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- Publisher
- Addleton Academic Publishers
- Copyright
- © 2009 Addleton Academic Publishers
- ISSN
- 1948-9137
- eISSN
- 2162-2752
- Publisher site
- See Article on Publisher Site
Abstract
I draw on a substantial body of theoretical and empirical research on the inherent regulatory capacity of data-driven automated decision-making, and to explore this, I inspected, used, and replicated survey data from Pew Research Center, performing analyses and making estimates regarding % of Facebook users who say they understand not at all/not very/somewhat/very well why certain posts are included in their news feed and others are not, % of U.S. adults who say that it is possible for computer programs to make decisions without human bias/computer programs will always reflect bias of designers (by age group), and % of Facebook users with no assigned category/fewer than 10 categories/10–20 categories/21+ categories listed on their “ad preferences” page. Structural equation modeling was used to analyze the data and test the proposed conceptual model. Keywords: governance; analytical algorithm; data-driven automated decision-making
Journal
Contemporary Readings in Law and Social Justice – Addleton Academic Publishers
Published: Jan 1, 2019