B9011 - Philosophy of Language (1) (LM)

Learning outcomes

By the end of the course, students will be able to: I) Explain major theories of meaning (Frege, Russell, Wittgenstein, Grice, etc.) and reference; II) Analyze the distinction between semantics and pragmatics, including truth-conditional and use-based accounts of meaning; III) Evaluate theories of speech acts and their role in communication; IV) Connect language and mind: discuss whether thought depends on language and how linguistic structures reflect cognition; V) Recognize initial philosophical challenges posed by LLMs regarding meaning, truth, and understanding.

Course contents

This course provides a rigorous introduction to the central debates in analytic philosophy of language. It is designed for an interdisciplinary cohort and does not presuppose an undergraduate degree in philosophy. The course examines the relations between language, meaning, truth, reference, context, communication, and thought. Classical theories are introduced through close analysis of arguments and linguistic examples. A limited formal-semantics component introduces semantic values, compositionality, extension and intension, and the distinction between context and circumstance of evaluation without presupposing advanced mathematical logic. The final part uses these conceptual tools to introduce the philosophical debate about language produced by large language models.

Unit 1 - Meaning and reference

• Frege on sense, reference, and the cognitive value of identity statements.

• Russell on definite descriptions and the distinction between grammatical and logical form.

• Kripke on proper names, rigid designation, and the critique of descriptivism.

• Putnam on natural-kind terms, Twin Earth, the division of linguistic labour, and semantic externalism.

Unit 2 - Truth, formal semantics, and context

• Truth conditions, semantic values, compositionality, extension, and intension.

• Davidsonian truth-theoretic approaches to meaning and a minimal introduction to formal semantics.

• Kaplan on indexicals, character, content, context, and circumstance of evaluation; verificationist theories and Wittgensteinian use theories.

Unit 3 - Semantics, dynamic context, pragmatics, and speech acts

• Semantic content, speaker meaning, pragmatic enrichment, context dependence, and indexicality.

• Grice on conversational implicature and the Cooperative Principle.

• Stalnaker on common ground and assertion as a proposal to update the conversational context.

• Lewis on conversational scorekeeping, salience, presupposition, and accommodation.

• Austin and Searle on performatives, illocutionary force, constitutive rules, and indirect speech acts.

Unit 4 - Language and mind

• Linguistic and mental content; language and thought; intentionality, representation, and understanding.

• Connections with the companion module Philosophy of Mind.

Unit 5 - Language and large language models

• A non-technical introduction to language models and conversational AI systems.

• The distinction between linguistic performance, semantic status, and understanding.

• Whether LLM-generated expressions can mean and refer; grounding and reference inheritance.

• Truth-aptness without assertion; speakerhood, commitment, answerability, and responsibility.

• Comparison between sceptical, layered, externalist, and Whole-Hog approaches to AI cognition.

The first four units occupy approximately 24 hours. The final unit occupies approximately 6 hours and provides an introductory map of questions developed in greater depth in the second-year course Language, Meaning, and AI.

Readings/Bibliography

Required course book

Kemp, Gary. What Is This Thing Called Philosophy of Language? 3rd ed. London: Routledge, 2024. Selected chapters.

Required primary readings

Frege, Gottlob. “On Sense and Reference.” Translated by Max Black. In Translations from the Philosophical Writings of Gottlob Frege, edited by Peter Geach and Max Black, 56–78. Oxford: Basil Blackwell, 1952. Originally published as “Über Sinn und Bedeutung,” Zeitschrift für Philosophie und philosophische Kritik 100 (1892): 25–50.

Russell, Bertrand. “On Denoting.” Mind 14, no. 56 (1905): 479–493. Selected passages.

Kripke, Saul A. Naming and Necessity. Cambridge, MA: Harvard University Press, 1980. Selected passages.

Putnam, Hilary. “The Meaning of ‘Meaning’.” In Language, Mind, and Knowledge, edited by Keith Gunderson, 131–193. Minnesota Studies in the Philosophy of Science 7. Minneapolis: University of Minnesota Press, 1975. Selected sections.

Davidson, Donald. “Truth and Meaning.” Synthese 17, no. 1 (1967): 304–323. https://doi.org/10.1007/BF00485035.

Kaplan, David. “Demonstratives: An Essay on the Semantics, Logic, Metaphysics, and Epistemology of Demonstratives and Other Indexicals.” In Themes from Kaplan, edited by Joseph Almog, John Perry, and Howard Wettstein, 481–563. New York: Oxford University Press, 1989. Selected sections on character, content, context, and circumstance of evaluation.

Wittgenstein, Ludwig. Philosophical Investigations. 4th ed. Translated by G. E. M. Anscombe, P. M. S. Hacker, and Joachim Schulte. Revised by P. M. S. Hacker and Joachim Schulte. Chichester: Wiley-Blackwell, 2009. §§1–43.

