Algorithms in practice
Comparing web journalism and criminal justice
Bibliographic Data
| ID | 5260641 |
|---|---|
| Authors | Angèle Christin (0000-0002-7437-2013, Stanford University, corresponding author) |
| Year | 2017 |
| Volume | 4 |
| Issue | 2 |
| Pages | 205395171771885 |
| Publication date | 2017-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2053951717718855 |
| OpenAlex | W2737089608 |
| Language | EN |
| Citations received | 151 |
| References cited | 46 |
Big Data evangelists often argue that algorithms make decision-making more informed and objective—a promise hotly contested by critics of these technologies. Yet, to date, most of the debate has focused on the instruments themselves, rather than on how they are used. This article addresses this lack by examining the actual practices surrounding algorithmic technologies. Specifically, drawing on multi-sited ethnographic data, I compare how algorithms are used and interpreted in two institutional contexts with markedly different characteristics: web journalism and criminal justice. I find that there are surprising similarities in how web journalists and legal professionals use algorithms in their work. In both cases, I document a gap between the intended and actual effects of algorithms—a process I analyze as “decoupling.” Second, I identify a gamut of buffering strategies used by both web journalists and legal professionals to minimize the impact of algorithms in their daily work. Those include foot-dragging, gaming, and open critique. Of course, these similarities do not exhaust the differences between the two cases, which are explored in the discussion section. I conclude with a call for further ethnographic work on algorithms in practice as an important empirical check against the dominant rhetoric of algorithmic power
Big data · Criminal justice · Criminology · Data mining · Data science · Economic Justice · Ethnography · Journalism · Media studies · Political science · Public relations · Rhetoric · Sociology · Computer Science · Ethics and Social Impacts of AI · Law · Privacy, Security, and Data Protection · Social Media and Politics
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| Unique citing works | 151 |
|---|---|
| Citations per year | 16,78 |
| Citation span | 2017 - 2026 (10) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 135 |