CHAPTER 7. ARTIFICIAL INTELLIGENCE IN INTERNATIONAL LAW SCHOLARSHIP: THE NARRATIVE OF CHATGPT

This record contains the full transcripts of three research conversations conducted with successive versions and functionalities of OpenAI’s GPT‑4 model, used as empirical material for a chapter in the edited volume Global Order in the Age of AI (Oxford University Press, forthcoming). The conversations were conducted by [authors’ names, incl. Emilia Justyna Powell] and focus on the theme “Legitimacy of International Law” (Example 1 in the chapter). Each session explores the same substantive topic but uses a different version or functionality of GPT‑4: Session 1 (5 April 2023) – ChatGPT‑4 (released 14 March 2023) Session 2 (23 October 2024) – ChatGPT‑4o (released 13 May 2024) Session 3 (28 July 2025) – GPT‑4 with Deep Research functionality All three conversations were conducted using the paid, professional versions of the respective models. The dataset allows readers to trace, in a granular way, how the model’s responses evolved over time in terms of legal reasoning, structure, and depth. In the chapter, we use these transcripts to examine: how different GPT‑4 variants reason about the legitimacy of international law, the stability and variability of AI‑generated legal arguments across model versions, the models’ abilities to manage complex normative debates, and the broader implications of AI‑assisted reasoning for international law scholarship and practice. Session 1 (ChatGPT‑4) documents the earliest conversation, in which GPT‑4 already displays sophisticated natural‑language abilities and a reasonably coherent treatment of doctrinal and theoretical debates, but with more limited contextual depth and fewer explicit meta‑reflections on its own reasoning process. Session 2 (ChatGPT‑4o) illustrates notable changes in speed, contextual understanding, and multimodal‑oriented design. In this session, GPT‑4o provides more nuanced, better‑structured, and often more responsive answers, with improved coherence over longer exchanges and a more refined ability to track the conversation’s normative and empirical dimensions. Session 3 (GPT‑4 – Deep Research) showcases the use of GPT‑4’s Deep Research functionality. Here the model engages in multi‑step reasoning, synthesizes information across multiple documents or sources, and produces systematically structured and explicitly reasoned answers. This session is used in the chapter to explore the potential and limitations of iterative, research‑style interactions with AI in legal scholarship. Together, the three transcripts serve as a comparative dataset documenting the evolution of GPT‑4‑based systems as tools for AI‑assisted legal reasoning. They are intended as: supplementary material to the book chapter (for transparency and reproducibility), a teaching resource for courses on international law, AI and law, or methodology, and a reference point for future empirical work on large language models in legal contexts. Users are encouraged to cite this dataset alongside the book chapter when using or discussing the transcripts in academic or policy work.