The study of the social impact of technology belongs to a class of problems in the social sciences that requires a more complex logic than that of simple causality (direct relationship among few variables and their explicit sequences). Dual effects are one reason for the paucity of the literature on its impact. Moreover, the rapid advances of information technology make any study of its consequences much more difficult to pin down. Therefore, a study of the impact of new information technologies should account for the fast-paced change by addressing future changes rather than studying only the present moment.
The future lies in the domain of goals, and its plasticity makes it more important to study and more difficult to predict ( Cornish 1977). Since the future is seldom a mere temporal continuation of past, it is likely to be significantly different from the present.
The study of the future implies the use of forecasting techniques. Forecasting applies available information to predict consequences of present policies and to propose actions to achieve desired goals. Forecasting, however, is not mere prediction; it needs to account for contextual situations, and uses informed judgments about events to draw a wide range of possible consequences. 1 As such, many forecasting methods qualify as tools for planning public policymaking. Yet, the field of planning seldom devotes enough attention to forecasts ( Wachs 1985). 2