Scientific journals, crucial components of our epistemic infrastructure, have continuously adapted to the changing technological landscape. Today, we stand at the precipice of a transformative phase brought about by generative AI, specifically large language models such as OpenAI’s GPT and Google’s Bard. In this opinion piece, I examine the implications of these models for the future of scientific journals and various stakeholders in the scientific community, including journals, scholars, and universities. To envisage the future trajectory of scientific journals, it’s imperative to comprehend the operational mechanisms of these models and the fundamentally recombinatorial nature of human knowledge creation. I suggest that one of the significant roles generative AI can play is facilitating “long jumps” in our knowledge exploration process. I further propose decentralization and deferred and temporary binding as two crucial characteristics of the evolving epistemic infrastructure that supports precarious knowledge production. I foresee a future where scientific journals extend beyond their traditional gatekeeping roles. I call for scholars—as authors, reviewers, and mentors—to utilize these technologies to traverse the broad landscape of potential knowledge, fostering a more inclusive and dynamic scientific ecosystem.
"Evolving Epistemic Infrastructure: The Role of Scientific Journals in the Age of Generative AI,"
Journal of the Association for Information Systems, 25(1), 137-144.
Available at: https://aisel.aisnet.org/jais/vol25/iss1/4
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