What is Left for Us? Second Scholarship Against the Degradation of Research by AI

Title:What is Left for Us? Second Scholarship Against the Degradation of Research by AI

Abstract:We argue that generative AI can degrade research by eroding the very practices through which scholarly judgement is formed. As constitutive conditions for the production and validation of knowledge, these practices cannot be reduced to the outputs of research, which is what AI tools so effectively simulate. When scholars delegate central tasks of inquiry to Large Language Models (LLMs), they may stop engaging in these practices and lose the formation they provide: the output may improve while the researcher fails to develop. Against this risk, merely keeping humans "in the loop" as prompters or quality checkers of AI outputs is insufficient to preserve research as a site of intellectual formation. What is needed instead is a renewed commitment to research as a lived practice in which judgement is formed gradually, often through friction, and participation in a scholarly community. We defend it because it rests on four sources and warrants of research that cannot be automated: tacit knowledge, personal commitment, socialisation, and deep reading. These enact what we call second scholarship, i.e., the reappropriation of scholarly craft, chosen out of a critical experience of what AI tools can and cannot do. Researchers who practise it may delegate tasks to these tools, provided that their own judgement in the delegated competence is already formed, that they can answer for the output, and that they keep exercising the competence themselves. What cannot and should not be delegated becomes what research communities must value and answer for. This is what is left for us.

Artificial Intelligence (cs.AI)

arXiv:2607.04049 [cs.AI]

(or arXiv:2607.04049v2 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2607.04049 Focus to learn more arXiv-issued DOI via DataCite

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