2022/06/01 by Matti Mäntymäki, Mäntymäki, Matti, Matti Minkkinen +5 · 2 citations
Decision Sciences · Social Sciences · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #Ethics and Social Impacts of AI #Ethics in Business and Education #FOS: Computer and information sciences #Innovation, Sustainability, Human-Machine Systems
paper · pdf · doi:10.48550/arxiv.2206.00335
openalex publication_date 2022/06/01 · openalex created_date 2022/06/13 · openalex updated_date 2026/08/01
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.