Sarah Inman and Professor David Ribes, part of the Data Ecologies Laboratory, have been awarded an Honorable Mention at CHI 2019. The paper, “Beautiful Seams: Strategic Revelations and Concealments” offers a review of literature on a debate that occurred first, within the field of Ubiquitous Computing, but spread to CHI and beyond, in which design scholars argued that seamlessness had long been an implicit and privileged design virtue. In stitching together multiple threads from prior work on sociotechnical design practice and theory, this research demonstrates the value that a literature review can contribute to the CHI community. The work was authored as part of a larger study seeking to inform the design of data archives and interfaces that treat the history of data as seamful, or rather an approach to design that strategically reveals and conceals certain aspects of human and technological operations.

Os Keyes, a student with the Data Ecologies Laboratory, has been awarded an inaugural Ada Lovelace Fellowship to support their work on gender and identity in artificial intelligence. The Fellowship provides three years of full funding, along with a generous stipend and internship opportunities. Os was one of only two students in the field of HCI to receive a Fellowship, and one of six overall. More information can be found on the HCDE Blog.

Os Keyes, a student with the Data Ecologies Lab, has had a paper (“The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition”) accepted to CSCW 2018:

Automatic Gender Recognition (AGR) is a subfield of facial recognition that aims to algorithmically identify the gender of individuals from photographs or videos. In wider society the technology has proposed applications in physical access control, data analytics and advertising. Within academia, it is already used in the field of Human-Computer Interaction (HCI) to analyse social media usage. Given the long-running critiques of HCI for failing to consider and include transgender (trans) perspectives in research, and the potential implications of AGR for trans people if deployed, I sought to understand how AGR and HCI understand the term "gender", and how HCI describes and deploys gender recognition technology.

Using a content analysis of papers from both fields, I show that AGR consistently operationalises gender in a trans-exclusive way, and consequently carries disproportionate risk for trans people subject to it. In addition, I use the dearth of discussion of this in HCI papers that apply AGR to discuss how HCI operationalises gender, and the implications that this has for the field’s research. I conclude with recommendations for alternatives to AGR, and some ideas for how HCI can work towards a more effective and trans-inclusive treatment of gender.