[Call for Reviewers]
[Call for Papers]


We are excited to announce the 1st International Workshop on “AI Governance: Alignment, Morality and Law” (AIGOV) at the IJCAI 2024, a critical event addressing the principles, frameworks, and best practices necessary to navigate the ethical, legal, and societal dimensions of AI.

The rapid advancements in Artificial Intelligence (AI) bring unprecedented opportunities and challenges. As organizations and governments increasingly integrate AI technologies into various aspects of society, the need for effective AI governance becomes paramount. This workshop aims to provide a comprehensive understanding of AI governance principles, frameworks, and best practices to empower participants in navigating the ethical, legal, and societal dimensions of AI.

In addition to insightful technical discussions, we also plan to hold introductory talks to educate a broader community about the importance and urgency of AI governance. These talks will serve as a foundational introduction to the subject matter and its implications for society at large. Some topics of interest include but not limited to:

  • Understanding AI Governance: Define the core principles of AI governance. Explore existing regulations and ethical frameworks
  • Role of LLMs in AI Governance: Highlight the capabilities of LLMs in analyzing and generating human-readable content. Discuss how LLMs can contribute to drafting policies and guidelines.
  • Addressing Bias and Fairness: Examine the challenges of bias in AI systems. Showcase how LLMs can assist in identifying and mitigating bias.
  • Transparency and Accountability: Explore the importance of transparency in AI decision-making. Discuss how LLMs can aid in creating understandable and accountable AI systems.
  • Policy Interpretation and Compliance: Illustrate how LLMs can assist policymakers in understanding complex technical concepts. Discuss the role of LLMs in monitoring and auditing AI systems for compliance with governance standards.
  • Human-AI Collaboration: Emphasize the need for human oversight in AI governance. Discuss the collaborative approach between humans and LLMs.
  • AI alignment methods
  • Prompt engineering
  • Fine tuning
  • Explainable AI
  • Responsible AI practices

We believe that incorporating knowledge can potentially solve many of the most pressing challenges tackling the AI and society today. The primary goal of this workshop is to facilitate community building, as AI governance is a critical field with two distinct communities: policymakers crafting regulations and researchers/developers working on the technologies. The workshop aims to bring these communities together to foster collaboration and enhance understanding. The workshop aims to educate a broader community about the intricacies of AI governance. Through informative sessions and discussions, participants will gain a deeper understanding of the challenges posed by AI technologies and the need for effective governance.

This workshop will be a hybrid event held in conjunction with IJCAI 2024, taking place on Aug 4th, 2024 at Jeju, South Korea. The session will cover invited talks, contributed talks, posters, and a panel discussion.

Key Dates

  • Submission deadline: April 26th, 2024 May 10th, 2024 (11:59 pm AOE, FINAL EXTENSION)
  • Acceptance notification: June 8th, 2024
  • Camera ready for accepted submissions: June 20th, 2024

Confirmed Keynote and Invited Speakers

Organizing Committee

Technical Program Committee (TPC)

We would like to express our sincere gratitude to our technical program committee for generously volunteering their time and expertise to review submissions for our workshop. Their valuable contributions have been instrumental in ensuring the quality and rigor of the workshop’s program. We deeply appreciate their dedication and commitment to our workshop’s success:

Sonali Son, Yohan Mathew, Arian Khorasani, Ashraf Abdul, Serge Stinckwich, Giandomenico Cornacchia, Jawad Haqbeen, Chi Xie, Xiaoxia Lei, Lisa Lehmann, Prithviraj (Raj) Dasgupta, Sray Agarwal, Moncef Garouani, Chemlal Yman, Imran Nasim, Fakhare Alam, Adnan Zaidi, Zahid Farid, Pengwei Li, Manish Nagireddy, Jesus Rios Aliaga, Miao Liu, Muneeza Azmat, Kinjal Basu, Nudrat Nida, Inas Bachiri, Sarathkrishna Swaminathan


For any questions, please contact us at bl2681@columbia.edu.


  • Columbia University
  • Icahn School of Medicine at Mount Sinai
  • IBM Research
  • Mila - Quebec AI Institute
  • Fordham University