Algorithmic content moderation: Technical and political challenges in the automation of platform governance
University of Oxford · Alexander von Humboldt Institute for Internet and Society
Abstract
As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinformation. Automated hash-matching and predictive machine learning tools – what we define here as algorithmic moderation systems – are increasingly being deployed to conduct content moderation at scale by major platforms for user-generated content such as Facebook, YouTube and Twitter. This article provides an accessible technical primer on how algorithmic moderation works; examines some of the existing automated tools used by major platforms to handle copyright infringement, terrorism and toxic speech; and identifies…
Citation impact
- FWCI
- 60.80
- Percentile
- 100%
- References
- 14
Authors
3Topics & keywords
- Moderation
- Corporate governance
- Computer science
- Sociotechnical system
- Government (linguistics)
- Computer security
- Politics
- Unintended consequences
- Peace, Justice and strong institutions