Grice, H. P. “Logic and Conversation.” In Syntax and Semantics, Volume 3: Speech Acts, edited by Peter Cole and Jerry L. Morgan, 41–58. New York: Academic Press, 1975.

Stalnaker, Robert. “Common Ground.” Linguistics and Philosophy 25, nos. 5–6 (2002): 701–721. https://doi.org/10.1023/A:1020867916902. Selected sections.

Austin, J. L. How to Do Things with Words. 2nd ed. Edited by J. O. Urmson and Marina Sbisà. Cambridge, MA: Harvard University Press, 1975. Selected lectures.

Searle, John R. Speech Acts: An Essay in the Philosophy of Language. Cambridge: Cambridge University Press, 1969. Selected passages.

Davidson, Donald. “Thought and Talk.” In Inquiries into Truth and Interpretation, 155–170. Oxford: Clarendon Press, 1984. Originally published in Mind and Language, edited by Samuel Guttenplan. Oxford: Clarendon Press, 1975.

Required readings on large language models

Shanahan, Murray. “Talking about Large Language Models.” Communications of the ACM 67, no. 2 (2024): 68-79.

Mandelkern, Matthew, and Tal Linzen. “Do Language Models’ Words Refer?” Computational Linguistics 50, no. 3 (2024): 1191-1200.

Borg, Emma. “LLMs, Turing Tests and Chinese Rooms: The Prospects for Meaning in Large Language Models.” Inquiry 69, no. 6 (2026): 2807-2837. Selected sections.

Recommended readings on formal semantics, context, and pragmatics

Lewis, David. “General Semantics.” Synthese 22, nos. 1-2 (1970): 18-67. Selected sections.

Lewis, David. “Scorekeeping in a Language Game.” Journal of Philosophical Logic 8, no. 1 (1979): 339-359. Selected sections on presupposition, accommodation, salience, and conversational score.

Recommended readings on LLMs and philosophy of language

Bender, Emily M., and Alexander Koller. “Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data.” Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020): 5185-5198.

Mitchell, Melanie, and David C. Krakauer. “The Debate over Understanding in AI’s Large Language Models.” Proceedings of the National Academy of Sciences 120, no. 13 (2023): e2215907120.

Pepp, Jessica. “Reference without Intentions in Large Language Models.” Inquiry, published online 2025. https://doi.org/10.1080/0020174X.2024.2448482.

Ostertag, Gary. “Language Models and Externalism: A Reply to Mandelkern and Linzen.” Computational Linguistics 51, no. 2 (2025): 651-659.

Butlin, Patrick, and Emanuel Viebahn. “AI Assertion.” Ergo 12 (2025): 968-988. https://doi.org/10.3998/ergo.7960.

Cappelen, Herman, and Josh Dever. Going Whole Hog: A Philosophical Defense of AI Cognition. Version 2, manuscript, 2026. https://philarchive.org/rec/CAPGWH.

Cuskley, Christine, Rebecca Woods, and Molly Flaherty. “The Limitations of Large Language Models for Understanding Human Language and Cognition.” Open Mind 8 (2024): 1058-1083.

Further interdisciplinary reading

Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” Proceedings of FAccT ’21 (2021): 610-623.

Ma, Bolei, et al. “Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges.” Proceedings of ACL 2025 (2025): 8679-8696.

All compulsory readings and the exact passages assigned for each class will be indicated on Virtuale.

Teaching methods

The course combines interactive lectures, guided close reading, argument reconstruction, case analysis, and peer instruction. Before most classes, students read and annotate an assigned text on Perusall. They identify central claims, reconstruct inferential steps, formulate questions, and respond constructively to peers. The instructor uses the annotations to identify recurring difficulties and adapt the following class.

During class, a typical peer-instruction sequence is:

1. a short mini-lecture introduces or clarifies a central distinction or argument;

2. students answer a conceptual question individually through Wooclap;

3. students discuss their reasons in pairs or small groups when responses reveal disagreement or misunderstanding;

4. students answer the same or a closely related question again;

5. the instructor leads a debrief and reconstructs why competing answers succeed or fail.

Wooclap answers are formative and are not graded for correctness. Other activities include argument maps, theory-comparison matrices, analysis of ordinary and AI-generated linguistic examples, guided debates, Moodle exit tickets, and a coordinated activity with Philosophy of Mind on language, thought, and intentionality. Formal-semantic notions are introduced through worked examples, visual representations, and short handouts rather than through advanced proof techniques, type theory, or lambda calculus. Students with a stronger background in logic or linguistics may pursue optional extensions through the recommended readings.

