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Department of Computer Science and Technology

Principal lecturer: 
Other lecturers: 
Part II CST 75%
Lent term
Course code: 

This module can accommodate up to 20 students consisting of both Part II students and MPhil / Part III Students


This is an advanced course in human-computer interaction, with a specialist focus on intelligent user interfaces and interaction with machine-learning and artificial intelligence technologies. The format will be largely Practical, with students working in pairs to carry out a mini-project 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 evaluation, Field observation, Hypothesis testing experiment, Design intervention or Corpus analysis, following set examples from recent research publications. Project work will be formally evaluated through a report and presentation.


(note that Lectures 2-7 also include one hour class discussion of practical work)
        • Current research themes in intelligent user interfaces
        • Program synthesis
        • Mixed initiative interaction
        • Interpretability / explainable AI
        • Labelling as a fundamental problem
        • Machine learning risks and bias
        • Visualisation and visual analytics
        • Student research presentations


By the end of the course students should:
        • be familiar with current state of the art in intelligent interactive systems
        • understand the human factors that are most critical in the design of such systems
        • be able to evaluate evidence for and against the utility of novel systems
        • have experience of conducting user studies meeting the quality criteria of this field
        • be able to write up and present user research in a professional manner

Recommended reading

Brad A. Myers and Richard McDaniel (2000). Demonstrational Interfaces: Sometimes You Need a Little Intelligence, Sometimes You Need a Lot.