15 Years of (Who)man Robot Interaction: Reviewing the H in Human-Robot Interaction
2023 (English)In: ACM Transactions on Human-Robot Interaction, E-ISSN 2573-9522, Vol. 12, no 3, article id 28Article, review/survey (Refereed) Published
Abstract [en]
Recent work identified a concerning trend of disproportional gender representation in research participants in Human-Computer Interaction (HCI). Motivated by the fact that Human-Robot Interaction (HRI) shares many participant practices with HCI, we explored whether this trend is mirrored in our field. By producing a dataset covering participant gender representation in all 684 full papers published at the HRI conference from 2006-2021, we identify current trends in HRI research participation. We find an over-representation of men in research participants to date, as well as inconsistent and/or incomplete gender reporting which typically engages in a binary treatment of gender at odds with published best practice guidelines. We further examine if and how participant gender has been considered in user studies to date, in-line with current discourse surrounding the importance and/or potential risks of gender based analyses. Finally, we complement this with a survey of HRI researchers to examine correlations between the who is doing with the who is taking part, to further reflect on factors which seemingly influence gender bias in research participation across different sub-fields of HRI. Through our analysis we identify areas for improvement, but also reason for optimism, and derive some practical suggestions for HRI researchers going forward.
Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2023. Vol. 12, no 3, article id 28
Keywords [en]
Gender, Systematic Review, User Study Methodologies, Participant Recruitment, Inclusivity
National Category
Human Aspects of ICT Gender Studies Robotics
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-22066DOI: 10.1145/3571718ISI: 001020331600001Scopus ID: 2-s2.0-85163177354OAI: oai:DiVA.org:his-22066DiVA, id: diva2:1712171
Note
CC BY 4.0
*All authors contributed equally to this work. KW has taken on first author responsibilities whilst 2nd-4th author ordering was decided by dice roll. Authors’ addresses: Katie Winkle*, Uppsala Universitet, Sweden, katie.winkle@it.uu.se; Erik Lagerstedt*, University of Skövde, Sweden,erik.lagerstedt@his.se; Ilaria Torre*, KTH Royal Institute of Technology, Sweden, ilariat@kth.se; Anna Ofenwanger*, Université Paris-Saclay, CNRS, Inria, LISN, Orsay, France, anna.ofenwanger@universite-paris-saclay.fr.
We first want to acknowledge those authors who came before us in identifying issues around gender in HCI – these works have signicantly informed this manuscript, but also our approaches to HRI research more broadly. We wish to specically thank Dongwook Yoon and Julia Bullard for their work on the conceptualisation and development of the gender data schema and extraction method that we build on [59]; also Minsuk Chang, Alan Milligan, and Austin Kobayashi for their input and work on initial version of the MAGDA tool [59].We would like to thank all of the HRI researchers who engaged with our survey. We additionally want to thank those reviewers who provided constructive feedback on an earlier version of this work, and reviewersfor/attendees of the DEI Workshop held at HRI 2022 for further discussion – the manuscript is improved greatly as a result and we hope we have done justice to both the positive and negative critique we have received. All figures were generated with a colour palette based on the non-binary pride lag, created by Joel Le Forestier (https://joelleforestier.com/#pridepalettes). This work was partially funded by the Digital Futures Research Centre.
2022-11-212022-11-212023-08-18Bibliographically approved