1. I agree there is no consensus on the meaning of intelligence, and this is probably because "intelligence" isn't one thing but many things. In humans these things are often correlated but only weakly.

2. As Scott argues, IQ gives an okay measure of some things under the intelligence umbrella. However, the economic impact of an AI will be measured entirely by job performance. And the correlation between IQ-like intelligence and job competency is pretty clearly already broken by existing AI expert systems. We may be able to get a better understanding of the human correlations by doing experiments.

3. Understanding what IQ measures and how it is related to competencies I expect with ~90% confidence will be a human coincidence. Since we don't have a notion of intelligence, IQ is a flawed measure only applicable to humans, and the connection between what IQ attempts to measure and the thing we care about is only present in humans, I don't expect models of IQ to improve our ability to forecast AI.

4. Even if I agreed that IQ research measured a coherent notion of intelligence and that there was a strong metaphor between human IQ and machine intelligence that would give us better models of takeoff and help with strategy, this does not imply that funding IQ research is an effective tactic unless there is a community of researchers with well aligned motivations capable of doing research aligned with these interests and that they expect results to be strategicaly useful in a foreseeable time frame. This may be true but it's an important part of the argument that should be presented.

And some specific comments:

If intelligence is not correlated with job performance or correlated only up to a certain point of performance, super intelligence's won't be super at job performance and they won't have as huge an impact as we might have expected.

If intelligence is not correlated with job performance we should not expect economically disruptive AI to be "superintelligent." This already seems clear, since AI that caused various Flash Crashes was not superintelligent. By the same analogy, this may be either convenient (for example, very corrigible) or inconvenient (for example, can commit grave errors without understanding them) for safety purposes.

It is unlikely to speed up the creation of intelligence directly as it is not working on a constructive view of intelligence but a descriptive one. It will point in a direction of research though

(warning, epistemic status: hot take) I think one of the major barriers in AI right now is a lack of clear functional analogies to existing intelligence systems. Building AI systems out of various pieces is very common (AlphaGo and self driving cars both do this) and some of the most exciting recent advances like use of convnets in computer vision are based on explicit analogies. I would suspect that good descriptive models of human intelligence would be very powerful tools to advance AI.

My overall takeaway here is:

1. Having better descriptive models of human intelligence would be valuable and interesting, though possibly would carry some dangers. This does not mean EAs should fund it.

2. Being able to constrain takeoff scenarios would be very valuable for AI safety research. This does not mean there's a connection between takeoff scenarios and IQ.