to behave ethically better than human beings from which their
behaviour is based on.
If morality can be boiled down to a formula or an algorithm then yes robots would be the ultimate arbiters of justice, free from any bias or prejudice whatsoever. You make a convincing argument but we know that right and wrong are not clear concepts. This is why different legal systems around the world rely to varying degrees on the laws themselves, on juries, on elders or just on someone with a funny wig making their own call. I wonder what the robot would decide on the dilemma of Jim and the Indians http://www.e-mago.co.il/e-magazine/jatiamq-kgng.html
ReplyDeleteI think that's why the maleficence score is more important than the beneficent score. Basically, the more people it can save, the more likely it will proceed to the sacrifice... Sure, it's a cold and straightforward way to make a decision but it is honest and rational.
DeleteThis work seems to borrow heavily from this:
ReplyDeletehttp://ieet.org/archive/IEEE-Anderson.pdf