UCLA faculty voice: Artificial intelligence can’t reason why
Computer programs have reached a bewildering point in their long and unsteady journey toward artificial intelligence. They outperform people at tasks we once felt to be uniquely human, such as playing poker or recognizing faces in a crowd. Meanwhile, self-driving cars using similar technology run into pedestrians and posts and we wonder whether they can ever be trustworthy.
Amid these rapid developments and nagging setbacks, one essential building block of human intelligence has eluded machines for decades: Understanding cause and effect.
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