When people talk about a “technological revolution,” the same story usually comes to mind: a new technology arrives, jobs disappear, and people lose their livelihoods. Yet we should understand technological transformation more broadly—as a transformation of control that restructures how work is organized and monitored.

Back in 2022, before the generative-AI explosion, I wrote a review of Work and Technological Change, a book by Stephen R. Barley, one of the legendary professors in the field, who offers a measured analysis of technological revolutions. As the book explains, their social consequences are not predetermined, nor can these technologies be treated as neutral tools.

The effects of technology are shaped by struggles involving many parties within the rules of organizations and industries, professional boundaries, and everyday practices. The passivity people have come to accept is partly the result of presenting these developments as an inevitable end state. It also reflects the tremendous power accumulated by the technology magnates now commonly called “tech bros,” through their giant corporations and, as illustrated by the Trump administration, their increasing proximity to political power.

The book’s greatest contribution to this debate is its refusal to describe technological effects deterministically. Instead of slogans such as “technology has arrived; software jobs are finished,” we need to trace how change is produced step by step at the level of organizations and practices.

As technologies are interpreted and put to use, the division of labor is redrawn, fields of expertise separate or converge, and regimes of control over workers change and are reconstituted. This perspective allows us to move debates about technology away from abstract predictions and fatalism, toward concrete problems of job design and arenas of social struggle.

In my review, I also offered a warning: we cannot analyze “intelligent” technologies in exactly the way we have become accustomed to analyzing conventional ones. Breaking technology down into components is often useful, but we cannot discover the “intelligence” of systems such as AI simply by taking their parts apart. Understanding the consequences of intelligent technologies therefore requires broader research programs, interdisciplinary teams, and new qualitative methods.

For example, in a project we recently submitted to Istanbul Technical University for special support as a priority-area initiative, I will work with professors Sule Gunduz Oguducu from our Faculty of Computer and Informatics Engineering and Onur Behzat Tokdemir from our Faculty of Civil Engineering to study the effects of AI on one of Türkiye’s critical sectors: construction. Very exciting!

What we need today is rigorous research tracing how work and working life are being reorganized, together with the capacity to translate that research into policy, education, and job design.

If humanity can imagine equitable governance that moves technology toward “better work” for everyone, rather than only for the tech bros, a better future may emerge.

REFERENCE

https://journals.sagepub.com/doi/abs/10.1177/09500170211058586