We're very likely to give them long term goals. And as I explain here: https://www.lesswrong.com/posts/x8bK7ohAHzMMchsaC/what-is-autonomy-and-how-does-it-lead-to-greater-risk-from lots of things people are likely to request seem near certain to lead to complex and autonomous systems.
(1) have goals, (2) which will be long term, (
In many cases, you also need incorrigibility, and stability under improvement.
The key is that if AGI's are smarter than humans those organizations run AGIs that have long-term goals will outperform organizations that mix humans with long-term goals along with AGIs that are only capable to pursue short-term goals.
One long-term goal that many AGIs are going to have is to create training data to make the AGI more effective. Training data is good when it makes the AGI more performant over a long timeframe.
AGIs that run that way are going to outperform AGIs where humans oversee all the training data.
The problem is the way we train AIs. We ALWAYS minimize error and optimize towards a limit. If I train an AI to take a bite out of an apple, what I am really doing is showing it thousands of example situations and rewarding it for acting in those situations where it improves the probability that it eats the apple.
Now let's say it goes super intelligent. It doesn't just eat one apple and say "cool, I am done - time to shut down." No, we taught it to optimize the situation as to improve the probability that it eats an apple. For lack of better words, it feels "pleasure" in optimizing situations towards taking a bite out of an apple.
Once the probability of eating an apple reaches 100%, it will eventually drop as the apple is eaten, then the AI will once again start optimizing towards eating another apple.
It will try to set up situations where it eats apples for all eternity. (Assuming superintelligence does not result in some type of goal enlightenment.)
Ok, ok, you say. Well, we will just hard program it to turn off once it reaches a certain probability of meeting its goal. Good idea. Once it reaches 99.9% probability of taking a bite out of an apple. We automatically turn it off. That will probably work for an apple eating AI.
But what if our goal is more complicated? (Like fix climate change). Well, the AI may reach superintelligence before finishing the goal and decide it doesn't want to be shut down. Good luck stopping it.
Short and long term goals have different implications regarding instrumental convergence . If I have the goal of immediately taking a bite of an apple that is in my hand right now, I don't need to gather resources or consider strategies, I can just do it. On the other hand, imagine I have an apple in my hand and I want to take a bite of it in a trillion years. I need to (define 'me', 'apple', and 'bite'; and) secure maximum resources, to allow the apple and I to survive that long in the face of nature, competitors and entropy. Thus, I instrumentally converge to throwing everything at universal takeover - except the basic necessities crucial to my goal.
Some of the cruxes that high P(Doom) rests on are that (sufficiently) General Intelligences will (1) have goals, (2) which will be long term, (3) and thus will instrumentally converge to wanting resources, (4) which are easiest to get with humans (and other AIs they might build) out of the way, (5) so when they can get away with it they'll do away with humans.
So if we make General Intelligences with short term goals perhaps we don't need to fear AI apocalypse.
Assuming the first crux, why the second? That is, assuming GIs will have goals, what are the best reasons to think that such intelligences will by default have long term goals (as opposed to short term goals like "quickly give a good answer to the question I was just asked")?