AI Slop in Academic Publishing: History, Characteristics, Manifestations, Causes, and Mitigation Strategies
Abstract
As AI gains prominence in research workflows, AI slop, defined as low-quality, mass-produced synthetic content lacking human oversight, poses a systemic threat to scholarly integrity. This column examines the evolution and characteristics of AI slop in academic publishing, framing it through the SLOP (shallow, low-quality, overgeneralized, poorly-sourced) anatomy. By analyzing manifestations such as fabricated citations and visual fraud, we highlight critical risks to SDG 4 (Quality Education) and SDG 16 (Peace, Justice, and Strong Institutions). We propose multi-level mitigation strategies focused on human oversight and robust editorial policies to preserve institutional trust and the reliability of the knowledge ecosystem.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Academic Publishing and Open Access
Ethics and Social Impacts of AI
Publication details
- Journal / source
- Internet Reference Services Quarterly
- Publisher
- Informa UK Limited
- Volume
- 30
- Issue
- 2
- Pages
- 221–244
- Publication date
- 3 March 2026
- Language
- EN