University of Illinois Urbana-Champaign

Digitally Dysfunctional: How HCI Researchers Examine BIPOC Interactions with Recommendation Algorithms

Dai, Jiarun; Wani, Sehba; Robinson, Zauryn; Hajiyeva, Naila; Scheuerman, Morgan Klaus

Content Files
241_abstract.docx
241_poster.pdf

Permalink

https://hdl.handle.net/2142/122798

Description

Title
Digitally Dysfunctional: How HCI Researchers Examine BIPOC Interactions with Recommendation Algorithms
Author(s)
  • Dai, Jiarun
  • Wani, Sehba
  • Robinson, Zauryn
  • Hajiyeva, Naila
  • Scheuerman, Morgan Klaus
Issue Date
2024-03-20
Keyword(s)
  • BIPOC
  • recommendation algorithms
  • human-computer interaction (HCI)
  • bias
  • personalization
  • recommender systems
  • social responsibility
  • sociotechnical systems
Abstract
Recommendation algorithms are often used in many mainstream media apps to provide content suggestions to users based on factors like individual preferences and virality. As a result, social media platforms circulate and popularize content trends. However, like other algorithmic approaches, recommender systems have been found to reinforce biases, particularly towards marginalized communities. This poster presents a preliminary literature review of how the Human-Computer Interaction (HCI) community has approached scholarship on both Black, Indigenous, and People of Color (BIPOC) individuals and recommendation algorithms. Our findings showcase a lack of focus at the intersection of BIPOC experiences and recommendation algorithms, with the technology and the population often being studied separately. Based on the gaps we identify in the literature, we propose future work aimed at understanding how BIPOC individuals experience recommendation algorithms, specifically on TikTok. Without proper recognition of the biases, lack of representation, and understanding of the offline impacts of the information that recommendation algorithms can create, certain populations could be at risk of encountering material that is untrue and harmful to their well-being.
Publisher
iSchools
Series/Report Name or Number
iConference 2024 Proceedings
Type of Resource
Other
Genre of Resource
Conference Poster
Language
eng
Handle URL
https://hdl.handle.net/2142/122798
Copyright and License Information
Copyright 2024 is held by Jiarun Dai, Sehba Wani, Zauryn Robinson, Haila Najiyeva, and Morgan Klaus Scheuerman. Copyright permissions, when appropriate, must be obtained directly from the authors.

Owning Collections

iConference 2024 Posters PRIMARY
Posters presented at the 2024 iConference https://www.ischools.org/iconference