This module can accommodate up to 20 students consisting of both Part II students and MPhil / Part III Students
Aims
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.
Lectures
(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
Objectives
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.