Reimagining Peer Review in the Age of AI
Reimagining Peer Review in the Age of AI
Why has this theme attracted such widespread attention? The reason is clear: artificial intelligence is transforming nearly every field, and scholarly workflows are no exception. From manuscript triage and reviewer recommendations to automated quality checks that help reduce reviewer workloads, these tools deliver efficiency — but they also raise urgent concerns about bias, transparency, accountability, accessibility, and the potential erosion of critical human judgment.Theme selection and significance
Ethical Peer Review
Imagine the peer review ecosystem in 2030: a landscape where technology supports—rather than replaces—human values, with journals anchored in ethics, transparency, AI literacy, and accountability. Achieving this vision requires collaboration among policymakers, publishers, and ethicists to establish future-ready policies that encourage the responsible use of AI in scholarly review. Authors, editors, and reviewers must openly disclose how AI is used in their work—whether in drafting, reviewing, or decision-making. Such openness builds trust. Reviewers and editors need the skills to interpret AI-generated content, evaluate its limitations, and spot algorithmic blind spots. This calls for dedicated training and resources. AI systems must be regularly audited to prevent the reinforcement of systemic biases. Journals should adopt tools and frameworks to identify and correct unfair outcomes. While AI can assist with submission triage or reviewer identification, essential scholarly judgment must remain human-led. Technology should augment—not replace—the nuanced expertise people bring. Clear ethical guidelines for AI in peer review, similar to those in clinical research or data protection, should become standard practice. Journals should anticipate advances such as AI-driven hypothesis generation or data-informed reviewing and implement policies that remain adaptable, robust, and rooted in integrity.Envisioning a Responsible Future for Peer Review
Transparency and Disclosure
AI Literacy and Training
Bias Mitigation and Fairness
Human-Centered Hybrid Models
Regulatory Guardrails
Foresight and Preparedness
Why Now—and How You Can Engage
The integration of AI into peer review is no longer a distant concept— it’s already underway. While this shift can feel both exciting and unsettling, it presents an opportunity to shape the future with confidence and responsibility. Through this journey, you’ll gain access to tools, perspectives, visual guides, and discussions that will help you: