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Philosophy of Artificial Intelligence

Code: 100315 ECTS Credits: 6
2025/2026
Degree Type Year
Philosophy OT 3
Philosophy OT 4

Contact

Name:
Jordi Vallverdú Segura
Email:
jordi.vallverdu@uab.cat

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

None.


Objectives and Contextualisation

"Philosophy of Artificial Intelligence" is a course designed for curious students who want to go beyond the clichés about AI. Throughout the course, we will analyze how the ideas of computation, algorithms, and intelligent machines came into being; how logic and formal languages have helped shape the digital world; and what it truly means for a system to understand language — or merely simulate it. We will also explore why large language models, like ChatGPT, raise new philosophical challenges, and how all of this impacts society, knowledge, and ethical decisions in both the present and the future.

You don’t need to know how to code — only a strong desire to think deeply and to put philosophy to work on real-world technology.


Competences

    Philosophy
  • Students must have and understand knowledge of an area of study built on the basis of general secondary education, and while it relies on some advanced textbooks it also includes some aspects coming from the forefront of its field of study.
  • Using the symbology and procedures of the formal sciences in the analysis and building of arguments.

Learning Outcomes

  1. Establishing relationships between science, philosophy, art, religion, politics, etc.
  2. Explaining the specific notions of the History of Philosophy.
  3. Formulating arguments for and against an issue, using proper vocabulary, conceptual precision and argumentative coherence.
  4. Recognising and using the several forms of reasoning in the history of philosophy.
  5. Regularising arguments of any source and calculating its logical correctness.
  6. Rigorously building philosophical arguments.

Content

Module I: Historical and Conceptual Foundations

  1. Calculation, Censuses and Control: From Leibniz to Babbage

  2. Logic, Machines and Formalisation (Frege, Boole, Peano, Hilbert)

  3. Turing, Church and Computability

  4. Von Neumann Architecture and Classical Computing

  5. Quantum Computing and Philosophical Implications

  6. Statistics and Prediction in Intelligent Systems

Module II: Philosophy of Computation
7. What is an Algorithm?
8. Programming Languages and Logic (Lisp, Prolog)
9. Computational Models of Mind (Functionalism, Searle, Dreyfus)

Module III: AI and Philosophy
10. History of AI: From McCarthy to AlphaGo
11. Ethics of AI: Bias, Accountability, Gender Impacts
12. Consciousness and Intentionality

Module IV: Philosophy of LLMs
13. What is a LLM? (Transformers, embeddings)
14. Philosophical Critiques (Stochastic Parrots, Bender, Semantics)
15. Epistemology of Generative AI

Module V: Contemporary Perspectives
16. Philosophical Debates on AGI
17. Biologically-Inspired and Neurodiverse AI
18. Neuro-symbolic AI (Hybrid Systems)
19. Cyberculture and Emerging Technologies
20. Conclusions: Towards a Critical Philosophy of Computation


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Philosophical Creativity Workshop with AI (experimentation with prompting, the role of AI as author) 40 1.6 6, 2, 3, 4
Type: Supervised      
Study of the technical and philosophical foundations of AI and knowledge representation (key concepts, faculty supervision) 44 1.76 6, 2, 5
Type: Autonomous      
Reading texts of Philosophy of the AI 34 1.36 6, 1, 4

The methodology of this course combines lectures, participatory seminars, and guided practical activities, with a strong emphasis on active philosophical analysis and the explicit use of artificial intelligence as an epistemological tool.


Lectures will introduce the fundamental concepts and the historical-philosophical context.

Through weekly guided readings, students will practice critical reading, conceptual analysis, and collective debate.

The written assignment, developed with ChatGPT, will encourage philosophical experimentation with AI tools, requiring transparency in prompting and reflection on their application.

Exams will assess deep understanding of the content and the ability to apply it in a reasoned manner.

The course promotes active participation, a critical attitude, and a cross-disciplinary perspective on the role of computing and artificial intelligence in contemporary society.

