Projects

Platform work constitutes the fastest growing segment of alternative work. While many problems (e.g. low wages, unfair treatment of workers) have been reported, the more existential question of worth has received scant attention. Other than providing an (extra) income and a flexible schedule, we know little of what makes platform work worth doing, and why. This is especially true for low-skill and low-status platform work such as ride-hailing or delivery work (often labelled as gig work). So why is gig work (e.g. driving for Bolt) considered work worth doing by those who have a choice? The project explores this from the theoretical perspective of account-making, focusing on how and why the workers themselves and the wider society justify their work as worth doing. A better grasp of a society’s account of why platform work is worth doing is essential in fostering a responsible platform economy, which is critical for the continued flourishing of Estonia's and EU's digital economy.

Demands on human managers seem ever-expanding: they must be able to lead in both virtual and in-person environments, foster psychological safety and avoid micromanagement, be algorithmically literate while in touch with their intuition, and, of course, adhere to high ethical standards. In practice, human managers often turn to smart machines for much-needed aid to meet all the demands placed on them. However, when machines are used to partially automate duties traditionally undertaken by human managers, a new, more- than-human management practice is born. Crucially, the characteristics of more-than-human management will reflect both the nature of human managerial work and the work of smart machines, as well as their synergies – making the outcome more than the sum of the parts. What is "good" and "bad" more-than-human management is, therefore, likely to significantly differ from what is “good” and “bad” human management. Accordingly, project M-BOT examines two pressing questions facing society in the next generation: (1) how smart machines and human managers work together, and (2) what kind of managerial work (e.g., how rich in skills, how wise in decisions) this generates, with the aim of building new general theory of more-than- human management. The project adopts a mixed-methods, three-phase approach of (1) hypotheses development through qualitative case research, (2) hypotheses testing through agent-based modeling, and (3) theory development through substantive and abstract mechanism-based explanations. As PI, I am uniquely prepared to undertake this project as part of my growing portfolio of high-impact, internationally recognized research on digital transformation and future of work, consisting of three cumulative areas: implications of work digitalization for (a) individual workers, (b) organizations, and (c) managers. I have ongoing research projects and publication pipelines in all three areas that help me prepare for project M-BOT.