I agree with this—the race to churn out papers is a systemetic problem. Early career scholars are desperate to get more papers to compete in the academic job market. This can make it hard for faculty mentors hard to reduce their output unless they shrink their lab (which clearly removes opportunities to the next generation). So the real change needs to be at the journals and hiring/promotion committees, where a focus on quality, rigor, and impact needs to take priority over the sheer volume of papers. This means search committees should ask for a couple of key papers and actually read them. And paper mills/journals should stop churning out garbage.

Are AI Tools Replacing Scientific Writing? Here's what some leading scientists have to say ⤵ Repost & Save (with 𝘤𝘭𝘪𝘱𝘱𝘦.𝘮𝘦) — Tools like ChatGPT are good helpers (but poor creators) — AI can speed up writing (but it's not ready to take over scientific thinking). — The real question isn't if we should use AI... ... but how to use it wisely! 𝐊𝐞𝐲 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐟𝐢𝐜 𝐖𝐫𝐢𝐭𝐢𝐧𝐠 ⤵ 𝗪𝗿𝗶𝘁𝗶𝗻𝗴 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲 — Helps break through writer's block — Makes helpful suggestions for titles & abstracts — Supports non-native English speakers with clear writing 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 & 𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 — Breaks complex topics into manageable pieces — Spots relevant papers you might have missed — Helps organize thoughts & arguments 𝐌𝐚𝐣𝐨𝐫 𝐂𝐨𝐧𝐜𝐞𝐫𝐧𝐬 — AI can't do deep analysis or generate true insights — Risk of shallow, cookie-cutter science writing — Tools might generate false references or incorrect info — Over-reliance could hurt students' learning Page 1/3