Indeed! And what about the 7th phase shift? I must be missing something here. We’re pointing to just two particular transitions in all of human history. I fear we’re calling them “phase shifts” to convince ourselves that there is a simple underlying phenomenon which has law-ordained “phases”. How can we assume that there will be a coherent series of N>2 such “phase shifts”? How can we assume that they will follow some simple mathematical function with just a handful of parameters?
I guess this makes me even more of a singularity skeptic than Hanson. He marshals powerful economic arguments against naive singularitarianism. But then he forecasts a similarly epochal transition to whole-brain emulations, yet seems worried that it needs more support than its own inside analysis provides. So goes back to an outside extrapolation from past data points a la Kurzweil, but he extrapolates from only 2 points, and says the resulting curve can’t really tell us anything beyond the 3rd point. By contrast, Kurzweil marshals multiple technological trends each with dozens of past data points. If we call that naive, then how confidently can we extrapolate along a single trend with only 2 prior data points?
That doesn’t feel like a curve to me. It just feels like a prediction of a 3rd transition that will have similar significance to two previous transitions. But being similar in significance is not really evidence of being similar in explainability by some simple underlying lawlike mechanism. The word choice of “phase” seems like sleight of hand here. If instead we talk of “epochs” or “periods”, we’re less likely to bias ourselves towards a phantom unifying phenomenology of what could just be three not-very-causally-related transitions.
My critique here seems obvious and unoriginal, and the people it’s aimed at are very well-informed and thoughtful. So I apologize if this has been addressed elsewhere already. What am I missing?
Indeed! And what about the 7th phase shift? I must be missing something here. We’re pointing to just two particular transitions in all of human history. I fear we’re calling them “phase shifts” to convince ourselves that there is a simple underlying phenomenon which has law-ordained “phases”. How can we assume that there will be a coherent series of N>2 such “phase shifts”? How can we assume that they will follow some simple mathematical function with just a handful of parameters?
In general you can’t assume anything like this, but you also can’t assume that the present growth rate will continue forever (or anything else, really) for similar reasons. The point is that to make forecasts about future economic transitions you need some kind of model, and the model in this post is meant to provide the outside view on how often such transitions have occured.
The less controversial version of this, namely people fitting a production function such as f(K,L)=AKαL1−α to the GDP of different countries with L,K,A denoting labor stock, capital stock and total factor productivity respectively, and then assuming some law of motion like Δlog(At+1)=(μ−σ2/2)+σεt is the basis of a whole lot of macroeconomic modeling . For example, the entirety of the real business cycle school probably falls into this category. In my view this is much less plausible and in fact this model is immediately refuted by the data since μ has changed so much over the span of thousands of years.
If you don’t like this real business cycle inspired model, what do you use instead to make forecasts? Clearly one kind of model you should keep in mind is the phase transition model, and it achieves a much better fit with data at the expense of only two or three parameters over the real business cycle model. I’m not saying you should treat the model’s forecasts as gospel (and I don’t, my forecasts are not identical to what the model outputs) but it’s definitely valuable to see what this type of model has to say. The same goes for Roodman’s stochastic hyperbolic growth model.
I guess this makes me even more of a singularity skeptic than Hanson. He marshals powerful economic arguments against naive singularitarianism. But then he forecasts a similarly epochal transition to whole-brain emulations, yet seems worried that it needs more support than its own inside analysis provides. So goes back to an outside extrapolation from past data points a la Kurzweil, but he extrapolates from only 2 points, and says the resulting curve can’t really tell us anything beyond the 3rd point. By contrast, Kurzweil marshals multiple technological trends each with dozens of past data points. If we call that naive, then how confidently can we extrapolate along a single trend with only 2 prior data points?
Kurzweil’s marshaled trends in individual technologies are highly unreliable because they don’t tell us anything about economic transformation directly, and the supposed connections of his measures to such a transformation are quite tenuous. In my view Hanson’s paper has a poor methodology and model specification (something I hope to remedy at some point in the future) but his general approach is much more justified because it looks specifically at examples of past economic transitions.
To give another remarkable example, consider abiogenesis, which is likely the most significant kind of transition that happens in the history of the universe. If you consider all the transitions of this form that have happened before humans even came to exist, I think the argument that phase transitions aren’t that unusual is compelling.
That doesn’t feel like a curve to me. It just feels like a prediction of a 3rd transition that will have similar significance to two previous transitions. But being similar in significance is not really evidence of being similar in explainability by some simple underlying lawlike mechanism. The word choice of “phase” seems like sleight of hand here. If instead we talk of “epochs” or “periods”, we’re less likely to bias ourselves towards a phantom unifying phenomenology of what could just be three not-very-causally-related transitions.
