And I'd say that even if someone had a correct general idea how to build an AGI (an assumption that by itself beggars belief given the current state of the relevant science), developing an actual working implementation with today's software tools and methodologies would be sort of like trying to build a working airplane with Neolithic tools.
This is the sort of sentiment that has people predict that AGI will be built in 300 years, because "300 years" is how difficult the problem feels like. There is a lot of uncertainty about what it takes to build an AGI, and it would be wrong to be confident one way or the other just how difficult that's going to be, or what tools are necessary.
We understand both airplanes and Neolithic tools, but we don't understand AGI design. Difficulty in basic understanding doesn't straightforwardly translate into the difficulty of solution.
We understand both airplanes and Neolithic tools, but we don't understand AGI design. Difficulty in basic understanding doesn't straightforwardly translate into the difficulty of solution.
That is true, but a project like OpenCog can succeed only if: (1) there exists an AGI program simple enough (in terms of both size and messiness) to be doable with today's software technology, and (2) people running the project have the right idea how to build it. I find both these assumptions improbable, especially the latter, and their conjunction vanishingly unlikel...
Artificial general intelligence researcher Ben Goertzel answered my question on charitable giving and gave his permission to publish it here. I think the opinion of highly educated experts who have read most of the available material is important to estimate the public and academic perception of risks from AI and the effectiveness with which the risks are communicated by LessWrong and the SIAI.
Alexander Kruel asked:
Ben Goertzel replied:
What can one learn from this?
I'm planning to contact and ask various experts, who are aware of risks from AI, the same question.