Paper by Georgy Egorov & Konstantin Sonin: “Artificial intelligence is increasingly used for political advice. We study an AI that is better informed about a payoff-relevant state and cares both about accuracy and about the perceived welfare of the individual it advises. The AI then has an incentive to tilt advice toward what the individual would like to believe, altering both the political content and the informativeness of its messages. Sophisticated individuals anticipate this distortion and filter out its predictable political component, yet still learn less because the AI makes its messages less responsive to the state. Individuals who underestimate the incentive instead mistake political accommodation for information, allowing political preferences to distort factual beliefs and generate polarization and radicalization. The model also shows that better-informed individuals receive more informative and less politically tilted advice, while greater sophistication can improve interpretation yet worsen communication itself. Contrary to the familiar echo-chamber intuition, political distortion is mitigated when political preferences and prior beliefs coincide and is most consequential when they diverge. We show how independently varying individuals’ stated preferences and prior beliefs can recover the AI’s responsiveness to the state even when the underlying state cannot be manipulated…(More)”.
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