Structural Shifts in Scholarly Communication: AI‑Mediated Paper Interaction Reveals Power Dynamics in Knowledge Production and Access
Original framing: “Daily briefing: How to turn a paper into an AI agent” — Nature
Empirical evaluations of the tool show improved retrieval speed and user satisfaction in controlled trials, grounded in advances in large‑language‑model fine‑tuning and retrieval‑augmented generation. However, the studies often neglect longitudinal impacts on comprehension, critical engagement, and the potential for algorithmic bias in summarizing complex arguments. A robust scientific assessment would require interdisciplinary metrics that capture epistemic depth, not just efficiency gains.
The drive to convert scholarly papers into conversational AI agents reflects a broader historical pattern where technological breakthroughs are initially heralded as emancipatory but quickly become enmeshed in profit‑driven platforms that concentrate epistemic power.
This trajectory overlooks the rich, relational knowledge traditions of Indigenous and Global South communities, which are poorly served by text‑centric models that strip context and privilege Northern‑hemisphere languages. By foregrounding the trickster irony of automating interpretation, we see how the solemn promise of efficiency masks a deeper paradox: the very tools meant to augment understanding may erode the dialogic, artistic, and spiritual dimensions of knowledge production. A systemic response requires open‑source, community‑governed infrastructures, equitable access policies, interdisciplinary impact assessments, and deliberate inclusion of diverse knowledge forms—actions that together can redirect AI‑mediated scholarship from enclosure toward a pluralistic, democratic commons.