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Going Beyond the Here and Now: Counterfactual Simulation in Human Cognition
The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.
The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.
The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infrastructure, because it over-emphasizes the capability layer.
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The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infrastructure, because it over-emphasizes the capability layer.
As humans, we spend much of our time going beyond the here and now. We dwell on the past, long for the future, and ponder how things could have turned out differently. In this talk, I will argue that people's knowledge of the world is organized around causally structured mental models, and that much of human thought can be understood as cognitive operations over these mental models. Specifically, I will highlight the pervasiveness of counterfactual thinking in human cognition. Counterfactuals are critical for how people make causal judgments, how they explain what happened, and how they hold others responsible for their actions.
