Transparency Paths: Documenting the Diversity of User Perceptions

Fausto Giunchiglia, Styliani Kleanthous, Jahna Otterbacher, Tim Draws

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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We are living in an era of global digital platforms, eco-systems of algorithmic processes that serve users worldwide. However, the increasing exposure to diversity online - of information and users - has led to important considerations of bias. A given platform, such as the Google search engine, may demonstrate behaviors that deviate from what users expect, or what they consider fair, relative to their own context and experiences. In this exploratory work, we put forward the notion of transparency paths, a process by which we document our position, choices, and perceptions when developing and/or using algorithmic platforms. We conducted a self-reflection exercise with seven researchers, who collected and analyzed two sets of images; one depicting an everyday activity, "washing hands,"and a second depicting the concept of "home."Participants had to document their process and choices, and in the end, compare their work to others. Finally, participants were asked to reflect on the definitions of bias and diversity. The exercise revealed the range of perspectives and approaches taken, underscoring the need for future work that will refine the transparency paths methodology.

Original languageEnglish
Title of host publicationUMAP 2021
Subtitle of host publicationAdjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization
EditorsJ. Masthoff, E. Herder, N. Tintarev, M. Tkalčič
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Number of pages6
ISBN (Print)978-1-4503-8367-7
Publication statusPublished - 2021
Event29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021 - Virtual at Utrecht, Netherlands
Duration: 21 Jun 202025 Jun 2020


Conference29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021
CityVirtual at Utrecht


  • Information systems
  • Web searching and information discovery
  • Social and professional topics
  • User characteristics


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