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COMP3647: Human-AI Interaction Design

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type Open
Level 3
Credits 10
Availability Available in 2023/24
Module Cap None.
Location Durham
Department Computer Science


  • COMP2261 Artificial Intelligence


  • None

Excluded Combinations of Modules

  • None


  • To discuss how the design of Human-AI interactions may affect user experience.
  • To introduce methods and tools for designing interactive AI systems.
  • To develop ethical and societal principles in the design of interactive AI systems.


  • AI and User Experience
  • Human-Centred AI Design
  • Human-AI Communication Channels
  • Inclusive Design and Digital Accessibility
  • Explainable AI and Building Trust
  • Privacy and Security Considerations
  • Affective Design for Interactive AI
  • Psychophysical Methods
  • Ambient Intelligence
  • Applications (e.g. gaming, healthcare, education, finance, automotive vehicles, etc.)

Learning Outcomes

Subject-specific Knowledge:

  • An understanding of impacts of interactive AI system design on user experience.
  • An understanding of concepts and principles of Human-AI interaction design.

Subject-specific Skills:

  • An ability to apply concepts and principles of Human-AI interaction design.
  • An ability to conduct experiments for assessing interactive AI systems.

Key Skills:

  • An ability to propose interactive AI solutions to real-world problems.
  • Awareness of ethical and societal considerations in building interactive AI systems.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lectures enable students to learn new materials relevant to Human-AI interaction design and evaluation, as well as their applications in the real-world.
  • Formative and summative assessments assess students' knowledge and skills of using Human-AI interaction principles, methods and tools in individual projects.

Teaching Methods and Learning Hours

lectures202 per week1 hour20 
preparation and reading80 

Summative Assessment

Component: CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Summative assignment 100No

Formative Assessment

Example formative exercises are given during the course.

More information

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