Towards a responsible AI-driven transformation of work (RESP-AI)

While there is no doubt that artificial intelligence (AI) will bring about an unprecedented transformation of work, researchers are still hotly debating how AI will transform work. The AI-pessimists warn against massive unemployment and the risks that AI deskills and enslaves humans. The AI-optimists laud AI’s potential to improve working lives and to enable innovating as never before.

Both camps seem to ignore that the future of work is still open: this future very much depends on how AI is deployed in organizations.

The future of work can be bright for both organizations and workers if organizations start right now responsibly reskilling and retraining workers to collaborate with AI, unleashing the extraordinary innovative potential of this new form of collaborations while providing workers with more meaningful work.

Today, there is, however, close to no scientific work to guide organizations in responsibly transforming work when adopting AI. My interdisciplinary research project addresses this urgent gap.

Combining innovative and cutting-edge qualitative, quantitative, and conceptual methods, I will deliver three scientific papers and a roadmap to fulfill two broad objectives.

My first objective is to provide an in-depth understanding of the state of affairs regarding the AI-driven transformation of work in multiple organizations and across multiple sectors (How is work transforming? How is this transformation affecting workers? How responsible has the transformation been so far?).

Then, based on a good grasp of both organizations’ and workers’ needs linked to the AI-driven transformation of work, my second objective is to provide a roadmap to guide managers on how to transform work responsibly to unleash AI innovative potential and ensure a bright future for workers.

The project is not only highly scholarly innovative, it is also highly relevant for the competiveness of EU firms and for EU workers (special attention will be paid to women).