Enterprise AI Analysis

Building trust in the generative AI era: a systematic review of global regulatory frameworks to combat the risks of mis-, dis-, and mal-information

By Fakhar Abbas, Simon Chesterman, Araz Taeihagh

The rapid evolution of generative artificial intelligence (genAI) technologies such as ChatGPT, DeepSeek, Gemini, and Stable Diffusion offers transformative opportunities while also raising profound ethical, societal, and governance challenges. As these tools become increasingly integrated into digital and social infrastructures, it is vital to understand their potential impact on consumer behavior, trust, information consumption, and societal well-being. Understanding how individuals interact with AI-enhanced content is, in turn, necessary for developing operative regulatory policies to address the growing challenges of mis-, dis-, and mal-information (MDM) on digital platforms. In this study, we systematically analyze global regulatory and policy frameworks as well as AI-driven tools to address the growing risks of MDM on digital platforms and optimize the interplay between humans and genAI moderation. The study highlights the need to balance technological innovation with societal protection and freedom of expression by identifying evolving trends and critical gaps in global policy coherence. We examine how the proliferation of MDM—often accelerated by genAI—distorts the information landscape, induces cognitive biases, and undermines informed decision-making. Our study proposes an integrative strategy that combines technical detection methods with actionable policy recommendations to mitigate MDM risks, reinforce digital resilience, and foster trustworthy genAI governance. The study also explores the potential role of AI itself in combating MDM risks.