[论文解读] Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance

Matti Mäntymäki, Matti Minkkinen+2 more|arXiv (Cornell University)|Jun 1, 2022

Ethics and Social Impacts of AI被引用 31

一句话总结

引入 hourglass 模型以将组织层面的AI治理转化为实践，将环境、组织与AI系统层级连接起来，以在整个系统生命周期中与欧洲AI法案保持一致。

ABSTRACT

The organizational use of artificial intelligence (AI) has rapidly spread across various sectors. Alongside the awareness of the benefits brought by AI, there is a growing consensus on the necessity of tackling the risks and potential harms, such as bias and discrimination, brought about by advanced AI technologies. A multitude of AI ethics principles have been proposed to tackle these risks, but the outlines of organizational processes and practices for ensuring socially responsible AI development are in a nascent state. To address the paucity of comprehensive governance models, we present an AI governance framework, the hourglass model of organizational AI governance, which targets organizations that develop and use AI systems. The framework is designed to help organizations deploying AI systems translate ethical AI principles into practice and align their AI systems and processes with the forthcoming European AI Act. The hourglass framework includes governance requirements at the environmental, organizational, and AI system levels. At the AI system level, we connect governance requirements to AI system life cycles to ensure governance throughout the system's life span. The governance model highlights the systemic nature of AI governance and opens new research avenues into its practical implementation, the mechanisms that connect different AI governance layers, and the dynamics between the AI governance actors. The model also offers a starting point for organizational decision-makers to consider the governance components needed to ensure social acceptability, mitigate risks, and realize the potential of AI.

研究动机与目标

• 推动在组织层面的AI使用中解决AI相关风险和危害（如偏见、歧视）。
• 提供将AI伦理原则转化为实践的全面治理框架。
• 使组织层面的AI治理与即将出台的监管标准（EU AI Act）保持一致。
• 提供覆盖环境、组织和AI系统层面的基于生命周期的治理方法。

提出的方法

• 提出 hourglass 治理框架，作为开发和使用AI系统的组织的结构。
• 将治理要求映射到环境、组织和AI系统层级。
• 将AI系统治理与系统生命周期连接起来，以确保在AI部署的整个生命周期内实施治理。
• 强调AI治理的系统性，以及需要连接治理层级的机制。
• 提出实际实施方向以及关于治理机制与参与者动态的未来研究方向。

实验结果

研究问题

• RQ1 在整个组织中，如何将伦理AI原则转化为实际治理？
• RQ2 在AI治理中，环境、组织和AI系统层级如何互动，以确保社会可接受性和风险缓释？
• RQ3 治理如何与现有或即将出台的法规（如欧洲AI法案）保持一致？
• RQ4 哪些机制连接不同的AI治理层级和参与者，以在系统生命周期内推动负责任的AI？

主要发现

• 将hourglass 模型作为组织AI使用的治理框架引入。
• 强调AI治理在环境、组织和AI系统层面上的系统性和多层次性。
• 将治理要求与AI系统生命周期相连接，以在系统的整个寿命期内支持治理。
• 识别关于实际实施、层间机制和参与者动态的AI治理新研究方向。
• 为决策者提供一个起点，以考虑实现社会可接受性和风险缓释的治理要素。