Students with disabilities and Specific Learning Disorders (SLD)

Students with disabilities or Specific Learning Disorders are entitled to special adjustments according to their condition, subject to assessment by the University Service for Students with Disabilities and SLD. Please do not contact teachers or Department staff, but make an appointment with the Service. The Service will then determine what adjustments are specifically appropriate, and get in touch with the teacher. For more information, please visit the page:

https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students

Assessment methods

Oral examination - 40%

The individual oral examination will be conducted jointly with the Philosophy of Mind module and will cover both modules of the integrated Mind & Language course. Students will be required to explain key concepts and theories, reconstruct an argument, compare competing positions, assess objections, apply a theory to a new case, and discuss the central argument of their written reflection.

Short written reflection - 50%

Students must submit an argumentative reflection of approximately 1,500 words in English, including the bibliography, for the Philosophy of Language module. An analogous essay will be required for the Philosophy of Mind module. The paper should connect a classical theory to a contemporary or digital case. It must formulate a clear thesis, reconstruct at least one argument, address at least one objection, draw on at least two academic sources, and include a declaration of any use of generative AI.

Indicative questions include:

• Can a descriptivist or causal-historical theory explain reference in LLM-generated text?

• Does Gricean speaker meaning require a human speaker?

• Can an LLM output be truth-apt without being an assertion by the model?

• Does successful linguistic performance justify the Whole-Hog attribution of understanding, belief, and assertion?

• How should Kaplan’s distinction between character and content be applied to first-person and indexical expressions generated by a chatbot?

• Can an LLM track or update a conversational common ground without being a normatively responsible participant in the conversation?

Documented participation - 10%

Participation is assessed through documented learning activities rather than physical attendance alone: Perusall annotations, constructive replies, Moodle reflections and exit tickets, peer-feedback exercises, and argument-reconstruction tasks. Students who cannot attend regularly complete an equivalent asynchronous pathway with the same outcomes, criteria, and expected workload.

Use of GenAI

Generative AI may be used for brainstorming, outlining, testing objections, formative feedback, and linguistic revision. Students remain responsible for accuracy, originality, sources, and argumentative quality. Any use must be disclosed through a brief statement identifying the tool, stages of use, representative prompts, and the way outputs were checked or revised.

Evaluation criteria

Concerning the essay, the basic criteria for the evaluation are: (i) whether and to what extent the essay shows an adequate knowledge and understanding of the main topics and arguments dealt with in the essay; (ii) whether the essay is adequately structured (as indicated by the guidelines made available during the course); (iii) clarity of exposition and argumentative rigor. Further criteria which, if present, may increase the evaluation are: (iv) some originality in either the content or the argumentative structure; (v) ability to critically assess in an autonomous manner the contents and arguments dealt with in the essay; (vi) ability to connect profitably the topic dealt with in the essay with some of the other topics discussed during the course; (vii) whether the student is able to autonomously perform bibliographical and thematic searches on the topic of the essay.

Concerning the oral part of the exam, the criteria for the evaluation are: (i) the extent to which the student knows and understands in a critical manner the topic of the essay, also in relation to the broader context of the course; (ii) the extent to which the student knows and understands the main topics discussed during the course—other than those discussed in the essay (this will weigh more for those students who didn’t attend the course).


Assessment Grid

30 (cum laude) — Excellent overall performance which demonstrates a solid knowledge as well as a deep and critical understanding of the topics dealt with during the course

30 — Very good overall performance which demonstrates solid knowledge and a very good understanding of the topics dealt with during the course

29-27 — Good overall performance which demonstrates a good knowledge and understanding of the topics dealt with during the course

26-24 — Fair overall performance which demonstrates adequate knowledge and understanding, but with detectable lacunae, of the topics dealt with during the course

23-20 – Sufficient overall performance which demonstrates barely adequate knowledge and understanding, with important lacunae, of the topics dealt with during the course

19-18 — Barely sufficient overall performance which demonstrates a rather superficial knowledge and understanding of the topics dealt with during the course

17 or less – Insufficient overall performance which demonstrates significant failures of understanding as well as absence of knowledge of significant parts of the topics dealt with during the course. Exam failed.

Teaching tools

• Virtuale (Moodle): announcements, slides, handouts, reading guides, accessible materials, assignments, forums, exit tickets, and assessment information.

• Perusall: social reading and collaborative annotation of compulsory texts.

• Formal-semantics and context handouts: worked examples, notation guides, context diagrams, and optional advanced exercises.

• Wooclap: ConcepTests, polls, short answers, retrieval practice, and anonymous formative assessment.

• Slides, argument maps, handouts, and digital whiteboard.

• University of Bologna library databases and electronic resources.

• Instructor-operated demonstrations of LLM outputs for philosophical analysis.

• Accessible digital materials, guiding questions, glossaries, and alternative forms of classroom participation.

Office hours

See the website of Sebastiano Moruzzi