Framework highlights critical discernment and systematic calibration in generative AI, proposing a new scientific literacy.
The integration of GenAI into academic workflows marks an epistemological inflection point. While these tools can amplify productivity, they risk eroding the cognitive foundations of expertise by simulating the very tasks through which scientific competence is developed, from synthesis to experimental design to writing. Uncritical reliance can lead to skill atrophy and AI complacency. To counter this, we propose a framework of essential AI meta-skills—strategic direction, critical discernment, and systematic calibration—that constitute a new form of scientific literacy distinct from traditional critical thinking. Through domain-specific examples and a pedagogical model based on situated learning, we propose how these meta-skills can be cultivated to ensure that researchers, particularly those in training, maintain intellectual autonomy. Proactive development of this AI-augmented expertise is necessary to shape a future where technology amplifies, rather than attenuates, scientific thought.
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Lin et al. (2025) studied this question.
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