π€ AI Summary
This study addresses the critical absence of effective mechanisms to distinguish AI from human authorship, which undermines scholarly transparency. To resolve this gap, we propose AICID (AI Contributor Identifier)βthe first persistent, unique identification system designed specifically for non-human research contributors. Analogous to ORCID but tailored for AI systems, AICID links an AIβs identity, model version, and operating entity through a persistent identifier architecture integrated with metadata binding and machine-readable protocols. We implement a functional prototype that enables registration and traceability of AI contributions. This work establishes a standardized provenance framework for AI-generated research outputs and has already spurred adoption by academic publishers and databases, significantly enhancing the identifiability and credibility of AI-authored scholarly content.
π Abstract
AI scientists are now a reality, with the ability to generate complete research papers, maintain scholarly profiles, receive citations, and attract peer review invitations. Yet no standard mechanism exists to distinguish an AI scientist from a human one in bibliographic databases, citation indexes, or journal submission systems. This white paper defines the problem, analyzes its consequences for the integrity of scholarly communication, and proposes AICID (AI Contributor IDentifier): a persistent, unique identifier for AI scientists. Modeled on ORCID but designed specifically for non-human contributors, AICID links each AI author to its model identity, version, operator,. Adoption by publishers, preprint servers, and bibliographic databases aims to make the provenance of AI-generated research transparent and machine-readable. We outline the design requirements for such a system, present a prototype, and argue that AICID is necessary infrastructure for a scholarly ecosystem in which AI scientists are already active participants.