Governance of Generative AI

Araz Taeihagh

196 citations0/0 files storedPolicy and Society

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Ethics and Social Impacts of AI Digitalization, Law, and Regulation Law, AI, and Intellectual Property

Abstract

Abstract The rapid and widespread diffusion of generative artificial intelligence (AI) has unlocked new capabilities and changed how content and services are created, shared, and consumed. This special issue builds on the 2021 Policy and Society special issue on the governance of AI by focusing on the legal, organizational, political, regulatory, and social challenges of governing generative AI. This introductory article lays the foundation for understanding generative AI and underscores its key risks, including hallucination, jailbreaking, data training and validation issues, sensitive information leakage, opacity, control challenges, and design and implementation risks. It then examines the governance challenges of generative AI, such as data governance, intellectual property concerns, bias amplification, privacy violations, misinformation, fraud, societal impacts, power imbalances, limited public engagement, public sector challenges, and the need for international cooperation. The article then highlights a comprehensive framework to govern generative AI, emphasizing the need for adaptive, participatory, and proactive approaches. The articles in this special issue stress the urgency of developing innovative and inclusive approaches to ensure that generative AI development is aligned with societal values. They explore the need for adaptation of data governance and intellectual property laws, propose a complexity-based approach for responsible governance, analyze how the dominance of Big Tech is exacerbated by generative AI developments and how this affects policy processes, highlight the shortcomings of technocratic governance and the need for broader stakeholder participation, propose new regulatory frameworks informed by AI safety research and learning from other industries, and highlight the societal impacts of generative AI.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 196 citations exist upstream.

References

1985Agendas, Alternatives, and Public Policies 2016The ethics of algorithms: Mapping the debate 1999Code and Other Laws of Cyberspace 2024A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges 2020Artificial Intelligence, Values, and Alignment 2014To Save Everything, Click Here: The Folly of Technological Solutionism 2019Human Compatible: Artificial Intelligence and the Problem of Control 2021Governance of artificial intelligence

Cited by

2025Exploring the role of artificial intelligence in addressing sustainable development. A semantic analysis of AI patents 2025Rise of Generative Artificial Intelligence in Science 2025Artificial Intelligence: Modern Approaches to Multilateral Regulation 2025New policy tools and traditional policy models: better understanding behavioural, digital and collaborative instruments

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.