Leaving AI unsupervised is like leaving a 5‑year‑old alone
Artificial intelligence governance frameworks have largely evolved around systems that are networked, centrally updated, cloud-monitored, and subject, at least in principle, to some form of human or institutional oversight. Yet a growing class of AI systems operates in conditions that challenge this paradigm. Systems that function offline, adapt locally and autonomously,…
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Implicit Assumptions About Human Behavior Embedded in AI Systems Prior to Prediction
Executive Lay Summary Artificial intelligence systems are often evaluated based on their outputs: prediction accuracy, error rates, fairness metrics, or performance benchmarks. However, long before an AI system produces a single prediction, it already embodies a set of assumptions about human behavior. These assumptions are not incidental but are structurally embedded…
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