Practical Research in Human-centred AI

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 course, and the final 2-hour session is a mini-conference, during which all students make short presentations of their 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: Practical Research in Human-centred AI

Introductory session

15 October: Alan Blackwell and Advait Sarkar - structure of course, overview of HCAI, planning your study

Timetable for thematic lectures

• 22 October: Mixed initiative interaction (AB)
• 29 October: Labelling as a fundamental problem (AS)
• 5 November: Program synthesis (AB)
• 12 November: Generative AI (AS)
• 19 November: Bias and fairness (AB)
• 26 November: Explainability (Guest lecture - Simone Stumpf)

Final session

3 December: Research mini-conference (all students)

Lecture Slides (will be uploaded after each lecture)

• Lecture 1 course overview and study planning
• Research design (2023 Research Skills unit)
• Lecture 2 - Mixed initiative interaction
• Lecture 3 - Labelling (and visualisation)
• Lecture 4 - Program synthesis
• Lecture 5 - Generative AI
• Lecture 6 - Fairness and bias
• Lecture 7 - Explanation (Stumpf)
• Mini-conference presentation slides

Publication format

Your final reports should follow formatting instructions given for the "Short Paper" format in the call for papers of the CHI 2025 conference.

Draft submissions can be in any format you find convenient. Each weekly draft should also include the text from all previous weeks for convenient reference, but formatted in a light grey colour. Feedback will be given each week on new text, and on specific revisions to earlier drafts. New content and specific revisions should be formatted as black text, so we can see what requires feedback.

Readings

Reading list of publications relevant to each lecture.

Books:

• The closest to a book of this course (but written for the general public, not as a textbook) is Alan Blackwell's Moral Codes: Designing alternatives to AI. (MIT Press, 2024)
• A more policy-oriented introduction to HCI perspectives on AI is Ben Shneiderman's Human-Centered Artificial Intelligence (Oxford University Press, 2022)

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.

• AI as Social Glue: Uncovering the Roles of Deep Generative AI during Social Music Composition
• “It’s like a rubber duck that talks back”: Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study
• Exploring the Learnability of Program Synthesizers by Novice Programmers
• Interpretable Program Synthesis
• Don’t Just Tell Me, Ask Me: AI Systems that Intelligently Frame Explanations as Questions Improve Human Logical Discernment Accuracy over Causal AI explanations
• Where to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence
• Predictive Text Encourages Predictable Writing
• When People and Algorithms Meet: User-reported Problems in Intelligent Everyday Applications
• Explanations as Mechanisms for Supporting Algorithmic Transparency

Background in HCI

Teaching materials for the research-oriented Cambridge undergraduate course in Further HCI can be found here:
https://www.cl.cam.ac.uk/teaching/2324/FHCI/.
During the Covid pandemic year 2020/21, a video version of the course was created.

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 in the same module last year. Readers wishing to see any of this in advance are welcome to refer to material from previous years.