The achievement gap thesis reconsidered: artificial intelligence, automation, and meaningful work

Abstract

John Danaher and Sven Nyholm have argued that automation, especially of the sort powered by artificial intelligence, poses a threat to meaningful work by diminishing the chances for meaning-conferring workplace achievement, what they call “achievement gaps”. In this paper, I argue that Danaher and Nyholm’s achievement gap thesis suffers from an ambiguity. The weak version of the thesis holds that automation may result in the appearance of achievement gaps, whereas the strong version holds that automation may result on balance loss in possibilities for workplace achievements, i.e., in the appearance of an overall gappier work landscape. Against the strong version of the achievement gap thesis, I characterize situations where automation may result in boons to meaning-conferring workplace achievements: the appearance of what I call achievement spread and achievement swaps. Nevertheless, Danaher and Nyholm are right to worry about some uses of automation whereby human workers become subservient to AI. But these situations are better framed, I argue, as autonomy gaps rather than achievement gaps.

Navigating technological shifts: worker perspectives on AI and emerging technologies impacting well-being

“…A potential way to analyse these elements is through organisational contexts of work that focus on the power relationships between digital technologies and workers and how these power relationships have changed. Previous research indicates that a loss of autonomy, a loss of power, or a loss of meaning of work by employees who are subservient to AI results in lower well-being (Scripter 2024;Bisht et al 2021;Danaher and Nyholm 2021).…”