AI Threatens Research Integrity, Advocates "Second Scholarship"

The proliferation of generative AI poses a significant threat to the integrity and foundational practices of academic research, according to this paper. The authors contend that by delegating core inquiry tasks to systems like Large Language Models, researchers risk undermining the very processes through which scholarly judgment is cultivated and academic trust is established. This delegation, they argue, can impede a researcher's intellectual development, even if the AI-generated output appears superficially improved. The paper asserts that merely keeping humans "in the loop" as prompt engineers or quality checkers is insufficient to preserve research as a site of intellectual formation. Instead, it advocates for a "second scholarship" – a renewed dedication to research as a lived practice. This approach emphasizes the irreplaceable value of tacit knowledge, personal commitment, active socialization within scholarly communities, and deep, critical reading. These four elements, the authors argue, are fundamental warrants of research that cannot be automated. By reappropriating scholarly craft and critically understanding AI's capabilities and limitations, researchers can identify and uphold what truly remains essential and non-delegable in the pursuit of knowledge. This commitment ensures that research continues to be a process of profound intellectual growth and community engagement.