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Become an author for GenAI Policy and view our Call for Papers

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AIMS & SCOPE

The Journal of Generative AI Policy (ISSN 3078-1922) is double-blind peer review journal which examines the intersection of generative AI technologies and policy across a wide range of domains, including but not limited to:

  • Algorithmic accountability, transparency, and fairness
  • Regulatory approaches to generative AI in media, education, and healthcare
  • Balancing innovation and ethical boundaries in generative AI use


  • Applications of generative AI in key industries such as finance, agriculture, and healthcare
  • Generative AI’s role in reshaping labor markets and societal norms
  • Policy responses to AI-driven misinformation and synthetic media


  • International and regional regulatory frameworks, including EU, US, and China
  • Cross-border governance challenges and opportunities in generative AI


  • Anticipating  the societal implications of next-generation generative AI technologies
  • Exploring  generative AI’s potential in climate change mitigation, security, and global trade


  • Examination of landmark judgments shaping the governance of generative AI
  • Comparative analyses of judicial approaches to generative AI-related disputes


Article Types

We accept the article types, including Research Articles, Policy Analyses, Case Studies, Commentary and Opinion Pieces, Literature Reviews, Technical Policy Briefs, Book and Report Reviews, Editorials, and Perspectives, catering to diverse scholarly and professional contributions.

Provide original, rigorous, and peer-reviewed research on topics related to generative AI policy. These articles should contribute new insights, methodologies, or frameworks to the field.

  

Length: Typically 6,000–10,000 words,  including references.


 Critical evaluations of existing or proposed policies governing generative AI, offering evidence-based recommendations. 

  

Length: Typically 4,000–7,000 words.


 Detailed examinations of real-world applications or incidents involving generative AI and their policy implications. These articles provide lessons learned and practical insights. 


Length: Typically 3,000–6,000 words.


Timely and thought-provoking discussions by experts on emerging issues, controversies, or trends in generative AI policy. 


Length: Typically 1,500–3,000 words.


Analyses of significant legal cases, court decisions, or legislative developments that shape the      governance of generative AI.


Length: Typically 6,000–10,000 words.


Concise articles translating complex technical advancements in generative AI into actionable insights for policymakers.


Length: Typically 2,000–4,000 words.


Evaluations of recent books, white papers, or reports that address topics relevant to generative AI policy. 


Length: Typically 1,000–2,500 words.


Written by editors or invited contributors to introduce the issue’s theme or discuss overarching trends in generative AI policy. 


Length: Typically 1,000–2,500 words.


 Forward-looking articles that discuss emerging trends, future challenges, and opportunities in generative AI policy. These articles aim to provoke dialogue and inspire innovation. 


Length: Typically 3,000–5,000 words.


Every Author Publication Ethics Statement

Coming soon, watch this space



Copyright / Open Access

Articles published in Gen AI will be Open-Access articles distributed under the terms and conditions of the Creative Commons Attribution License (CC BY). The copyright is retained by the author(s). Every Author will insert the following note at the end of the published text:

© 2024 by the authors. Published by Every Author on behalf of the xxxx. Licensee Every Author Publishing, Hong Kong SAR. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).


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