Study by Jennifer A. Stark and Nicholas Diakopoulos. They investigate bias in Google’s image selection for the main search results pages of presidential candidates’ main search results page. The paper indicates that bias may have been introduced by the Google image selection algorithm.
Stark, Jennifer A. and Nicholas Diakopoulos. 2017. “Using Baselines for Algorithm Audits”. European Conference on Data and Computional Journalism.
Read MoreDeborah G. Johnson and Mario Verdicchio identify three factors that give people anxiety about artificial intelligence. The reasons, they argue, may not be what you think they are.
Johnson, Deborah G. and Mario Verdicchio. 2017. “AI Anxiety” Journal of the Association for Information Science and Technology . DOI: https://doi.org/10.1002/asi.23867
Read MoreAs the news media adopts algorithmic components into the production of news information, it raises the question of how to maintain an accountable media system. Nicholas Diakopoulos explores algorithmic transparancy.
Diakopoulos Nicholas. 2017. “Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens”. In: Cerquitelli,Tania, Daniele Quercia and Frank Pasquale (eds) Transparent Data Mining for Big and Small Data. Studies in Big Data, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-319-54024-5_2
Read MoreDeborah G. Johnson and Mario Verdicchio. The way public understanding of AI is being shaped, often by fear, is a way that may ultimately impede its research. This knowledge leads to a confusion about the notion of ‘autonomy’.
Johnson, Deborah G. and Mario Verdicchio. 2017. “Reframing AI Discourse”. Minds & Machines 27: 575–590. https://doi.org/10.1007/s11023-017-9417-6
Read MoreNicholas Diakopoulos and Michael Koliska. This research presents a focus group study that engaged 50 participants across the news media and academia to discuss case studies of algorithms in news production and elucidates factors that are amenable to disclosure.
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