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COMP41740

Academic Year 2024/2025

Human-Centred AI (COMP41740)

Subject:
Computer Science
College:
Science
School:
Computer Science
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Assoc Professor David Coyle
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This is an advanced course in Human-Computer Interaction, with a focus on intelligent user interfaces and interaction with machine-learning and artificial intelligence technologies.

Human-Centered AI (HCAI) is an emerging discipline focused on creating AI systems that amplify and augment rather than displace human abilities. It build on the fields of Human Computer Interaction and Artificial Intelligence and emphasises the development of artificial intelligence technologies that prioritize human needs, values, and capabilities. HCAI seeks to preserve human control in a way that ensures artificial intelligence meets our needs while also operating transparently, delivering equitable outcomes, and respecting privacy. HCAI aims to ensure that AI systems enhance human abilities and well-being rather than replacing or diminishing human roles.

This module addresses the development of HCAI systems and examines how AI and humans communicate and collaborate. Importantly it also addresses the ethical, social, and cultural implications of AI and how we ensure AI systems are accessible, usable, and beneficial to all segments of society.

The format will be both theoretical and practical. It will involve assigned reading based on recent research publications and books in HCAI. It also mini-projects involving empirical research investigation. These studies will investigate human interaction with some kind of model-based system for planning, decision-making, automation etc. Possible study formats might include: system evaluations, controlled experiments, or a design intervention. Project work will be formally evaluated through a report and presentation. Reading assignments will be examined through written submissions and a final exam.

Topics covered will include:
Design strategies HCAI
Human AI collaboration
Fairness, bias and transparency
Interpretability / explainable AI
Evaluation strategies for HCAI

About this Module

Learning Outcomes:

An understanding of the current state of the art in Human Centred AI
An understanding of the human factors critical in the design of such systems
Be able to identify and apply appropriate design techniques for HCAI
Be able to identify and apply appropriate evaluations techniques for HCAI
Be able to design and implement controlled experiments and users studies for HCAI
Be able to write up and present user research in a professional manner

Indicative Module Content:

The module will be partially based on the following book:
Shneiderman, B. (2022). Human-centered AI. Oxford University Press.

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Specified Learning Activities

48
Autonomous Student Learning

48
Total

120

Approaches to Teaching and Learning:
Lectures
Practicals and discussion groups
Assigned reading

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Additional Information:
This is an advanced module cover aspects of in Human Computer Interaction and Artificial Intelligence. It is recommended the students taking the module have previously undertaking an introductory module in at least one of these subjects.


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): The final exam is based on assigned reading and lecture materials. Week 12 Graded No
40
 No
Assignment(Including Essay): Individual reports on assigned reading will be submitted throughout the semester. Week 3, Week 5, Week 7, Week 9, Week 11 Graded No
20
 No
Group Work Assignment: Students will work on a group assignment throughout the semester, focus on user studies and empirical evaluation of Human-AI systems. Week 6, Week 11 Graded No
40
 No

Carry forward of passed components
No
 

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
• Peer review activities
• Self-assessment activities

How will my Feedback be Delivered?

Not yet recorded.

The module will be partially based on:
Shneiderman, B. (2022). Human-centered AI. Oxford University Press.

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 Fri 11:00 - 11:50
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 14:00 - 14:50
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