论文标题
将AI伦理付诸实践:组织AI治理的沙漏模型
Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance
论文作者
论文摘要
人工智能(AI)的组织使用已迅速遍及各个部门。除了对AI带来的好处的认识之外,还越来越同意应对先进的AI技术带来的风险和潜在危害,例如偏见和歧视。已经提出了许多AI道德原则来应对这些风险,但是组织过程和实践的概述是确保社会负责的AI发展处于新生状态。为了解决综合治理模型的匮乏,我们提出了一个AI治理框架,即组织AI治理的沙漏模型,该模型针对开发和使用AI系统的组织。该框架旨在帮助部署AI系统的组织将道德AI原则转化为实践,并将其AI系统和流程与即将到来的欧洲AI法进行调整。沙漏框架包括环境,组织和AI系统级别的治理要求。在AI系统级别,我们将治理要求与AI系统生命周期联系起来,以确保整个系统寿命的治理。治理模型强调了AI治理的系统性,并为其实际实施,将不同的AI治理层连接的机制以及AI治理参与者之间的动态开放了新的研究途径。该模型还为组织决策者考虑了确保社会可接受性,减轻风险并实现AI潜力所需的治理组件的起点。
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.