Reimagining the Journal Editorial Process: An AI-Augmented Versus an AI-Driven Future

Summary

The authors note that the IS editorial process has become long and frustrating for editors, reviewers, and authors, and that AI tools are a tempting fit to ease and advance it. They run a thought experiment contrasting two futures: an AI-augmented process where systems provide algorithmic predictions and recommendations while preserving human judgment and accountability, and an AI-driven, fully autonomous process. They argue the AI-driven future risks misalignment with academic values, perpetuating data biases, and eroding the social bonds and community practices of human-led editing, and conclude by advocating AI as augmentation rather than replacement.

Contribution

Presents a thought experiment that distinguishes AI-augmented from AI-driven editorial futures, contrasts their benefits and dangers for authors, reviewers, editors, and publishers, and argues for an augmentation path that strengthens academic discourse and community-building over metric-driven efficiency.

Method

Opinion piece structured as a conceptual thought experiment; no empirical study reported.

Relevance to RISE

Two-axis framework — AI-augmented (humans driving, AI assisting) vs. AI-driven (AI driving, humans approving) editorial processes. The framework maps directly onto the catalog's autonomy_level scoring dimension for review-focused projects.

Critique / open questions

Thought experiment without empirical grounding; the two-future dichotomy may oversimplify a continuum, and risks/benefits are asserted rather than measured.