I agree that what I’ve presented in the post is not sufficient evidence to use the word “phase” to describe what’s happening. The reason I use this word is because of higher resolution evidence. To give one example, I think any kind of hyperbolic growth model seriously struggles to explain the lack of rapid growth in China or India for most of history, while a phase transition model can explain this by diffusion dynamics.
I also don’t want to present a unifying phenomenology of all the transitions and I think I haven’t attempted to do anything of the sort. The only real information I’ve looked at when it comes to the phases is how many doublings of GWP they took to complete.
My critique here seems obvious and unoriginal, and the people it’s aimed at are very well-informed and thoughtful. So I apologize if this has been addressed elsewhere already. What am I missing?
I think you’re appropriately skeptical of the scant amount of evidence in this area. The problem is just that we don’t have anything better to go on and we need to rely on some understanding if we want to make quantitative forecasts. This model is at least a corrective to some other models that in my view are even less reliable.
Indeed! And what about the 7th phase shift? I must be missing something here. We’re pointing to just two particular transitions in all of human history. I fear we’re calling them “phase shifts” to convince ourselves that there is a simple underlying phenomenon which has law-ordained “phases”. How can we assume that there will be a coherent series of N>2 such “phase shifts”? How can we assume that they will follow some simple mathematical function with just a handful of parameters?
I guess this makes me even more of a singularity skeptic than Hanson. He marshals powerful economic arguments against naive singularitarianism. But then he forecasts a similarly epochal transition to whole-brain emulations, yet seems worried that it needs more support than its own inside analysis provides. So goes back to an outside extrapolation from past data points a la Kurzweil, but he extrapolates from only 2 points, and says the resulting curve can’t really tell us anything beyond the 3rd point. By contrast, Kurzweil marshals multiple technological trends each with dozens of past data points. If we call that naive, then how confidently can we extrapolate along a single trend with only 2 prior data points?
That doesn’t feel like a curve to me. It just feels like a prediction of a 3rd transition that will have similar significance to two previous transitions. But being similar in significance is not really evidence of being similar in explainability by some simple underlying lawlike mechanism. The word choice of “phase” seems like sleight of hand here. If instead we talk of “epochs” or “periods”, we’re less likely to bias ourselves towards a phantom unifying phenomenology of what could just be three not-very-causally-related transitions.
My critique here seems obvious and unoriginal, and the people it’s aimed at are very well-informed and thoughtful. So I apologize if this has been addressed elsewhere already. What am I missing?
In general you can’t assume anything like this, but you also can’t assume that the present growth rate will continue forever (or anything else, really) for similar reasons. The point is that to make forecasts about future economic transitions you need some kind of model, and the model in this post is meant to provide the outside view on how often such transitions have occured.
The less controversial version of this, namely people fitting a production function such as f(K,L)=AKαL1−α to the GDP of different countries with L,K,A denoting labor stock, capital stock and total factor productivity respectively, and then assuming some law of motion like Δlog(At+1)=(μ−σ2/2)+σεt is the basis of a whole lot of macroeconomic modeling . For example, the entirety of the real business cycle school probably falls into this category. In my view this is much less plausible and in fact this model is immediately refuted by the data since μ has changed so much over the span of thousands of years.
If you don’t like this real business cycle inspired model, what do you use instead to make forecasts? Clearly one kind of model you should keep in mind is the phase transition model, and it achieves a much better fit with data at the expense of only two or three parameters over the real business cycle model. I’m not saying you should treat the model’s forecasts as gospel (and I don’t, my forecasts are not identical to what the model outputs) but it’s definitely valuable to see what this type of model has to say. The same goes for Roodman’s stochastic hyperbolic growth model.
Kurzweil’s marshaled trends in individual technologies are highly unreliable because they don’t tell us anything about economic transformation directly, and the supposed connections of his measures to such a transformation are quite tenuous. In my view Hanson’s paper has a poor methodology and model specification (something I hope to remedy at some point in the future) but his general approach is much more justified because it looks specifically at examples of past economic transitions.
To give another remarkable example, consider abiogenesis, which is likely the most significant kind of transition that happens in the history of the universe. If you consider all the transitions of this form that have happened before humans even came to exist, I think the argument that phase transitions aren’t that unusual is compelling.
I agree that what I’ve presented in the post is not sufficient evidence to use the word “phase” to describe what’s happening. The reason I use this word is because of higher resolution evidence. To give one example, I think any kind of hyperbolic growth model seriously struggles to explain the lack of rapid growth in China or India for most of history, while a phase transition model can explain this by diffusion dynamics.
I also don’t want to present a unifying phenomenology of all the transitions and I think I haven’t attempted to do anything of the sort. The only real information I’ve looked at when it comes to the phases is how many doublings of GWP they took to complete.
I think you’re appropriately skeptical of the scant amount of evidence in this area. The problem is just that we don’t have anything better to go on and we need to rely on some understanding if we want to make quantitative forecasts. This model is at least a corrective to some other models that in my view are even less reliable.