"How We're Predicting AI — or Failing to"

lukeprog

The new paper by Stuart Armstrong (FHI) and Kaj Sotala (SI) has now been published (PDF) as part of the Beyond AI conference proceedings. Some of these results were previously discussed here. The original predictions data are available here.

Abstract:

This paper will look at the various predictions that have been made about AI and propose decomposition schemas for analysing them. It will propose a variety of theoretical tools for analysing, judging and improving these predictions. Focusing speciﬁcally on timeline predictions (dates given by which we should expect the creation of AI), it will show that there are strong theoretical grounds to expect predictions to be quite poor in this area. Using a database of 95 AI timeline predictions, it will show that these expectations are born out in practice: expert predictions contradict each other considerably, and are indistinguishable from non-expert predictions and past failed predictions. Predictions that AI lie 15 to 25 years in the future are the most common, from experts and non-experts alike.

Abstract:

This paper will look at the various predictions that have been made about AI and propose decomposition schemas for analysing them. It will propose a variety of theoretical tools for analysing, judging and improving these predictions. Focusing speciﬁcally on timeline predictions (dates given by which we should expect the creation of AI), it will show that there are strong theoretical grounds to expect predictions to be quite poor in this area. Using a database of 95 AI timeline predictions, it will show that these expectations are born out in practice: expert predictions contradict each other considerably, and are indistinguishable from non-expert predictions and past failed predictions. Predictions that AI lie 15 to 25 years in the future are the most common, from experts and non-experts alike.

I predict that the search for AI will continue to live up to it's proud tradition of failing to produce a viable AI for the indefinite future. Since the Chinese Room argument does refute the strong AI hypothesis no AI will be possible on current hardware. An artificial brain that duplicates the causal functioning of an organic brain is necessary before an AI can be constructed.

I further predict that AI researchers will continue to predict immanent AI in direct proportion to research grant dollars they are able to attract. Corollary: A stable nuclear fusion reactor will be built before a truly conscious artificial mind is. Neither of which will happen in the lifetime of anyone reading this.

Since the Chinese Room argument does refute the strong AI hypothesis no AI will be possible on current hardware. An artificial brain that duplicates the causal functioning of an organic brain is necessary before an AI can be constructed.

There's a lot of objections to the Chinese room, but in this context, the primary issue is that the Chinese room doesn't matter: Even if the AI isn't conscious in some deep philosophical sense, it has all the same results then for humans the dangers and promises of strong AI are identical.

I further predict that AI res

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"How We're Predicting AI — or Failing to"

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"How We're Predicting AI — or Failing to"

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