Technological progress increases productivity and therefore creates the possibility of achieving the same output with less human work. One might therefore expect that, over time, people would work fewer hours and enjoy more time for family, hobbies, or personal projects.
Yet reality appears to tell a different story. Despite enormous productivity gains through computers and robots, working hours have not declined to the same extent. Instead, productivity gains are often absorbed by rising expectations, additional responsibilities, and an increasingly accelerated pace of work.
Three Dimensions of Social Acceleration
I came across this paradox through the work of the German sociologist and social philosopher Hartmut Rosa. In his book Social Acceleration: A New Theory of Modernity, originally published in German in 2005 as Beschleunigung. Die Veränderung der Zeitstrukturen in der Moderne, Rosa identifies three dimensions of social acceleration:
- Technical acceleration
- The acceleration of social change
- The acceleration of the pace of life
According to Rosa, these three dimensions reinforce one another. Technological innovations accelerate communication, production, and mobility. This, in turn, causes social structures, institutions, and ways of living to change more rapidly.
As a consequence, individuals experience increasing pressure to adapt and attempt to fit more activities into the same amount of time. The central problem, Rosa argues, is therefore not technological acceleration itself, but the fact that the time it saves is continuously consumed by new demands and additional activities.
Applying Rosa’s Theory to Generative AI
Rosa developed his theory based on earlier technologies such as computers, the internet, and email. Yet the same reasoning can be applied to generative AI.
If AI dramatically increases the productivity of knowledge work, it does not necessarily follow that people will work less. A more likely outcome is that organizations will raise expectations, pursue more initiatives, and create additional value. Productivity gains would then be translated not into more leisure time, but into a further acceleration of work and organizational processes.
Will AI Eliminate Jobs?
Viewed from this perspective, the frequently asked question of whether AI will eliminate jobs may be framed too narrowly. Historically, productivity gains have rarely resulted in people working substantially less. Instead, they have transformed the nature of work, raised expectations, and created new forms of value creation.
Whether AI will ultimately follow this historical pattern or represent a genuine break with it remains one of the most important questions of the coming decade.