Abstract.
Artificial intelligence (AI) is transforming industries, governance, and daily life, but
its rapid adoption raises significant ethical and regulatory challenges. This paper
explores the intersections of bias, copyright, liability, and security in AI systems,
analyzing real-world cases such as generative art copyright disputes, algorithmic bias in
chatbots, and AI-assisted military technologies. Using qualitative policy analysis and
case study methodology, the research identifies structural gaps in existing legal and
regulatory frameworks that leave creators, users, and society vulnerable. Findings
highlight the need for standardized yet flexible approaches, including compulsory
licensing for copyrighted data, algorithmic impact assessments, tiered liability
frameworks, and dual-use security regulations. By proposing integrated and globally
coordinated policies, the thesis demonstrates how responsible AI development can
balance innovation with accountability, equity, and security, providing a blueprint for
ethical AI governance.
https://st-anselm-cam.uk/journal
