PHIL31000 Philosophy and Ethics of AI

Academic Year 2023/2024

This module offers an introduction to and critical assessment of the Philosophy and Ethics of AI.

It asks questions such as:
- Are machines capable of thought and action?
- Are machine learning models genuinely intelligent or are they just clever mimics?
- Is it morally acceptable to place people’s lives in the hands of a computer program, and if so who is responsible for the outcome?

The advent of artificial intelligence, or AI, is forcing us to rethink how we live, work, learn, and communicate. Some predict that it will bring about social change on a scale not seen since the industrial revolution, or that AI constitutes an existential threat to humankind. In this module we will examine some of the philosophical issues that arise from the use of AI technologies in order to better understand and evaluate the risks and opportunities that they present. It will include issues in the philosophy of mind and cognitive science concerning the nature of mind and intelligence, and in applied ethics, such as how to develop and apply ethical frameworks to AI systems and the values that they encode.

Sample questions that may be covered include:
• Could a machine understand or be conscious?
• Do AI systems think and reason like we do, or do they possess a different form of intelligence from humans?
• Will the values of AI systems align with human interests, or could they develop their own (potentially hostile) agenda?
• How can we prevent machine learning algorithms from acquiring morally objectionable
biases?

Note: this module will require use of AI systems, including for assessment purposes, for which instruction and guidance will be given. No prior familiarity with AI is assumed.

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Curricular information is subject to change

Learning Outcomes:

Students who successfully complete this course will have:
(1) a good grasp of some central issues in the philosophy and ethics of AI
(2) engaged critically with some important views and arguments in this area, and
(3) developed their own independent thoughts and arguments concerning some of those
issues.

Indicative Module Content:

In this module we will examine some of the philosophical issues that arise from the use of AI technologies in order to better understand and evaluate the risks and opportunities that they present. It will include issues in the philosophy of mind and cognitive science concerning the nature of mind and intelligence, and in applied ethics, such as how to develop and apply ethical frameworks to AI systems and the values that they encode.

Sample content and questions that may be covered include:
• Could a machine understand or be conscious?
• Do AI systems think and reason like we do, or do they possess a different form of intelligence from humans?
• Will the values of AI systems align with human interests, or could they develop their own (potentially hostile) agenda?
• How can we prevent machine learning algorithms from acquiring morally objectionable
biases?

Note: this module will require use of AI systems, including for assessment purposes, for
which instruction and guidance will be given. No prior familiarity with AI is assumed.

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Tutorial

7
Autonomous Student Learning

94
Total

125
Approaches to Teaching and Learning:
The module is taught through a mixture of lectures, tutorials and interactive discussion in which students are encouraged to develop their own views and arguments in response to the material covered in the lectures and the portrayal of AI in the media, science-fiction and entertainment. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Assignment due at the end of the Trimester Coursework (End of Trimester) n/a Graded No

50
Continuous Assessment: Participation and attendance in tutorials, assessed by submission of short questions for discussion in tutorials, consisting of 10% of the final mark. Throughout the Trimester n/a Graded No

10
Assignment: Assignment due in week 8 Week 8 n/a Graded No

40

Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring 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

How will my Feedback be Delivered?

Feedback will be given to individually to students post-assessment.

Name Role
Dr Silvia Ivani Lecturer / Co-Lecturer
Samuel Ferns Tutor
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) - Autumn: All Weeks Tues 15:00 - 15:50
Lecture Offering 1 Week(s) - Autumn: All Weeks Wed 15:00 - 15:50
Tutorial Offering 1 Week(s) - 3 Tues 14:00 - 14:50
Tutorial Offering 1 Week(s) - 4, 5, 6, 7, 8, 9, 10 Tues 14:00 - 14:50
Tutorial Offering 2 Week(s) - 3, 4, 5, 6, 7, 8, 9, 10 Mon 14:00 - 14:50
Autumn