Note that Kurzweil’s responded to the data dredging complaint by taking major lists compiled by other people, combining them and showing that they fit a roughly exponential graph. (I don’t have a citation for this unfortunately).
Edit: I’m not aware of anyone making a model of the sort you envision but it seems to suffer they same problem that Kurzweil has in general which is a potential overemphasis on information processing ability.
Information processing isn’t the whole story of what we care about. For example, the amount of energy available to societies and the per a capita energy availability both matter. (In fairness, Kurzweil has discussed both of these albeit not as extensively as information issues).
Another obvious metric to look at is average lifespan. This is one where one doesn’t get an exponential curve. Now, if you assert that most humans will live to at least 50 and so look at life span − 50 in major countries over the last hundred years, then the data starts to look slightly more promising, but Kurzweil’s never discussed this as far as I’m aware because he hasn’t discussed lifespan issues much at all, except in the most obvious fasion. You can modify the data in other ways also. One of my preferred metrics looks at the average lifespan of people who survive past age 3 (this helps deal with the fact that we’ve done a lot more to handle infant mortality than we have to actually extend lifespan on the upper end). And when you do this, most gains of lifespan go away.
Good points. Still I feel that basing the crux of the argument on information processing is valid, unless the other concerns you mention interfere with it at some point. Is that what you’re saying?
Good observation about infant mortality; there should be an opposite metric of “% of centenarians”, which would be a better measure in this context.
%Centenarians might not be a good metric given that one will get an increasing fraction of those as birth rates decline. For the US, going by the data here and here, I get a total of 1.4 10^-4 for the fraction of the US pop that is over 100 in 1990, and a result of 1.7 10^-4 in 2000. But I’m not sure how accurate this data is. For example, in the first of the two links they throw out the 1970 census data as given a clearly too high number. One needs a lot more data points to see if this curve looks exponential (obviously two isn’t enough), but the linked paper claims that for the foreseeable future the fraction of the pop that will be over 100 will increase by 2/3rds each decade. If that is accurate, then that means we are seeing an exponential increase.
Another metric to use might be the age of the oldest person by year of birth worldwide. That data shows a clear increasing trend, but the trend is very weak. Also, one would expect such an increase simply by increasing the general population (Edit: and better record keeping since the list includes only those with good verification), so without a fair bit of statistical crunching, it isn’t clear that this data shows anything.
Well, they do interfere, for example, lifespan issues help tell us if we’re actually taking advantage of the exponential growth in information processing, or for that matter if even if we are taking advantage that it actually matters. If for example information processing ability increases exponentially but the marginal difficulty in improving other things (like say lifespan) increases at a faster rate, then even with an upsurge in information processing one isn’t necessarily going to see much in the way of direct improvements. Information processing is also clearly limited in use based on energy availability. If I went back to say 1950 and gave someone access to a set of black boxes that mimic modern computers, the overall rate of increase in tech won’t be that high, because the information processing ability while sometimes the rate limiting step, often is not (for example, generation of new ideas and speed at which prototypes can be constructed and tested both matter). And this is even more apparent if I go further back in time. The timespan from 1900 to 1920 won’t look very different with those boxes added, to a large extent because people don’t know how to take advantage of their ability. So there are a lot of constraints other than just information processing and transmission capability.
Edit: Information processing might potentially work as one measure among a handful but by itself it is very crude.
Note that Kurzweil’s responded to the data dredging complaint by taking major lists compiled by other people, combining them and showing that they fit a roughly exponential graph. (I don’t have a citation for this unfortunately).
Edit: I’m not aware of anyone making a model of the sort you envision but it seems to suffer they same problem that Kurzweil has in general which is a potential overemphasis on information processing ability.
Why is basing this argument on information processing bad?
Information processing isn’t the whole story of what we care about. For example, the amount of energy available to societies and the per a capita energy availability both matter. (In fairness, Kurzweil has discussed both of these albeit not as extensively as information issues).
Another obvious metric to look at is average lifespan. This is one where one doesn’t get an exponential curve. Now, if you assert that most humans will live to at least 50 and so look at life span − 50 in major countries over the last hundred years, then the data starts to look slightly more promising, but Kurzweil’s never discussed this as far as I’m aware because he hasn’t discussed lifespan issues much at all, except in the most obvious fasion. You can modify the data in other ways also. One of my preferred metrics looks at the average lifespan of people who survive past age 3 (this helps deal with the fact that we’ve done a lot more to handle infant mortality than we have to actually extend lifespan on the upper end). And when you do this, most gains of lifespan go away.
Good points. Still I feel that basing the crux of the argument on information processing is valid, unless the other concerns you mention interfere with it at some point. Is that what you’re saying?
Good observation about infant mortality; there should be an opposite metric of “% of centenarians”, which would be a better measure in this context.
%Centenarians might not be a good metric given that one will get an increasing fraction of those as birth rates decline. For the US, going by the data here and here, I get a total of 1.4 10^-4 for the fraction of the US pop that is over 100 in 1990, and a result of 1.7 10^-4 in 2000. But I’m not sure how accurate this data is. For example, in the first of the two links they throw out the 1970 census data as given a clearly too high number. One needs a lot more data points to see if this curve looks exponential (obviously two isn’t enough), but the linked paper claims that for the foreseeable future the fraction of the pop that will be over 100 will increase by 2/3rds each decade. If that is accurate, then that means we are seeing an exponential increase.
Another metric to use might be the age of the oldest person by year of birth worldwide. That data shows a clear increasing trend, but the trend is very weak. Also, one would expect such an increase simply by increasing the general population (Edit: and better record keeping since the list includes only those with good verification), so without a fair bit of statistical crunching, it isn’t clear that this data shows anything.
Well, they do interfere, for example, lifespan issues help tell us if we’re actually taking advantage of the exponential growth in information processing, or for that matter if even if we are taking advantage that it actually matters. If for example information processing ability increases exponentially but the marginal difficulty in improving other things (like say lifespan) increases at a faster rate, then even with an upsurge in information processing one isn’t necessarily going to see much in the way of direct improvements. Information processing is also clearly limited in use based on energy availability. If I went back to say 1950 and gave someone access to a set of black boxes that mimic modern computers, the overall rate of increase in tech won’t be that high, because the information processing ability while sometimes the rate limiting step, often is not (for example, generation of new ideas and speed at which prototypes can be constructed and tested both matter). And this is even more apparent if I go further back in time. The timespan from 1900 to 1920 won’t look very different with those boxes added, to a large extent because people don’t know how to take advantage of their ability. So there are a lot of constraints other than just information processing and transmission capability.
Edit: Information processing might potentially work as one measure among a handful but by itself it is very crude.