IS41080 AI, Ethics & Auditing

Academic Year 2023/2024

Artificial Intelligence is presenting urgent ethical questions and is currently the focus of much attention from both government and industry. This module explores foundational ethical issues such as the relationship between AI and human autonomy, ethical frameworks, bias and discrimination in AI. This course takes a multidisciplinary viewpoint incorporating concepts from a range of disciplines including social science, philosophy, law and computing. Solutions to ethical issues will be examined from a theoretical, technical and regulatory perspective. The aim of this module is to equip students with the skills and expertise to understand the source of ethical issues in AI, potential solutions and critically examine the ethical implications of AI systems. Students will learn how to conduct a comprehensive ethical audit of an AI systems.

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module students should be able to:

1. Demonstrate an understanding of key concepts in ethical AI
2. Describe the state of the art in addressing issues of bias from a theoretical, technical and regulatory perspective
3. Critically evaluate the ethical implications of an AI system
4. Engage in contemporary debates in the field of ethical AI
5. Conduct a formal ethical audit of an AI system

Student Effort Hours: 
Student Effort Type Hours
Lectures

40

Autonomous Student Learning

260

Total

300

Approaches to Teaching and Learning:
This module is a 2-week intensive module. The course will be delivered through a combination of lectures and workshop sessions. 
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: Project - Design an Audit for a Proposed AI System. Involves a state of the art review of existing approaches and building on these to design a bespoke ethics audit of a specific kind of AI system.
Unspecified n/a Graded No

100


Carry forward of passed components
No
 
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

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Marion Bartl Lecturer / Co-Lecturer
Dr Thompson Kwarkye Lecturer / Co-Lecturer
Abhishek Mandal
Lecturer / Co-Lecturer
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Summer
     
Lecture Offering 51 Week(s) - 37, 38 Fri 10:00 - 15:50
Lecture Offering 51 Week(s) - 37, 38 Mon 10:00 - 15:50
Lecture Offering 51 Week(s) - 37, 38 Thurs 10:00 - 15:50
Lecture Offering 51 Week(s) - 37, 38 Tues 10:00 - 15:50
Lecture Offering 51 Week(s) - 37, 38 Wed 10:00 - 15:50
Summer