Practical tools and agents

That is meant to be informative to those wondering what Holden was talking about. I do not know what do you mean by 'some substance'.

edit: Actually, okay, I should be less negative. It probably is a case of accidental/honest self deception here, and the technobabbling arose by honest attempt to best communicate the intuitions. You approach problem from direction - how do we make a safe oracle out of some AGI model that runs in your imagination reusing the animalism to predict it. Well you can't. That's quite true! However, the actual software is using branches and loops and arithmetic, it's not run on animalism module of your brain, it's run on computer. There's this utility function, and there's the solver which finds maximum of it (which it just does, it's not trying to maximize yet another utility ad infinitum, don't model it using animalism please), and together they can work like animalist model, but the solver does NOT work as animalist model does.

edit: apparently animalism is not exactly the word I want. The point is, we have a module in our brain made for predicting other agents of a very specific type (mammals) and it is a source of some of the intuitions about the AI.

former post:

Ultimately, I figured out what is going on here. Eliezer and Luke are two rather smart technobabblers. That really is all to it. Not explaining anything about the technobabble. Not worth it. The technobabble is what results when one is thinking in terms of communication-level concepts rather than in terms of reasoning-level concepts, within a technical field. The technobabble can and has been successfully published in peer reviewed journals ( Bogdanov affair ) and, sadly, can even be used to acquire a PhD.

The Oracle AI as defined here is another thing defined in terms of the 'utility' as known on LW and has nothing to do with the solver component of the agents as currently implemented.

The bit about predictor having implicit goal to make world match predictions is utter and complete bullshit not even worth addressing. It arises from thinking in terms of communication level concepts such as 'should' and 'want', which can be used to talk about AI but can not be used to reason about AI.

This one. The argument on LW goes as "you can't define distinction between tool and agent, so we're right".

Now, to those with knowledge of the field, it is akin to some supposedly engineer claiming you can't define distinction between a bolt and a screw, as a way to defy the statement that "you can avoid splitting the brittle wood if you drill a hole and use a bolt, rather than use a screw", which was a rebuttal to "a threaded fastener would split the brittle wood piece". The only things it demonstrates is ignorance, incompetence, and lack of work towards actually fulfilling the stated mission.

For this 'oracle' link, it clearly illustrates the mechanism of generation of strings employed to talk about the AI risks. You start with the scary idea, then you progress to necessity for each type of AI to be shown scary, then you proceed to each subtype, then you make more and more detailed strings designed to approximate the strings that result from entirely different process of starting from basics (and study of the field) and proceeding upwards to risk estimate.

That task is aided by fact that it is impossible to define a provably safe AI in English (or in technobabble) due to vagueness/ambiguousity, and due to fact that language predominantly attributes real world desires when describing anything that seems animate. That is, when you have a system that takes in sequences and generates functions that approximate the sequences (thus allowing prediction of next element in sequences, without over-training on noise), you can describe it as predictor in English and now you got 'implicit' goal of changing the world to match the prediction. Followed by "everyone give us money or it is going to kill us all, we're the only ones whom understand this implied desire! [everyone else's more wrong because we call ourselves less wrong seem to be implied]". Speaking of which use of language is a powerful irrationality technique.

Meanwhile, in the practice, such stuff is not only not implicit, it is incredibly difficult to implement even if you wanted to implement it. Ultimately, many of the 'implied' qualities that are very hard to avoid in English descriptions of AI are, also, incredibly difficult to introduce when programming. We have predictor-type algorithms, which can be strongly superhuman if given enough computing power - and none of them would exhibit a trace of 'implicit' desire to change the world.

There's the notion that anything which doesn't 'understand' your implied, is not powerful enough (not powerful enough for what?), that's just rationalization, and is not otherwise substantiated or even defined. Or even relevant. Let's make example in other field. Clearly, any space propulsion we know is possible, is not powerful enough to get to faster than speed of light. Very true. Shouldn't be used to imply that we'll have faster than light travel.