In general I’m skeptical about the ability of the social sciences to offer predictions about future social developments. (In this respect I follow some of the instincts of Oskar Morgenstern in On the Accuracy of Economic Observations.) We have a hard time answering questions like these:
- How much will the first installment of TARP improve the availability of credit within three months?
- Will the introduction of UN peacekeeping units reduce ethnic killings in the Congo?
- Will the introduction of small high schools improve student performance in Chicago?
- Will China develop towards more democratic political institutions in the next twenty years?
- Will American cities witness another round of race riots in the next twenty years?
However, the situation isn’t entirely negative, and there certainly are some social situations for which we can offer predictions in at least a probabilistic form. Here are some examples:
- The unemployment rate in Michigan will exceed 10% sometime in the next six months.
- Coalition casualties in the Afghanistan war will be greater in 2009 than in 2008.
- Illinois Governor Blogojevich will leave office within six months.
- Germany will be the world leader in solar energy research by 2020 (link).
- The Chinese government will act strategically to prevent emergence of regional independent labor organizations.
It is worth exploring the logic and function of prediction for a few lines. Fundamentally, it seems that prediction is related to the effort to forecast the effects of interventions, the trajectory of existing trends, and the likely strategies of powerful social actors. We often want to know what will be the net effect of introducing X into the social environment. (For example, what effect on economic development would result from a region’s succeeding in increasing the high school graduation rate from 50% to 75%?) We may find it useful to project into the future some social trends that can be observed in the present. (Demographers’ prediction that the United States will be a “majority-minority” population by 2042 falls in this category (link).) And we can often do quite a bit of rigorous reasoning about the likely actions of leaders, policy makers, and other powerful actors given what we know about their objectives and their beliefs. (We can try to forecast the outcome of the current impasse between Russia and Ukraine over natural gas by analyzing the strategic interests of both sets of decision-makers and the constraints to which they must respond.)
So the question is, what kinds of predictions can we make in the social realm? And what circumstances limit our ability to predict?
Predictions about social phenomena are based on a couple of basic modes of reasoning:
- extrapolation of current trends
- modeling of causal hypotheses about social mechanisms and structures
- reasoning about strategic actions likely to be taken by actors
- derivation of future states of a system from a set of laws
And predictions can be presented in a range of levels of precision, specificity, and confidence:
- prediction of a single event or outcome: the selected social system will be in state X at time T.
- prediction of the range within which a variable will fall: the selected social variable will fall within a range Q ±20%.
- prediction of the range of outcome scenarios that are most likely: “Given current level of unrest, rebellion 60%, everyday resistance 30%, resolution 10%”
- prediction of the direction of change: the variable of interest will increase/decrease over the specified time period
- prediction of the distribution of properties over a group of events/outcomes. X percent of interventions will show improvement of variable Y.
Here are some particular obstacles to reliable predictions in the social realm:
- unquantifiable causal hypotheses — “small schools improve student performance”. How large is the effect? How does it weigh in relation to other possible causal factors?
- indeterminate interaction effects — how will school policy changes interact with rising unemployment to jointly influence school attendance and performance?
- open causal fields. What other currently unrecognized causal factors are in play?
- the occurrence of unpredictable exogenous events or processes (outbreak of disease)
- ceteris paribus conditions. These are frequently unsatisfied.
So where does all this leave us with respect to social predictions? A few points seem relatively clear.
Specific prediction of singular events and outcomes seems particularly difficult: the collapse of the Soviet Union, China’s decision to cross the Yalu River in the Korean War, or the onset of the Great Depression were all surprises to the experts.
Projection of stable trends into the near future seems most defensible — though of course we can give many examples of discontinuities in previously stable trends. Projection of trends over medium- and long-term is more uncertain — given the likelihood of intervening changes of structure, behavior, and environment that will alter the trends over the extended time.
Predictions of limited social outcomes, couched in terms of a range of possibilities attached to estimates of probabilities and based on analysis of known causal and strategic processes, also appear defensible. The degree of confidence we can have in such predictions is limited by the possibility of unrecognized intervening causes and processes.
The idea of forecasting the total state of a social system given information about the current state of the system and a set of laws of change is entirely indefensible. This is unattainable; societies are not systems of variables linked by precise laws of transition.