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IS41120

Academic Year 2021/2022

AI Ethics (IS41120)

Subject:
Information Studies
College:
Social Sciences & Law
School:
Information & Comms Studies
Level:
4 (Masters)
Credits:
10
Module Coordinator:
Dr Susan Leavy
Trimester:
Summer
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

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.

About this Module

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

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

160
Lectures

40
Total

200

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 In Module Component Repeat Offered
Assignment: Survey of ethical issues in artificial intelligence Unspecified n/a Graded No
15
 No
Assignment: Literature review - theoretical approaches to AI ethics Unspecified n/a Graded No
15
 No
Assignment: Survey of existing toolkits/audits for ethical AI Unspecified n/a Graded No
15
 No
Assignment: Project - ethical evaluation of AI system Unspecified n/a Graded No
55
 No

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.

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