The rise of large language model (LLM)-driven information services is reshaping how public knowledge institutions operate, according to a new research paper on arXiv. The paper warns that these systems risk absorbing the editorial function that such institutions exist to exercise, as pretrained LLMs arrive already aligned with the values and dissemination strategies of their commercial developers.
To address this challenge, the authors introduce editorial alignment as a design practice within the field of Participatory AI. The approach frames AI alignment as an ongoing design process, positioning the editorial standard as a design artefact that translates editorial practice and values into alignment objectives for technical implementation.
"This paper investigates editor participation in re-aligning LLM interfaces to editorial standards through design workshops, in a case study where we design and implement an LLM-enabled encyclopedia interface with a Nordic public knowledge institution."
The research is based on a case study with a Nordic public knowledge institution, where editors participated in workshops to re-align an LLM-powered encyclopedia interface to their editorial standards. The authors argue that LLMs offer powerful new affordances for knowledge dissemination but threaten editorial authority.
Key Concepts of Editorial Alignment
The paper identifies several core ideas:
- Editorial alignment is positioned as a participatory design practice, distinct from conventional AI alignment which often happens before deployment.
- The editorial standard is treated as a design artefact — a tangible representation of editorial practice and values that can guide technical implementation.
- The process aims to create space for ongoing participation, giving editors agency in how LLMs mediate knowledge dissemination.
- This approach counters the threat of commercial LLMs imposing their own alignment, which may not align with institutional values.
Implications for Enterprise AI Governance
While the case study focuses on a public knowledge institution, the principles of editorial alignment have direct relevance for enterprise technology decision-makers. Organizations deploying LLMs for internal knowledge management, customer support, or technical documentation face similar challenges: pretrained models carry embedded assumptions that may not match corporate policies, brand voice, or domain-specific standards.
The participatory workshop methodology offers a template for enterprises to involve subject-matter experts — such as editors, compliance officers, or senior engineers — in re-aligning LLM outputs to organizational norms. By treating editorial or expert standards as explicit design artefacts, enterprises can translate their governance requirements into technical alignment objectives.
The paper is authored by Enni, Simon Aagaard, Erslev, Malthe Stavning, Bilstrup, Karl-Emil Kjær, Nielbo, and Kristoffer Laigaard. It is available on arXiv under the identifier 2606.20258 in the Human-Computer Interaction category. As LLM adoption accelerates across industries, editorial alignment provides a framework for ensuring that AI systems serve institutional values rather than subsuming them.
