PHIL20640 Philosophy of Mind and AI

Academic Year 2024/2025

What is the nature of the human mind? How are thought and consciousness related to one’s brain and body? How do we know that what we experience is real rather than a convincing simulation or illusion? These foundational questions in the philosophy of mind have returned to the fore in the context of modern ‘machine learning’ systems. These create the possibility of artificially intelligent agents (‘AI’) that aim to replicate 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 these apply to current AI technologies such as autonomous vehicles and Large Language Models (LLMs). While the focus will be on philosophical theories, such as mind–brain identity, psychophysical supervenience, functionalism and mental representation, we will use AI as a test case to explore and advance our understanding of the nature of mind in general.

Note: No prior knowledge of AI systems is required or assumed, though the module will require the use of AI systems, for which instruction will be provided, including for assessment purposes.

May be taken as part of the Philosophy of Mind and Science structured elective. For details, go to https://www.ucd.ie/students/registration/structuredelectives/philosophyofmindandscience/

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Curricular information is subject to change

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:

• 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?
• Could reality be a simulation? If so, how would we know?
• Do Large Language Models like ChatGPT hallucinate?

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 using a mixture of weekly 1-hour lectures, 1-hour tutorials (from Week 2), in-class discussion, and independent reading and reflection. As part of the module, students will be required to make use of one or more AI systems, including for assessment purposes. 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
Incompatibles:
PHIL31000 - Philosophy and Ethics of AI


 
Assessment Strategy  
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): Submit two (or more) graphical memes plus textual explanations illustrating philosophical points covered in the module Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11, Week 12 Graded No

25

 Yes
Assignment(Including Essay): 1,000-word essay critiquing an AI-generated text Week 7 Graded No

25

 Yes
Assignment(Including Essay): 2,000-word essay, plus additional supporting materials, which could include images, news articles, video and/or notes Week 14 Graded No

50

 Yes

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.