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PHIL20640

Academic Year 2025/2026

Philosophy of Mind and AI (PHIL20640)

Subject:
Philosophy
College:
Social Sciences & Law
School:
Philosophy
Level:
2 (Intermediate)
Credits:
5
Module Coordinator:
Dr Keith Wischmann Wilson
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

What is the nature of the mind? How are thought and consciousness related to the brain and body? How do we know that what we experience is real rather than a convincing illusion or simulation? These foundational questions in the philosophy of mind have returned to the fore in the context of modern machine-learning or ‘AI’ systems. Such systems create the possibility of artificially intelligent agents that aim to replicate or replace various aspects of human thought and behaviour.

This module will provide an introduction to these debates by examining foundational issues in the philosophy of mind concerning the nature of thought, consciousness and intelligence, and how they apply to current AI technologies such as autonomous vehicles and Large Language Models (LLMs). Though the focus will be on philosophical theories, such as mind–brain identity, psychophysical supervenience, functionalism and mental representation, we will explore AI as a test case to help sharpen and advance our understanding of the mind.

Note: If you are taking this module as an elective you may be interested in pursuing a Structured Elective programme in Philosophy (this will entail taking two more Philosophy electives). Your University Transcript could show that you have a Structured Elective in either Existential Philosophy & Critical Theory or Philosophy of Mind & Science depending on which other electives you choose. See https://www.ucd.ie/students/registration/structuredelectives/ for details.

About this Module

Learning Outcomes:

Students who successfully complete this module will:

(1) have a good grasp of some central issues in contemporary philosophy of mind and AI
(2) have engaged critically with the most important views and arguments in this area, and
(3) have developed some independent thoughts and arguments on those issues.

Indicative Module Content:

Sample questions that may be covered in this module include:

• What is the mind and how does it relate to the physical world?
• Why do conscious experiences feel the way that they do—or any way at all?
• Are mental states representational? If so, what and how do they represent?
• Do AI systems think and reason like we do, or do they possess some other kind of intelligence?
• How does machine learning differ from human learning?
• Do Large Language Models like ChatGPT hallucinate?
• What, if anything, can we learn from human-like AI about the human mind?

Student Effort Hours:
Student Effort Type Hours
Specified Learning Activities

50
Autonomous Student Learning

50
Lectures

12
Tutorial

11
Total

123

Approaches to Teaching and Learning:
The module will be taught via a combination of weekly 50-minute interactive lectures, during which students are encouraged to ask questions and raise issues of interest; weekly 50-minute tutorials (from Week 2) which will focus on discussing the set readings for each week illustrating key concepts from the lecture; plus independent reading and reflection. To successfully complete the module, students are expected and advised to participate fully in all three components.

As part of the module, students may be required to make use of one or more AI systems, and in accordance with UCD’s academic integrity guidelines. Further instructions and guidance will be given for this, and no prior familiarity with Philosophy of Mind or AI is required or assumed.

Requirements, Exclusions and Recommendations
Learning Requirements:

No prior knowledge of AI systems is required or assumed, though the module will require the use of some AI systems, including for assessment purposes, for which further guidance will be given.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Participation in Learning Activities: Participation in tutorial activities and discussion Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11, Week 12 Alternative linear conversion grade scale 40% No
15
 No
Assignment(Including Essay): Graphical meme or other creative work plus a short textual explanation illustrating a philosophical point covered in Weeks 1–6 of the module Week 6 Graded No
15
 No
Assignment(Including Essay): Short (up to 800 word) philosophical critique of an AI-generated text, which will be provided Week 8 Graded No
10
 No
Assignment(Including Essay): Graphical meme or other creative work plus short textual explanation illustrating a philosophical point covered in Weeks 7–12 of the module Week 12 Graded No
15
 No
Assignment(Including Essay): Approx. 1,500-word essay plus notebook, which may include images, news articles, sound or video recordings, and/or rough work Week 14 Graded No
45
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Peer review activities

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Keith Wilson Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 12:00 - 12:50
Spring Tutorial Offering 1 Week(s) - 21, 23, 24, 25, 26, 29, 30, 33 Mon 15:00 - 15:50
Spring Tutorial Offering 1 Week(s) - 31 Thurs 15:00 - 15:50
Spring Tutorial Offering 1 Week(s) - 32 Thurs 15:00 - 15:50
Spring Tutorial Offering 1 Week(s) - 22 Tues 15:00 - 15:50
Spring Tutorial Offering 2 Week(s) - 21, 23, 24, 25, 26, 29, 30, 33 Mon 16:00 - 16:50
Spring Tutorial Offering 2 Week(s) - 31 Thurs 16:00 - 16:50
Spring Tutorial Offering 2 Week(s) - 32 Thurs 16:00 - 16:50
Spring Tutorial Offering 2 Week(s) - 22 Tues 16:00 - 16:50
Spring Tutorial Offering 4 Week(s) - 21, 23, 24, 25, 26, 29, 30, 33 Mon 13:00 - 13:50
Spring Tutorial Offering 4 Week(s) - 31 Thurs 13:00 - 13:50
Spring Tutorial Offering 4 Week(s) - 32 Thurs 13:00 - 13:50
Spring Tutorial Offering 4 Week(s) - 22 Tues 13:00 - 13:50
Spring Tutorial Offering 5 Week(s) - 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 11:00 - 11:50
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