I thought another significant difference was that "Ethics" doesn't even imply getting as far as "How do I?".
No, Machine Ethics is the field concerned with exactly the question of how to program ethical machines. For example, Arkin's Governing Lethal Behavior in Autonomous Robots is a work in the field of Machine Ethics.
In principle, a philosopher could try to work in Machine Ethics and only do speculative work on, for example, whether it's good to have robots that like torture. But inasmuch as that's a real question, it's relevant to the practical project.
I was under the impression that Machine Ethics is mostly being researched by Computer Science experts and AI or Neuro-something specialists in particular.
My prior for someone already doing research in IT concentrating their research efforts into "How do I code something that does X" is much higher than for someone doing research in, say, propagation of memes in animal populations or intergalactic lensing distortions (Dark Matter! *shivers*).
The project of Friendly AI would benefit from being approached in a much more down-to-earth way. Discourse about the subject seems to be dominated by a set of possibilities which are given far too much credence:
Add up all of that, and you have a great recipe for enjoyable irrelevance. Negate every single one of those ideas, and you have an alternative set of working assumptions that are still consistent with the idea that Friendly AI matters, and which are much more suited to practical success:
The simplest reason to care about Friendly AI is that we are going to be coexisting with AI, and so we should want it to be something we can live with. I don't see that anything important would be lost by strongly foregrounding the second set of assumptions, and treating the first set of possibilities just as possibilities, rather than as the working hypothesis about reality.
[Earlier posts on related themes: practical FAI, FAI without "outsourcing".]