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Detecting manuscripts written by generative AI and AI-assisted technologies in the field of pharmacy practice
- Source :
- Journal of Pharmaceutical Policy and Practice, Vol 17, Iss 1 (2024)
- Publication Year :
- 2024
- Publisher :
- Taylor & Francis Group, 2024.
-
Abstract
- ABSTRACTGenerative AI can be a powerful research tool, but researchers must employ it ethically and transparently. This commentary addresses how the editors of pharmacy practice journals can identify manuscripts generated by generative AI and AI-assisted technologies. Editors and reviewers must stay well-informed about developments in AI technologies to effectively recognise AI-written papers. Editors should safeguard the reliability of journal publishing and sustain industry standards for pharmacy practice by implementing the crucial strategies outlined in this editorial. Although obstacles, including ignorance, time constraints, and protean AI strategies, might hinder detection efforts, several facilitators can help overcome those obstacles. Pharmacy practice journal editors and reviewers would benefit from educational programmes, collaborations with AI experts, and sophisticated plagiarism-detection techniques geared toward accurately identifying AI-generated text. Academics and practitioners can further uphold the integrity of published research through transparent reporting and ethical standards. Pharmacy practice journal staffs can sustain academic rigour and guarantee the validity of scholarly work by recognising and addressing the relevant barriers and utilising the proper enablers. Navigating the changing world of AI-generated content and preserving standards of excellence in pharmaceutical research and practice requires a proactive strategy of constant learning and community participation.
Details
- Language :
- English
- ISSN :
- 20523211
- Volume :
- 17
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Journal of Pharmaceutical Policy and Practice
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.39f7f60e4f3a4af8ad396c277e4793c6
- Document Type :
- article
- Full Text :
- https://doi.org/10.1080/20523211.2024.2303759