Jeremy Rozansky, assistant editor of National Affairs in The New Atlantis: ” In his debut book Uncontrolled, entrepreneur and policy analyst Jim Manzi argues that social scientists and policymakers should instead adopt the “experimental method.” The essential tool of this method is the randomized field trial (RFT), a technique that already informs many of our successful private enterprises. Perhaps the best known example of RFTs — one that Manzi uses to illustrate the concept — is the kind of clinical trial performed to test new medicines, wherein researchers “undertake a painstaking series of replicated controlled experiments to measure the effects of various interventions under various conditions,” as he puts it.
 
The central argument of Uncontrolled is that RFTs should be adopted more widely by businesses as well as government. The book is helpful and holds much wisdom — although the approach he recommends is ultimately just another streetlamp in the night, casting a pale light that tapers off after a few yards. Much still lies beyond its glow….
The econometric method now dominates the social sciences because it helps to cope with the problem of high causal density. It begins with a large data set: economic records, election results, surveys, and other similar big pools of data. Then the social scientist uses statistical techniques to model the interactions of sundry independent variables (causes) and a dependent variable (the effect). But for this method to work properly, social scientists must know all the causally important variables beforehand, because a hidden conditional could easily yield a false positive.
The experimental method, which Manzi prefers, offers a different way of coping with high causal density: sidestepping the problem of isolating exact causes. To sort out whether a given treatment or policy works, a scientist or social scientist can try it out on a random section of a population, and compare the results to a different section of the population where the treatment or policy was not implemented. So while econometric models aim to identify which particular variables are responsible for different results, RFTs have more modest aims, as they do not seek to identify every hidden conditional. By using the RFT approach, we may not know precisely why we achieved a desired effect, since we do not model all possible variables. But we can gain some ability to know that we will achieve a desired effect, at least under certain conditions.
Strictly speaking, even a randomized field trial only tells us with certainty that some exact technique worked with some specific population on some specific date in the past when conducted by some specific experimenters. We cannot know whether a given treatment or policy will work again under the same conditions at a later date, much less on a different population, much less still on the population as a whole. But scientists must always be cautious about moving from particular results to general conclusions; this is why experiments need to be replicated. And the more we do replicate them, the more information we can gain from those particular results, and the more reliably they can build toward teaching us which treatments or policies might work or (more often) which probably won’t. The result is that the RFT approach is very well suited to the business of government, since policymakers usually only need to know whether a given policy will work — whether it will produce a desired outcome.”