In my final “bench to bot” column, I reflect on over two years of examining AI’s role in scientific writing. Initially apprehensive, my perspective evolved from cautious curiosity to a realization that AI’s ability to produce competent prose may not align with the nuanced needs of scientific communication. While AI could alleviate time-consuming writing tasks and assist researchers struggling with prose, I increasingly recognize the inherent risks: rapid production could hinder actual scientific progress. This paradox mirrors past observations about computing and productivity; we’ve seen advancements without significant gains in output. Engaging with writing is essential for deepening understanding, revealing gaps in knowledge. The discomfort of articulating complex ideas often signals a pivotal learning moment. As we navigate AI’s integration, we must distinguish between enhancing clarity and merely producing text. The future of impactful science lies in valuing the writing process itself, not merely the efficiency of outcomes, ensuring that genuine discovery prevails over superficial accomplishments.
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