The rise of the research automaton: acience as process or product in the era of generative AI?

Abstract Generative Artificial Intelligence (Gen AI) now allows for the seeming automation of most if not all steps in the scientific research lifecycle, giving rise to what I refer to as the Research Automaton – the production of science-like output with minimal meaningful human engagement. This development is often framed through a techno-solutionist lens, promising efficiency gains by treating the traditional, often strenuous, research process as a problem to be solved. This paper challenges that perspective, arguing that the intrinsic value of science lies in this very process rather than solely in the product . Uncritically embracing automation thus entails eroding the formative experiences crucial for researcher development, particularly for early-career researchers, leading to potential skill atrophy and undermining the long-term innovative capacity of science. Drawing on both normative arguments about science as a vocation and pragmatic concerns about preserving essential cognitive and critical skills, I advocate for resisting the Research Automaton, while acknowledging the potential for AI to augment human capabilities when used judiciously within a hybrid cognitive constellation. I conclude by outlining practical implications for researchers, supervisors, institutions, policymakers, and publishers in navigating the integration of Gen AI in research.