A putative new idea for AI control; index here.
Part of the problem with a reduced impact AI is that it will, by definition, only have a reduced impact.
Some of the designs try and get around the problem by allowing a special "output channel" on which impact can be large. But that feels like cheating. Here is a design that accomplishes the same without using that kind of hack.
Imagine there is an asteroid that will hit the Earth, and we have a laser that could destroy it. But we need to aim the laser properly, so need coordinates. There is a reduced impact AI that is motivated to give the coordinates correctly, but also motivated to have reduced impact - and saving the planet from an asteroid with certainty is not reduced impact.
Now imagine that instead there are two AIs, X and Y. By abuse of notation, let ¬X refer to the event that the output signal from X is scrambled away from the the original output.
Then we ask X to give us the x-coordinates for the laser, under the assumption of ¬Y (that AI Y's signal will be scrambled). Similarly, we Y to give us the y-coordinates of the laser, under the assumption ¬X.
Then X will reason "since ¬Y, the laser will certainly miss its target, as the y-coordinates will be wrong. Therefore it is reduced impact to output the correct x-coordinates, so I shall." Similarly, Y will output the right y-coordinates, the laser will fire and destroy the asteroid, having a huge impact, hooray!
The approach is not fully general yet, because we can have "subagent problems". X could create an agent that behave nicely given ¬Y (the assumption it was given), but completely crazily given Y (the reality). But it shows how we could get high impact from slight tweaks to reduced impact.
EDIT: For those worried about lying to the AIs, do recall http://lesswrong.com/r/discussion/lw/lyh/utility_vs_probability_idea_synthesis/ and http://lesswrong.com/lw/ltf/false_thermodynamic_miracles/
I read those two, but I don't see what this idea contributes to AI control on top of those ideas. If you can get the AI to act like it believes what you want it to, in spite of evidence, then there's no need to try the tricks with two coordinates. Conversely, if you cannot then you won't fool it either with telling it that there's a second coordinate involved. Why is it useful to control an AI through this splitting of information, if we already have the false miracles? Or in case the miracles fail, how do you prevent an AI from seeing right through this scheme? I think that in the latter case you are trying nothing more than to outsmart an AI here...
The approach I'm trying to get is to be able to make the AI do stuff without having to define hard concepts. "Deflect the meteor but without having undue impact on the world" is a hard concept.
"reduced impact" seems easier, and "false belief" is much easier. It seems we can combine the two in this way to get something we want without needing to define it.