 

This subject allows the use of AI technologies as an integral part of the submitted work, provided that the final result reflects a significant contribution from the student in terms of
analysis and personal reflection. The student must clearly (i) identify which parts have been generated using AI technology; (ii)
specify the tools used; and (iii) include a critical reflection on how these have influenced the process and final outcome of the activity.
Lack of transparency regarding the use of AI in the assessed activity will be considered academic dishonesty; the corresponding grade may be lowered, or the work may even be awarded a zero.
In cases of greater infringement, more serious action may be taken.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Written work with AI (ChatGPT) 25 8 0.32 6, 2, 5, 3
Commented readings and philosophical debate 25 8 0.32 6, 1, 5, 4
Final exam: critical synthesis 25 8 0.32 6, 1, 2, 3, 4
Midterm exam: philosophical analysis and application 25 8 0.32 6, 1, 3

1. Weekly Guided Readings (25%)
Students will read key philosophical texts (Turing, Searle, Bender, etc.) and are expected to actively participate in guided class discussions.

Assessment criteria:

  • Text comprehension

  • Analytical and argumentative skills

  • Participation in collective debate

2. Written Assignment with ChatGPT (25%)
Individual paper (2,500–4,000 words) developed using ChatGPT.

The full conversation thread must be included as an appendix.

Assessment criteria:

  • Critical ability to analyze, complement, or correct AI responses

  • Prompting level, density, and sophistication

  • Philosophical clarity and original reflection

  • Transparency and justification of the interaction process with the AI

3. Midterm Exam (25%)
In-person written test held mid-course.

Open-ended questions, definitions, comparisons, and analysis of philosophical cases.

4. Final Exam (25%)
Final in-person exam with open-ended questions or critical commentary on texts.

It is possible that the Department of Philosophy will establish (as will be done during the first semester) a period dedicated to evaluative tests. The teaching staff will indicate whether such a period exists or what the test dates are at the beginning of each course.

 

Single Assessment

Students who choose the single assessment option will be required to complete a comprehensive final exam at the end of the semester. This exam is designed to assess their overall understanding and critical engagement with the course content.

The exam will include:

  • Multiple questions (both long-form and analytical) covering each and every topic from the syllabus.

  • Particular emphasis will be placed on:

    • Philosophical dimensions (ontological, epistemological, and metaphysical issues related to AI),

    • Ethical and social questions arising from the deployment of intelligent systems,

    • Logical and computational aspects, including concepts such as algorithms, computational architectures, neural networks, and formal logic as they relate to AI.

The exam will be in person, will last two and a half hours, and will be held during the official final assessment period.

This single assessment will cover the full range of competencies and learning outcomes stated in the course guide, under conditions equivalent to those of continuous assessment.


Bibliography

Philosophy of Computation and AI

  • Boden, M. A. (2016). AI: Its Nature and Future. Oxford University Press.

  • Copeland, J. (1993). Artificial Intelligence: A Philosophical Introduction. Wiley‑Blackwell.

  • Dennett, D. (1991). Consciousness Explained. Little, Brown and Company.

  • Floridi, L. (2011). The Philosophy of Information. Oxford University Press.

  • Searle, J. (1980). Minds, Brains and Programs. Mind, 89(4), 417–424.

  • Smith, B. C. (1996, 2019). On the Origin of Objects / The Promise of Artificial Intelligence. MIT Press.

  • Vallverdú, J. (2024). Causality for Artificial Intelligence: From a Philosophical Perspective. Springer.

Ethics and Society

  • Bender, E. et al. (2021). On the Dangers of Stochastic Parrots. FAccT.

  • Coeckelbergh, M. (2018). Ethics of Artificial Intelligence. Cátedra.

  • Coeckelbergh, M. (2022). Robo Ethics. MIT Press.

  • Crawford, K. (2021). Atlas of AI. Yale University Press.

Logic, Epistemology, and Language

  • Smith, N. J. J. (2013). Vagueness and Degrees of Truth. Oxford University Press.

  • Van Benthem, J. (2000). Modal Logic for Open Minds. CSLI.

  • Van Benthem, J., Van Ditmarsch, H., Van Eijck, J., Jaspars, J. (2016). Logic in Action. CSLI.


Software

None.


Groups and Languages

Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.

Name Group Language Semester Turn
(PAUL) Classroom practices 1 Catalan first semester morning-mixed
(TE) Theory 1 Catalan first semester morning-mixed