skip to primary navigationskip to content
 

Course pages 2022–23

Interaction with Machine Learning

Course structure

This practical course includes 8 2-hour contact sessions. For most sessions, the first hour will be a lecture on a thematic topic related to the course, and the second hour will involve discussion of practical work in progress. The first 2-hour session is dedicated to a practical and theoretical overview of the coruse, and the final 2-hour session is dedicated to presentation of individual research results.

Moodle Link

Note that we do not expect to place any of the course content in Moodle. This link will be used for submission of assignment work. Moodle course: Interaction with Machine Learning 2022-23

Introductory session

11 October: Alan Blackwell and Advait Sarkar - structure of course, overview of HCI, major themes in IUI/TIIS, HCI research methods, planning your study

Timetable for thematic lectures

  • 18 October: Mixed initiative interaction (AB)
  • 25 October: Labelling as a fundamental problem (AS)
  • 1 November: Program synthesis (AB)
  • 8 November: Visualisation and visual analytics (AS)
  • 15 November: Bias and fairness (AB)
  • 22 November: Explainability (Guest lecture from Simone Stumpf, University of Glasgow)

Final session

29 November: Research presentations (all students)

Lecture Slides (will be uploaded after each lecture)

Publication format

Your reports can follow formatting instructions given in the call for papers for the IUI 2021 conference.

Readings

Annotated reading list of relevant publications:

Scanning recent publications at ACM IUI and TIIS will give a useful overview of methods currently used in the field. Archives of both are available on the ACM digital library:

Books:

Recent research overviews

  • Dudley, J. J., & Kristensson, P. O. (2018). A Review of User Interface Design for Interactive Machine Learning. ACM Transactions on Interactive Intelligent Systems, 8(2), 1–37. https://doi.org/10.1145/3185517
  • Abdul, A., Vermeulen, J., Wang, D., Lim, B. Y., & Kankanhalli, M. (2018). Trends and Trajectories for Explainable, Accountable and Intelligible Systems. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18, 1–18. https://doi.org/10.1145/3173574.3174156

Background reading, in which senior figures in HCI reflect on the overall themes addressed by this course.

Candidate replication studies (Part II only)

The following papers address themes that are relevant to the course, and use research methods that are appropriate to the practical component. In most cases, a Part II student would not have access to all the resources (e.g. large sample sizes, large datasets, significant custom software development) to allow full replication of one of these research projects. We therefore expect you to select one part of a study, a reduced number of conditions and/or measurements, and substantially smaller sample sizes. Your research question submission should explain what adaptations you plan to make.

Background in HCI

Teaching materials (including video lectures in 2021) for the research-oriented Cambridge undergraduate course in Further HCI can be found here:
https://www.cl.cam.ac.uk/teaching/2021/FHCI/

Conduct of research

Before starting your study with human participants, you must make an application to the Computer Lab ethics committee, describing what you plan to do and how you will remove or mitigate any risks.

As described on the application form for ethical review, you should consult the Cambridge Guidance on technology research with human participants, paying particular attention to the type of study you will be conducting, the risks associated with that kind of study, and how you will address them.

Online ethical review form

This form is accessed via the local VPN for computer science department research ("VPN2", not the University-wide VPN provided for other students). All master's students should have installed VPN2 using these instructions. Note that the local server authentication requested by the review form uses your CRSID as username, but the password is your department password (as used for department research facilities such as Kerberos authentication), not your Raven password (as used to access many University-wide IT services).

If master's students are struggling with VPN installation or their department login, send email to the ethics committee secretary including all information requested on the form, as specified in this read-only version of the form. Undergraduate students may send this information directly to AB, who will arrange this on their behalf.

Material from previous years

Much of the content this year will follow the format used for MPhil/Part III module P230 in previous years. Readers wishing to see any of this in advance are welcome to refer to material from previous years.