HUCO

Key areas

1) Fieldwork

People & Organisations
We apply systematic qualitative techniques to understand the social and organisational settings where technology is used.
ACTIVITIES: Observation, Fieldwork, and Interviews.
METHODS: Video-based interaction analysis, Ethnography for design, Sensory ethnography.

2) Design

Participatory Design
We engage stakeholders in the design process using co-design methods that provide stakeholder communities with the opportunity to engage directly in the process of design, and to contribute to the identification and definition of requirements.
ACTIVITIES: Idea generation, Co-design activities
METHODS: Cooperative prototyping, Scenario development, Workshops.

3) Evaluation

Assessment
We conduct user studies to understand how well a system supports interaction and activity in its intended setting. For a technology to be successful it should be assessed to determine its usefulness (does it do want is wanted or expected), and usability (is it easy to use) as well as its impact on day-to-day interaction. We also need to understand how it might support or constrain activity.
METHODS: Naturalistic evaluation, Interviews, Focus groups.

Ongoing projects

Remembering the future: A study of work in street trials of driverless buses (SNSF Spark, 2024–2025)

PI: Jakub Mlynář. Collaborators: Benjamin Nanchen, Luisa Ehrenzeller.

The project focuses on past trials of automated vehicles for public transport in Switzerland. Through “oral history” interviews with professionals involved in these trials, such as safety operators and technicians, our goal is to explore the social aspects and implications of automated mobility. We seek to understand the narratives surrounding the organization of pilot trials and the participants’ roles within them.

Concluded projects

RADHED – Radiomics in higher education: QuantImage as a teaching tool (RCSO ISNet, 2022–2023)

PI: Florian Evéquoz. Collaborators: Jakub Mlynář, Adrien Depeursinge, Roger Schaer. Partner: John O. Prior (CHUV Lausanne).

The project explored the possible use of an AI-based software platform QuantImage in the context of teaching radiomics, the new field of medical imaging analysis based on extracting large-scale quantitative features by machine-learning algorithms. The project was based on 13 trial sessions organized at Centre hospitalier universitaire vaudois (CHUV) in Lausanne. We have obtained multiple-angle video recordings from the sessions to examine the interactional details of novice users’ collaborative work with QuantImage, specifying its educational potential and proposing design improvements.

Publications

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