[...] SIAI's Scary Idea goes way beyond the mere statement that there are risks as well as benefits associated with advanced AGI, and that AGI is a potential existential risk.
[...] Although an intense interest in rationalism is one of the hallmarks of the SIAI community, still I have not yet seen a clear logical argument for the Scary Idea laid out anywhere. (If I'm wrong, please send me the link, and I'll revise this post accordingly. Be aware that I've already at least skimmed everything Eliezer Yudkowsky has written on related topics.)
So if one wants a clear argument for the Scary Idea, one basically has to construct it oneself.
[...] If you put the above points all together, you come up with a heuristic argument for the Scary Idea. Roughly, the argument goes something like: If someone builds an advanced AGI without a provably Friendly architecture, probably it will have a hard takeoff, and then probably this will lead to a superhuman AGI system with an architecture drawn from the vast majority of mind-architectures that are not sufficiently harmonious with the complex, fragile human value system to make humans happy and keep humans around.
The line of argument makes sense, if you accept the premises.
But, I don't.
Ben Goertzel: The Singularity Institute's Scary Idea (and Why I Don't Buy It), October 29 2010. Thanks to XiXiDu for the pointer.
The usefulness of testing is beside the point. The argument is that testing would be dangerous.
By "testing" I meant "running the code to see if it works", which includes unit testing individual components, integration or functional testing on the program as a whole, or the simple measure of running the program and seeing if it does what it's supposed to. By "doing test runs" I meant doing either of the latter two.
I would never ship, or trust in production, a program that had only been subjected to unit tests. This poses a problem for AI researchers, because while unit testing a potentially-FOOMing AI might well be safe (and would certainly be helpful in development), testing the whole thing at once would not be.
I think EY's the original person behind a lot of this, but now the main visible proponents seem to be SIAI. Here's a link to the big ol' document they wrote about FAI.
On the specific issue of having to formally prove friendliness before launching an AI, I can't find anything specific in there at the moment. Perhaps that notion came from elsewhere? I'm not sure; but, it seems straightforward to me from the premises of the argument (AGI might FOOM, we want to make sure it FOOMs into something Friendly, we cannot risk running the AGI unless we know it will) that you'd have to have some way of showing that an AGI codebase is Friendly without running it, and the only other way I can think of would be to apply a rigorous proof.
Life is dangerous: the issue is surely whether testing is more dangerous than not testing.
It seems to me that a likely outcome of pursuing a strategy involving searching for a proof is that - while you are searching for it - some other team makes a machine intelligence that works - and suddenly whether your machine is "friendly" - or not - becomes totally irrelevant.
I think bashing testing makes no sense. People are interested in proving what they can about machines - in the hope of making them ... (read more)