The Third Option: integrating AI training‑data licensing into scholarly publishing workflows

Position	Summary (core claim and implications)
Unilateral back‑catalogue licensing	Efficient for rightsholders but can provoke backlash if communities perceive weak transparency, weak participation or unclear benefit allocation (National Communication Association, 2024).
Retroactive opt‑in outreach	Improves procedural legitimacy by seeking author decisions, but it is costly and difficult to scale, particularly for large back catalogues (Coase, 1937; Williamson, 2010).
‘Open licences already solve it’	When works are CC BY, permission exists for broad reuse, so additional licensing can be redundant. This stance often under‑specifies provenance, documentation and auditability for curated dataset supply (Bender & Friedman, 2018; Gebru et al., 2021).
‘Scraping and legal exceptions dominate’	Developers can scrape public text or rely on text and data mining exceptions, reducing willingness to pay. This stance may underestimate compliance incentives and the value of curated datasets with documentation and assurances (European Union, 2019, 2024; Mitchell et al., 2019).

Table 2

Definitions (Layer A operational definitions with representative anchors)

Term	Layer A: operational definition (this article)	Representative anchors	Boundary conditions	Implications
Third Option	A post‑acceptance, opt‑in addendum integrated into the publication agreement, authorizing defined AI training uses of the accepted article in exchange for an author‑facing benefit.	Coase (1937); Williamson (2010)	Consent requested only after acceptance; does not alter peer review.	Converts consent into a routine workflow artefact rather than a retroactive campaign.
AI training use	Use of article text (and optionally tables) as input to train, fine‑tune or evaluate machine‑learning models, distinct from the redistribution of the article as an access substitute.	Bender and Friedman (2018); Mitchell et al. (2019)	Does not resolve all downstream misuse risks.	Enables permitted and prohibited use boundaries to be stated and audited.
Author‑facing benefit	A tangible benefit offered for opting in that is monetary or fee‑neutral, depending on the publishing model.	Dufour et al. (2023); Smith et al. (2021)	Must be independent of acceptance decisions; design must address inducement risk.	Supports uptake but can also threaten legitimacy without safeguards.
Social licence	Stakeholder‑perceived legitimacy grounded in trust, transparency and perceived public value, beyond legal permission.	Carter et al. (2015); Muller et al. (2021)	Contextual and contested; not a legal standard.	Motivates transparency reporting and procedural safeguards.
Provenance record	Machine‑readable metadata linking content to persistent identifiers, version, date and inclusion parameters, enabling traceability and audit.	Buneman and Tan (2019)	Provenance does not guarantee accuracy of content.	Supports traceability, correction and audit narratives.
Withdrawal (future‑only)	Exclusion of an article from future dataset releases after opt in is withdrawn, with disclosure that prior training may not be reversible.	Buneman and Tan (2019); Xu et al. (2023)	Cannot guarantee model untraining; cannot revoke open licences.	Provides an operationally coherent agency mechanism tied to versioning.

Table 3

Decision table (publishing model and feasible author‑facing benefit structures)

Publishing model	Example benefit structures	Constraint to state explicitly
Subscription‑only journal	Direct author honorarium; society membership reduction; institutional credit; community reinvestment commitment.	Benefit must not be tied to acceptance; access terms remain unchanged.
Hybrid journal (subscription + optional OA with APC)	APC discount or rebate; waiver top‑up; institutional rebate; fee‑neutral benefit.	Needs‑based waivers should be independent of consent; monitor disparate uptake (Smith et al., 2021).
Diamond open access journal (no APC, often CC BY)	Fee‑neutral benefits (author services); institutional rebates; conference discounts; community reinvestment commitments aligned with diamond funding strategies.	Addendum cannot restrict CC BY rights; value must be framed as governance, provenance and assurance (Dufour et al., 2023).
Full open access journal (APC‑funded)	APC discount or rebate; waiver top‑up; institutional rebate.	Equity risks may be amplified and require monitoring (Ellers et al., 2017; Smith et al., 2021).

Table 4

Safeguards (risks, safeguards and implementation notes)

Risk	Recommended safeguard	Implementation note
Perceived editorial influence	Collect consent only post‑acceptance; consent status not visible to editors or reviewers.	Separate editorial and licensing workflows with audit logs.
Undue inducement	Offer equivalent routes and needs‑based waivers independent of consent.	Declining the addendum must not foreclose viable publication options (McGregor, 2005; Smith et al., 2021).
Information asymmetry	Standardized, plain‑language disclosure of scope, terms and withdrawal limits.	Avoid pre‑checked boxes; allow time for consideration where feasible.
Irreversibility misunderstanding	Disclose limits of reversing prior training; define withdrawal as future‑only.	Tie withdrawal to dataset versioning and licensee notifications (Xu et al., 2023).
Third‑party rights leakage	Exclude third‑party content by default unless separately cleared.	Require author attestation and implement checks where feasible.
Opaque value distribution	Aggregate transparency reporting on uptake and benefit allocation.	Report at journal or publisher level while protecting author privacy (Muller et al., 2021).

Table 5

Evaluation protocol (propositions, indicators, designs and boundary conditions)

Proposition	Observable indicators (examples)	Candidate study designs	Boundary conditions to report explicitly
P1	Uptake rate among accepted articles; time‑to‑consent completion; administrative cost per consented article.	Journal roll‑out evaluation using administrative records; comparative case studies of workflow designs.	Disclosure clarity; workflow integration; separation of editorial and licensing systems.
P2	Provenance completeness; documentation quality; third‑party exclusion rates; audit clause prevalence in contracts.	Document analysis of dataset artefacts and contracts; interviews with compliance and procurement stakeholders.	Field heterogeneity in third‑party content prevalence and documentation norms.
P3	Growth of consented corpus over time; partnership frequency; any association with submission trends.	Time‑series analysis across venues; matched comparisons of early and late adopters.	Tools must differentiate provenance‑rich datasets; market demand for auditability must be present.
P4	Withdrawal requests; time‑to‑exclusion from subsequent releases; version traceability and notification logs.	Implementation audits; stakeholder surveys on acceptability and understanding.	Withdrawal cannot imply guaranteed model untraining; open‑licence terms remain unaffected.
P5	Uptake disparities by region, funding context or career stage; waiver use; complaint rates and perceived pressure.	Equity monitoring with privacy‑preserving aggregate reporting; quasi‑experimental comparison of benefit and waiver policies.	Reporting must protect privacy and interpret disparities in context (discipline, mandates and funding).