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Bianca G. S. Schor

dblp:377/1888 · also Bianca G. Schor, Bianca Giulia Sarah Schor · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0001-5359-4656ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 77% Design research and methods · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction
algorithmic transparency
0.812024
Mind The Gap: Designers and Standards on Algorithmic System Transparency for Users · CHI 2024
Design research and methods
responsible design
0.212024
Mind The Gap: Designers and Standards on Algorithmic System Transparency for Users · CHI 2024

Methods — techniques the papers use, named apart from their topics

mixed-method study · 0.8
YearPublicationVenuePosition
2024 Mind The Gap: Designers and Standards on Algorithmic System Transparency for Users
abstract
Many call for algorithmic systems to be more transparent, yet it is often unclear for designers how to do so in practice. Standards are emerging that aim to support designers in building transparent systems, e.g by setting testable transparency levels, but their efficacy in this regard is not yet understood. In this paper, we use the ‘Standard for Transparency of Autonomous Systems’ (IEEE 7001) to explore designers’ understanding of algorithmic system transparency, and the degree to which their perspectives align with the standard’s recommendations. Our mixed-method study reveals participants consider transparency important, difficult to implement, and welcome support. However, despite IEEE 7001’s potential, many did not find its recommendations particularly appropriate. Given the importance and increased attention on transparency, and because standards like this purport to guide system design, our findings reveal the need for ‘bridging the gap’, through (i) raising designers’ awareness about the importance of algorithmic system transparency, alongside (ii) better engagement between stakeholders (i.e. standards bodies, designers, users). We further identify opportunities towards developing transparency best practices, as means to help drive more responsible systems going forward.
Bianca G. S. Schor, Chris Norval, Ellen Charlesworth, Jatinder Singh
CHI1