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Artificial Intelligence (AI) is at a crucial point in its development: stable enough to be used in production systems, and increasingly pervasive in our lives. What does that mean for its safety? In his book Normal Accidents, the sociologist Charles Perrow proposed a framework to analyze new technologies and the risks they entail. He showed that major accidents are nearly unavoidable in complex systems with tightly coupled components if they are run long enough. In this essay, we apply and extend Perrow’s framework to AI to assess its potential risks. Today’s AI systems are already highly complex, and their complexity is steadily increasing. As they become more ubiquitous, different algorithms will interact directly, leading to tightly coupled systems whose capacity to cause harm we will be unable to predict. We argue that under the current paradigm, Perrow’s normal accidents apply to AI systems and it is only a matter of time before one occurs.
This article appears in the AI & Society track.