Room "Sala Seminari" - Abacus Building (U14)
Epistemological fault lines between human and artificial intelligence
Speaker
Valerio Capraro
University of Milano-Bicocca
Abstract: Large language models (LLMs) are widely described as artificial intelligence, yet their epistemic profile diverges sharply from human cognition. Here we show that the apparent alignment between human and machine outputs conceals a deeper structural mismatch in how judgments are produced. Tracing the historical shift from symbolic AI and information filtering systems to large-scale generative transformers, we argue that LLMs are not epistemic agents but stochastic pattern-completion systems, formally describable as walks on high-dimensional graphs of linguistic transitions rather than as systems that form beliefs or models of the world. By systematically mapping human and artificial epistemic pipelines, we identify seven epistemic fault lines, divergences in grounding, parsing, experience, motivation, causal reasoning, metacognition, and value. We call the resulting condition Epistemia: a structural situation in which linguistic plausibility substitutes for epistemic evaluation, producing the feeling of knowing without the labor of judgment. We conclude by outlining consequences for evaluation, governance, and epistemic literacy in societies increasingly organized around generative AI.
Bio: Valerio Capraro combines human experiments, mathematical modelling, and numerical simulations to shed light on human behaviour. His work has been published in leading academic journals, including Nature, Nature Human Behaviour, and PNAS. His book "The economics of language: How large language models can reshape behavioural economics" is forthcoming by Cambridge University Press.
The seminar is associated to NeSS and can also be followed online. Registration is mandatory at:
https://unimib.webex.com/weblink/register/r5ba248458c28c2139ec5ff14d5ff6efe
Contact person for the seminar: rafael.penaloza@unimib.it