Nature of Science as an Epistemic Lens for AI-Generated Knowledge

The proliferation of AI systems generating scientific-sounding content poses a pressing epistemological challenge. This chapter argues the Nature of Science (NOS) framework provides a rigorous lens for evaluating AI-generated knowledge. Drawing on NOS literature and research on AI limitations, it develops three arguments. First, scientific tentativeness reflects an epistemically virtuous openness to revision, sharply contrasting with LLM hallucinations that mimic knowledge without evidential basis. Second, the theory-laden nature of science highlights the urgent need for transparency regarding AI training data bias and opacity. Third, NOS's view of the scientific community as the locus of epistemic authority challenges the legitimacy of unverified algorithmic authority. The chapter concludes by proposing a NOS-grounded framework for warranted epistemic trust, centered on verification, transparency, and accountability. Furthermore, it introduces a risk-differentiated taxonomy to help researchers calibrate verification efforts across various AI-assisted tasks.