# A multilevel framework for AI governance

**Authors:** Hyesun Choung, Prabu David, John S. Seberger  
**arXiv:** [2307.03198](https://arxiv.org/abs/2307.03198)  
**Date:** 2023-07-04  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2307.03198v2/

## Key points

- Importance of developing a governance structure aligned with ethical principles and human values for AI governance
- Guidelines and ethical frameworks for trustworthy AI are not enough without a mediating governance structure
- Proposed multilevel approach involving governments, corporations, and citizens as key stakeholders in AI governance
- Examination of interrelationships through trust dimensions such as competence, integrity, and benevolence
- Practical insights to enhance user experiences and inform public policy related to AI
- Collaboration among stakeholders necessary for effective AI governance
- Structured framework addressing technical aspects of AI development and societal implications
- Need for proactive measures to govern AI technologies responsibly while upholding ethics and human values
- Important resource for policymakers, researchers, industry professionals, and other stakeholders involved in responsible development and deployment of AI technologies.

## Summary

, , , ,  In their paper titled "A Multilevel Framework for AI Governance," authors Hyesun Choung, Prabu David, and John S. Seberger emphasize the importance of developing a governance structure that aligns with ethical principles and fundamental human values to harness the potential benefits of artificial intelligence (AI) while mitigating its risks. Numerous organizations have issued guidelines and ethical frameworks for trustworthy AI, but these principles cannot be effectively implemented without a mediating governance structure. To address this gap, the authors propose a multilevel approach involving three key stakeholders: governments, corporations, and citizens. These groups are interdependent and play crucial roles in shaping the development and deployment of AI technologies. The authors examine their interrelationships through trust dimensions such as competence, integrity, and benevolence. By considering different levels of governance along with trust dimensions in AI, the proposed framework offers practical insights to enhance user experiences and inform public policy related to AI. This comprehensive approach recognizes that effective AI governance requires collaboration among various stakeholders to ensure ethical practices and protect human values. The authors' research contributes to the ongoing discourse on AI governance by providing a structured framework that addresses both technical aspects of AI development and societal implications. Their work highlights the need for proactive measures to govern AI technologies responsibly while upholding ethics and fundamental human values in order to maximize their potential benefits for society as a whole. This paper serves as an important resource for policymakers, researchers, industry professionals, and other stakeholders involved in shaping the responsible development and deployment of AI technologies.