Interaction with Machine Learning
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, and for registered students to access the Zoom link for seminars. Moodle course: Interaction with Machine Learning 2020-21
Introductory Lecture
Lecture 1: Alan Blackwell and Advait Sarkar - structure of course, overview of HCI, major themes in IUI/TIIS, HCI research methods, planning your study (Presentation slides)
Thematic Lectures
- 2 February: Mixed initiative interaction (AB) [Slides for Lecture 2]
- 9 February: Labelling as a fundamental problem (AS) [Slides and lecture notes for Lectures 3 and 5]
- 16 February: Program synthesis (AB) [Slides for Lecture 4]
- 23 February: Visualisation and visual analytics (AS) [Slides and lecture notes for Lectures 3 and 5]
- 2 March: Addressing data bias (Dr Daniela Masiceti, Microsoft Research) [Powerpoint (including some embedded video) for Lecture 6]
- 9 March: Interpretability (Prof Neil Lawrence) [Slides with notes]
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:
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.
- Ben Shneiderman (2020). Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy
- Brad A. Myers and Richard McDaniel (2000). Demonstrational Interfaces: Sometimes You Need a Little Intelligence, Sometimes You Need a Lot
- Alan F. Blackwell (2015). Interacting with an Inferred World: The challenge of machine learning for humane computer interaction.
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.
- Predictive Text Encourages Predictable Writing
- The Effect of User Characteristics in Time Series Visualizations
- Recommendation for Video Advertisements based on Personality Traits and Companion Content
- When People and Algorithms Meet: User-reported Problems in Intelligent Everyday Applications
- BigBlueBot: Teaching Strategies for Successful Human-Agent Interactions
- Explanations as Mechanisms for Supporting Algorithmic Transparency
Background in HCI
Teaching materials (including video lectures in 2021) for the
research-oriented Cambridge undergraduate course in 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.
Online review form
(Note that access to this form requires login to department VPN. Undergraduates please prepare answers using the
read-only version,
then ask one of the lecturers to submit on your behalf.)
As described on the form, you should also 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.
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.