𝗔𝗜 𝗶𝘀 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗶𝗻𝗴𝗹𝘆 𝗽𝗿𝗲𝘀𝗲𝗻𝘁 𝗶𝗻 𝗯𝗼𝘁𝗵 𝗮𝗰𝗮𝗱𝗲𝗺𝗶𝗰 𝗺𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁𝘀 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗽𝗲𝗲𝗿 𝗿𝗲𝘃𝗶𝗲𝘄 𝗽𝗿𝗼𝗰𝗲𝘀𝘀

Many researchers already rely on AI tools at different stages: from brainstorming and outlining to spellcheck and even rephrasing of prose. Yes, this can boost efficiency and streamline mundane tasks, but it also introduces serious ethical risks.

Biases ingrained in AI systems can subtly influence scholarly communication. When we ask an LLM to participate in the writing process, we risk reinforcing existing biases in knowledge production. Overreliance on AI can also deteriorate the quality of peer reviews and manuscripts, replacing critical judgment with automated suggestions.

Academic publishers and editorial boards play a crucial role in shaping what knowledge gets legitimized and what ends up rejected. Should they delegate parts of this responsibility to algorithms? Are the efficiency gains really worth the loss of context, ethical nuance, and innovative thinking that human experts bring?

We’re curious: 𝘸𝘩𝘢𝘵 𝘥𝘰 𝘺𝘰𝘶 𝘵𝘩𝘪𝘯𝘬 𝘪𝘴 𝘵𝘩𝘦 𝘴𝘪𝘯𝘨𝘭𝘦 𝘮𝘰𝘴𝘵 𝘪𝘮𝘱𝘰𝘳𝘵𝘢𝘯𝘵 𝘴𝘵𝘦𝘱 𝘦𝘥𝘪𝘵𝘰𝘳𝘴 𝘰𝘧 𝘢𝘤𝘢𝘥𝘦𝘮𝘪𝘤 𝘫𝘰𝘶𝘳𝘯𝘢𝘭𝘴 𝘴𝘩𝘰𝘶𝘭𝘥 𝘵𝘢𝘬𝘦 𝘳𝘪𝘨𝘩𝘵 𝘯𝘰𝘸 𝘵𝘰 𝘥𝘦𝘢𝘭 𝘸𝘪𝘵𝘩 𝘈𝘐 𝘪𝘯 𝘸𝘳𝘪𝘵𝘪𝘯𝘨 𝘢𝘯𝘥 𝘱𝘦𝘦𝘳 𝘳𝘦𝘷𝘪𝘦𝘸?

We’ll dive into this topic and more during the Openjournals Network and Users’ Day on June 3, 2026.