As a starting point, a system of AI morality would have to be deontological, because for it to be something you can implement as a program, it would have to be a clear cut set of rules, as opposed to a utility measure.
Utilitarian ethics, even when applied to human situations, run into the difficulty of how to practically measure the utility of each situation. The problem of calculating such utilities would be impossible to implement in an AI system: It would be difficult to for an AI to have knowledge beforehand of all the variables that should go into such a calculation, and even if it did, such utility maximization/optimization problems are computationally very costly. This would make them impractical in real world situations. Using approximations or meta-heuristics to calculate probable values would be dangerous.
On the other hand, straightforward deontological ethical rules would be relatively simple to implement, since the rules are categorical and would not be context dependent the way utilitarian rules are.
Most importantly, in a utilitarian system, utilities would have to be assigned numerical values. To see why this is dangerous, consider the following situation:
A utilitarian AI is faced with the scenario where it can increase the happiness of 1000 000 people each by 1%, but only at the cost of imprisoning an innocent orphan child for life, therefore reducing the happiness of that child by 100%. An AI using purely quantitative measures of utility is very likely to fall into such a scenario. The only way to avoid such a scenario is introduce some hard non-quantitative rules: "You can increase the happiness of everyone, but only as long as nobody is killed, no innocent is harmed, nobody is enslaved, etc..." - so deontological ethics are unavoidable.
An example of AI ethics, taken from Sci-Fi, not philosophy are Asimov's 3 laws of robotics. Although Asimov doesn't mention Kant or the word deontological anywhere in his works, it is clear from their formulation that they are Kantian in spirit, in the sense that they are universal and context independent.
Postscript added in response to nir's comment and to some parts of his answer:
- It is true that neural networks and other machine learning algorithms learn from interacting with environment, but their purpose is to solve problems for which we do not know what the explicit rules are. Presumably in the context of machine ethics, we already know what the rules are, we are just trying to get an AI to follow them.
- Machine learning algorithms such as neural networks give probabilistic answers. They can learn from past data, but their prediction/recognition rates are never 100% accurate. In many real life applications, a 95% accuracy is considered a very good result. This might be good for some business applications, but consider a military system that manages to target enemy combatants 95% of the time, but accidentally targets innocent civilians 5% of the time. Would this be acceptable?
- Machine learning applications have already been shown to be prone to gender and racial bias, see this article for examples.
(2) and (3) are why I mentioned above in my initial answer that "Using approximations or meta-heuristics to calculate probable values would be dangerous."
- The technical problem here is that machine algorithms are already inherently performing utilitarian type calculations. Algorithms like Neural Nets, Random Forests, Supports Vector Machines, etc..all base learn how to solve problems from example by minimizing an error or risk metric, or maximizing a profit metric etc...to make them ethical, we would need to counter-balance that with some rule based considerations, not muddy the waters by making them even more utilitarian.
- In response to Nir's point number (2) - In an ideal world, I agree, such machines should remain nothing but sophisticated tools, providing people with objective facts while leaving the ultimate decision making to humans. In real life, complicated software systems are already making decisions on their own, for example approving loans and credit applications without human intervention, filtering job applicants and deciding which resume get seen by the hiring manager, Google will soon have self-driving cars, etc...the issue is not whether such system should be treated as moral agents in terms of crime and punishment, but the fact that such systems are already making decisions that have an ethical impact on people's lives, so how should such a decision making process be regulated.