Technical Summary: Editorial Alignment in LLM-Mediated Knowledge Dissemination

Problem Statement

The emergence of Large Language Model (LLM)-driven information services poses a structural threat to public knowledge institutions (e.g., national encyclopedias, libraries, archives). These institutions traditionally derive their authority from human editorial accountability and the curation of trustworthy knowledge. However, the shift toward "zero-click-search" paradigms, where LLMs synthesize and summarize information, risks absorbing the editorial function.

The core challenge is twofold:

1. Misalignment of Values: Pre-trained LLMs are inherently aligned with the values and dissemination strategies of their commercial developers, potentially compromising the editorial authority and specific institutional standards of public knowledge providers.
2. The "Data-Sourcing" Trap: Existing approaches to AI alignment often reduce human participation to the extraction of preference data (e.g., via Reinforcement Learning from Human Feedback). In this model, practitioners act merely as data generators rather than co-designers, resulting in "aggregated intuition" rather than a deep, situated translation of professional values into system constraints.
3. Tacit Knowledge Gap: Editorial standards are largely tacit—reliably exercised in practice but resistant to abstract verbalization. Current alignment methods struggle to capture these embedded professional norms, leading to a gap between principled institutional policies (e.g., banning AI-generated content) and the operational reality of LLM-mediated dissemination interfaces.

Methodology

The paper proposes Editorial Alignment, a design practice within Participatory AI (PAI) that reframes alignment as a collaborative, practice-centered design activity rather than a technical optimization problem. The methodology is grounded in Participatory Design (PD) traditions, specifically the concept of a "third space" where stakeholders negotiate system designs.

The approach was tested through a case study with a Nordic public online encyclopedia involving two workshops with senior editors:

1. Future Workshop (Workshop 1): A "Future Workshop" format used to establish a shared vision and mutual understanding between researchers and editors. This session focused on critiquing prototype outputs and identifying high-level concerns regarding source reliability, tone, and audience mismatch.
2. Practice-Centered Workshop (Workshop 2): A specialized session designed to elicit tacit editorial standards through concrete engagement with LLM outputs. The process involved:
   • Preparation: Editors individually edited 20 exemplar question-answer pairs from a prototype.
   • Collective Deliberation: Editors presented their edits to surface transversal values, best practices, and boundaries.
   • Edge-Case Stress Testing: The group evaluated "manufactured" responses generated by researchers using specific personas (e.g., social-media style, peer-register) designed to breach existing linguistic norms. This forced the articulation of implicit boundaries regarding tone and style.
   • Codification: The group resolved contradictions and prioritized findings to produce a concrete "Editorial Standard."

The resulting Editorial Standard serves as a boundary object between the editorial and technical communities, translating situated professional judgment into actionable alignment objectives (constraints and rules) for technical implementation.

Key Contributions

1. Conceptualization of Editorial Alignment: The paper introduces "editorial alignment" as a specific design practice for LLM-based interfaces in editorially governed institutions. It positions the editorial standard not as a fixed set of rules, but as a "living document" subject to ongoing revision.
2. Methodological Bridge: It establishes a bridge between AI alignment literature and Participatory Design. It challenges the universalist and essentialist conceptions of "human values" in alignment by grounding value specification in the concrete, context-specific practice of a real institutional community.
3. Case Study Evidence: The paper provides a detailed case study demonstrating how editors can participate in developing and governing AI alignment objectives. It shows that when editors engage directly with LLM-generated text, they surface genuine institutional values that differ significantly from generic user preferences.
4. Critical Reflection on Power: The authors critically analyze the limitations of their approach, noting that while editors were given influence through the design process, they were not granted power (formal co-ownership or governance authority) over the system. This highlights a structural gap between "consultative" participation and genuine agency in AI governance.

Results

The workshops resulted in the creation of an Editorial Standard consisting of five core values and twelve concrete rules.

Core Values:

• Respect the reader's time and attention.
• Provide appropriate context.
• Present content pedagogically.
• Do not talk down to the reader.
• Maintain a neutral and measured tone.

Concrete Rules (Selected):

• Open with a lead paragraph summarizing the answer.
• Signal how the user's query has been interpreted.
• Minimize textual complexity and academic register.
• Avoid normative or emotional judgments.
• Avoid directly addressing the reader (no first/second person).
• Avoid figurative or narrative language.

Implementation Outcome:
The standard led to a restructuring of the system's output format. The interface shifted from a conversational style to a structured, third-person, impersonal format. This included a lead paragraph, optional interpretation signals, and a detailed body section. These changes were implemented via context engineering and constrained generation, prioritizing high compatibility with available alignment techniques.

Crucially, the process revealed that the editors' professional standards were more conservative than the project's initial "conversational" ambitions. The editors prioritized the preservation of the institution's intellectual authority and tone over maximizing accessibility or engagement, even if it meant requiring more cognitive effort from the reader.

Significance and Claims

The paper claims that Editorial Alignment offers a viable pathway for public knowledge institutions to integrate LLMs without ceding their editorial authority. By treating alignment as a design process rather than a technical specification, institutions can translate tacit professional values into system constraints.

However, the authors are modest regarding the transformative power of the design practice alone. They argue that:

• Design is not Governance: The creation of an editorial standard does not automatically grant editors power over the system. Without structural changes—such as formal co-ownership, recurring editorial review processes, and constitutional status for the standard—editorial alignment risks remaining a consultative exercise that fails to break the "data-sourcing" dynamic.
• Conservatism as a Feature: The "conservative" nature of the resulting standard (rejecting conversational tropes) is not a failure of imagination but a reflection of the institution's core ethic: responsible dissemination over accessibility.
• Future Requirements: Realizing the full potential of this approach requires institutional will to restructure governance, moving editors from "influencers" to "governors" of the LLM system.

The paper concludes that while editorial alignment successfully establishes the boundaries of responsible dissemination, it is only a step toward a broader transformation where the practitioners accountable for knowledge quality also govern the systems through which that knowledge is disseminated.