Contemporary urban and regional planning practice and scholarship often fails to address the full implications of technological change (technology blindness), lacks a clear or consistent definition of the long term (temporal imprecision) and seldom uses formal foresight methodologies. Discussion in the literature of time horizons beyond 10 years is, therefore, based on profoundly unrealistic assumptions about the future. The paper aims to discuss why conventional reasoning about possible futures is problematic, how consideration of long-term timescales is informal and inconsistent and why accelerating technological change requires that planners rethink basic assumptions about the future from 2030s onward.
The author reviews 1,287 articles published between January 2010 and December 2014 in three emblematic urban and regional planning journals using directed content analysis of key phrases pertaining to long-term planning, futures studies and self-driving cars.
The author finds that there is no evidence of consistent usage of the phrase long term, that timeframes are defined in fewer than 10 per cent of articles and that self-driving cars and related phrases occur nowhere in the text, even though this technology is likely to radically transform urban transportation and form starting in the early 2020s. Despite its importance, discussion of disruptive technological change in the urban and regional planning literature is extremely limited.
To make more realistic projections of the future from the late 2020s onward, planning practitioners and scholars should: attend more closely to the academic and public technology discourses; specify explicit timeframes in any discussion or analysis of the future; and incorporate methods from futures studies such as foresight approaches into long-term planning.
This paper identifies accelerating technological change as a major conceptual gap in the urban and regional planning literature and calls for practitioners and scholars to rethink their foundational assumptions about the long-term and possible, probable and preferable futures accordingly.
