The calculator analogy: Epistemic virtues for using LLMs
Like the arrival of calculators in 1970s classrooms, large language models (LLMs) provoke both fears of intellectual deskilling and hopes of more efficient learning. In this paper we analyze the calculator analogy, arguing that while it is a useful starting point to understand the potential impact of LLMs in education, it is ultimately insufficient. We show where the analogy holds and, just as importantly, where its limitations reveal the unique pedagogical challenges posed by LLMs. These challenges arise from fundamental differences in how calculators and LLMs mediate learning, reflecting the distinct affordances of each technology. We argue that because of their affordances, realizing the educational potential of LLMs calls for cultivating epistemic virtues suited to human–AI interaction, such as patience, reflective engagement, or intellectual vigilance and humility. Equally, LLM design must actively foster these virtues through features like built-in prompts, feedback loops or reflective questions, to name just a few. • The calculator analogy illuminates but ultimately only partially captures LLMs' unique educational impact. • Technological affordances explain how tools shape, not just support, learning. • LLMs redistribute cognitive labour across all stages of reasoning, from framing to interpretation. • Persuasive fluency makes LLM outputs appear true, amplifying epistemic risks. • Effective use of LLMs demands cultivating epistemic virtues like patience and vigilance.
Authors
- Julian Savulescu (ORCID: https://orcid.org/0000-0003-1691-6403)
- Brian David Earp (ORCID: https://orcid.org/0000-0001-9691-2888)
- Sebastian Porsdam Mann (ORCID: https://orcid.org/0000-0002-1867-2097)
- Cristina Voinea (ORCID: https://orcid.org/0000-0003-4654-0697)
Publication Details
- Journal
- Technology in Society
- Published
- 2025-12-13
- DOI
- https://doi.org/10.1016/j.techsoc.2025.103198
- Primary Topic
- Mathematics Education and Teaching Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Wellcome Trust
- National Research Foundation
- National University of Singapore
- National Research Foundation Singapore
- Novo Nordisk
- Novo Nordisk Fonden