This study explores the regulation of generative AI, focusing on its role as a "floating signifier" and the challenges it presents in terms of visibility and invisibility. The research examines the regulatory approaches of the European Union (EU) and the United States (US), highlighting both their alignment and structural challenges. Drawing on Foucault's concept of panopticism, the study emphasizes the need to regulate the power of the unseen, which is central to understanding the impact of generative AI on society. The EU and US have distinct regulatory frameworks, with the EU emphasizing safety and fairness through a risk-based approach, while the US focuses on self-regulation and technological innovation. The study identifies key challenges in AI regulation, including ethical risks, privacy concerns, and the potential for monopolization. It also discusses the structural challenges of AI-related regulation, such as the need for comprehensive and dynamic regulatory frameworks. The research proposes a synthetic regulatory framework that integrates interdisciplinary perspectives, including semiotics, panopticism, and discourse-power theory, to address the multifaceted challenges of generative AI regulation. The study concludes that a holistic approach is necessary to ensure the ethical and effective governance of generative AI, balancing technological advancement with social and legal considerations. The findings underscore the importance of regulating the unseen aspects of AI to mitigate risks and promote responsible innovation.This study explores the regulation of generative AI, focusing on its role as a "floating signifier" and the challenges it presents in terms of visibility and invisibility. The research examines the regulatory approaches of the European Union (EU) and the United States (US), highlighting both their alignment and structural challenges. Drawing on Foucault's concept of panopticism, the study emphasizes the need to regulate the power of the unseen, which is central to understanding the impact of generative AI on society. The EU and US have distinct regulatory frameworks, with the EU emphasizing safety and fairness through a risk-based approach, while the US focuses on self-regulation and technological innovation. The study identifies key challenges in AI regulation, including ethical risks, privacy concerns, and the potential for monopolization. It also discusses the structural challenges of AI-related regulation, such as the need for comprehensive and dynamic regulatory frameworks. The research proposes a synthetic regulatory framework that integrates interdisciplinary perspectives, including semiotics, panopticism, and discourse-power theory, to address the multifaceted challenges of generative AI regulation. The study concludes that a holistic approach is necessary to ensure the ethical and effective governance of generative AI, balancing technological advancement with social and legal considerations. The findings underscore the importance of regulating the unseen aspects of AI to mitigate risks and promote responsible innovation.