There is a gargantuan application for fish welfare legislation that recognises the ecosystem of stakeholders involved. Human activity is heavily regulated, but little attention is paid to animal welfare (Walker, 2006), and to the welfare of fish in particular (Maia, 2023). However, the welfare of fish, humans and the marine environment are heavily interconnected.
Recent developments include recent developments in fish sentience, our ethical obligations to minimise their suffering (Lambert et al., 2022), a steep increase in the global importance of fish as a food source (FAO, 2024), and corresponding concerns about antimicrobial resistance. These developments increasingly impact human wellbeing and the wider environment (Singh et al., 2024).
These developments provide a clear imperative to pursue holistic, evidence-based fish welfare regulation. However, any such pursuit by humans would be enormously complicated and time-consuming. In contrast, the complex and interconnected nature of this requirement is an ideal match for the strengths claimed by AI-supported legislative drafting, which lauds its capacity to process data, benchmark, identify gaps and simplify complex information in a consistent feedback loop (Staff, 2025).
The proposed PhD thesis will consider these benefits, along with concerns currently associated with the use of AI in regulatory settings, i.e., data security, bias, transparency, explainability, and ethical dilemmas (Şimşek, 2025). It would also consider factors that contribute to effective regulation, including a clear framework, opportunities for comparison, and the ability to measure outcomes, along with challenges arising from regulations created by jurisdictions, socioeconomics, and enforcement capacity.