Many critics of Age of Em are critics of social science; they suggest that even though we might be able to use today’s physics or computer science to guess at futures, social science is far less useful.
For example At Crooked Timber Henry Farrell was “a lot more skeptical that social science can help you make predictions”, though he was more skeptical about thinking in terms of markets than in terms of “vast and distributed hierarchies of exploitation”, as these “generate complexities” instead of “ breaking them down.”
At Science Fact & Science Fiction Concatenation, Jonathan Cowie suggests social science only applies to biological creatures:
While Hanson’s treatise is engaging and interesting, I confess that personally I simply do not buy into it. Not only have I read too much SF to think that em life will be as prescriptive as Hanson portrays, but coming from the biological sciences, I am acutely aware of the frailties of the human brain hence mind (on a psychobiological basis). Furthermore, I am uncomfortable in the way that the social science works Hanson draws upon to support his em conclusions: it is an apples and oranges thing, I do not think that they can readily translate from one to the other; from real life sociobiological constructs to, in effect, machine code. There is much we simply do not know about this, as yet, untrodden land glimpsed from afar.
At Ricochet, John Walker suggests we can’t do social science if we don’t know detail stories of specific lives:
The book is simultaneously breathtaking and tedious. The author tries to work out every aspect of em society: the structure of cities, economics, law, social structure, love, trust, governance, religion, customs, and more. Much of this strikes me as highly speculative, especially since we don’t know anything about the actual experience of living as an em or how we will make the transition from our present society to one dominated by ems.
At his blog, Lance Fortnow suggests my social science assumes too much rationality:
I don’t agree with all of Hanson’s conclusions, in particular he expects a certain rationality from ems that we don’t often see in humans, and if ems are just human emulations, they may not want a short life and long retirement. Perhaps this book isn’t about ems and robots at all, but about Hanson’s vision of human-like creatures as true economic beings as he espouses in his blog. Not sure it is a world I’d like to be a part of, but it’s a fascinating world nevertheless.
At Entropy Chat List, Rafal Smigrodzki suggests social science doesn’t apply if ems adjust their brain design:
My second major objection: Your pervasive assumption that em will remain largely static in their overall structure and function. I think this assumption is at least as unlikely as the em-before-AI assumption. Imagine .. you have the detailed knowledge of your own mind, the tools to modify it, and the ability to generate millions of copies to try out various modifications. .. you do analyze this possibility, you consider some options but in the end you still assume ems will be just like us. Of course, if ems are not like us, then a lot of the detailed sociological research produced on humans would not be very applicable to their world and the book would have to be shorter, but then it might be a better one. In one chapter you mention that lesbian women make more money and therefore lesbian ems might make money as well. This comes at the end of many levels of suspension of disbelief, making the sociology/gender/psychology chapters quite exhausting.
At his blog, J Storrs Hall said something similar:
Robin’s scenario precludes some of these concerns by being very specific to a single possibility: that we have the technology to copy off any single particular human brain, we don’t understand them well enough to modify them arbitrarily. Thus they have to operated in a virtual reality that is reasonably close to a simulated physical world. There is a good reason for doing it this way, of course: that’s the only uploading scenario in which all the social science studies and papers and results and so forth can be assumed to still apply.
Most social scientists, and especially most economists, don’t see what they have learned as being quite so fragile. Yes it is nice to check abstract theories against concrete anecdotes, but in fact most who publish papers do little such checking, and their results only suffer modestly from the lack. Yes being non-biological, or messing a bit with brain design, may make some modest differences. But most social science theory just isn’t that sensitive to such details. As I say in the book:
Our economic theories apply reasonably well not only to other classes and regions within rich nations today, but also to other very different nations today and to people and places thousands of years ago. Furthermore, formal economic models apply widely even though quite alien creatures usually populate them, that is, selfish rational strategic agents who never forget or make mistakes. If economic theory built using such agents can apply to us today, it can plausibly apply to future ems.
The human brain is a very large complex legacy system whose designer did not put a priority on making it easy to understand, modify, or redesign. That should greatly limit the rate at which big useful redesign is possible.
Economics. Yah I'll but that. It is the projections about em socialization, values and other sociology/psychology style assumptions that I am concerned about.
I expect economics to describe extraterrestials when we meet them. I don't expect them to pair bond, engage in human social structures or leisure. While small molecule drugs won't totally undo those inclinations it does alter relative the subtle balances that dictate whether we are social or anti-social, looking for long term or short term mate investment etc.. And with simulations we can do way better than small molecule drugs.
But I doubt this will convince you.
There are frequently criticisms of the social sciences out of hand, because it's "not empirical enough". It's a part of the Humanities vs. Science false dichotomy, which assumes that we can only look at problems in one way, and that way is Science. But what we have here are different tools for different needs, and we need to be confident with all of them to properly tackle a complex problem like that described in the article.
I have a friend who has an even stricter view on this: "The Science part is easy because the data is what it is. You need the Humanities for the hard part- to think about what the data means, and what we should do as a result."