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PHIL20640

Academic Year 2026/2027

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:
Autumn
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 physical body and brain? How do we know that experience is real rather than a convincing illusion or simulation? These and other foundational questions in the philosophy of mind have returned to the fore in the context of modern ‘machine learning’ or ‘AI’ systems. Such systems raise the possibility of artificially intelligent agents that aim to replicate or even replace various aspects of human thought and behaviour, despite being physically very unlike us.

This module will provide an introduction to these contemporary debates by examining foundational issues in the philosophy of mind concerning the nature of thought, consciousness and intelligence, and how these apply to current AI technologies such as machine learning (ML) and Large Language Models (LLMs). The focus will be on philosophical theories, such as physicalism, intentionality, externalism, and the extended mind, that enable us to explore AI as a test case to sharpen and advance our understanding of the mind, brain and body.

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 brain and body?
• 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?
• Are thoughts purely ‘in the head’, or does the mind extend into the surrounding environment?
• Can 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?
• What, if anything, can we learn from human-like AI about our own minds?

The United Nations identified seventeen Sustainable Development Goals (SDGs) as core to the 2030 Agenda for Sustainable Development, and UCD contributes in general to SDG 4 Quality Education. Further SDGs explored within this module if relevant are listed below. A scale of 1 - 5 indicates the extent to which the SDG is covered.


 

Student Effort Hours:
Student Effort Type Hours
Lectures

11
Tutorial

10
Specified Learning Activities

35
Autonomous Student Learning

70
Total

126

Approaches to Teaching and Learning:
The module will be taught via a combination of: (1) weekly 50-minute lectures, during which students are encouraged to ask questions and raise issues of interest; (2) weekly 50-minute tutorials (from Week 2) which will focus on discussing a set reading for each week illustrating some key concepts from the lecture; (3) independent reading and reflection. To successfully complete the module, students are advised and expected to participate fully in all three of these components.

No use of AI is required for this module, though some assignments may permit students to use of AI systems 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 does not require the use AI systems, some assignments may permit the use of AI for specific purposes only, and in accordance with UCD and School of Philosophy Academic Integrity policies. Further instructions and guidance on this will be given by the Module Co-ordinator.


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
Assignment(Including Essay): Short (750-word) critique of an AI-generated text, which will be provided, with peer feedback Week 6, Week 7 Graded No
25
 No
Assignment(Including Essay): Graphical meme or other creative work plus short textual explanation illustrating a philosophical point covered in the module Week 11 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 personal reflection Week 14 Graded No
45
 No
Participation in Learning Activities: Participation in tutorial activities and discussion Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 9, Week 10, Week 11, Week 12 Alternative linear conversion grade scale 40% No
15
 No

As part of UCD's student support, under the Additional Consideration policy, extensions may be available for the following assessments in the module: Assignment (including essay/poster), Portfolio, Reflective Assignment, Report(s), and Individual Project.


Carry forward of passed components
No
 

Resit In Terminal Exam
Spring Yes - 2 Hour
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.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 11, 12 Wed 10:00 - 10:50
Autumn Lecture Offering 1 Week(s) - 6 Wed 10:00 - 10:50
Autumn Lecture Offering 1 Week(s) - 7 Wed 10:00 - 10:50
Autumn Lecture Offering 1 Week(s) - 9, 10 Wed 10:00 - 10:50
Autumn Tutorial Offering 1 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Tues 10:00 - 10:50
Autumn Tutorial Offering 2 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Tues 16:00 - 16:50
Autumn Tutorial Offering 3 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Tues 13:00 - 13:50
Autumn Tutorial Offering 4 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 13:00 - 13:50
Autumn Tutorial Offering 5 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 10:00 - 10:50
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