Algorithmic fairness in online information mediating systems (Extended Abstract)

Ansgar Koene, Sofia Ceppi, Helena Webb, Menisha Patel, Elvira Perez, Giles Lane, Marina Jirotka, Michael Rovatsos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This paper explores the fundamental challenges around fair management of information access when the limits of human attention require algorithmic assistance for ‘€finding the diamond in the coal mountain’. While o‰en named as a key demand from users, the seemingly intuitive concept of fairness has proven to be very difficult to satisfyingly operationalise for implementation in algorithms.
Here we present two pilot studies aimed at getting a better understanding
of the conceptualisation of algorithmic fairness by users. The first was a multi-stakeholder focus-group discussion, the second a user experiment/questionnaire. Based on our data we arrive at a picture of fairness that is highly dependent and context and informedness of users, and possibly inherently misleading due to the implied projecting of human intentions onto an algorithmic process.
Original languageEnglish
Title of host publicationWebSci '17 Proceedings of the 2017 ACM on Web Science Conference
Place of PublicationTroy, NY, USA
Number of pages2
ISBN (Print)978-1-4503-4896-6
Publication statusPublished - 25 Jun 2017
Event2017 ACM on Web Science Conference - Troy, United States
Duration: 25 Jun 201728 Jun 2017


Conference2017 ACM on Web Science Conference
Abbreviated titleWEBSCI’17
Country/TerritoryUnited States
Internet address


Dive into the research topics of 'Algorithmic fairness in online information mediating systems (Extended Abstract)'. Together they form a unique fingerprint.

Cite this