It turns out that both graduate students and humans tend to evaluate faulty arguments as true if their content seems logically sound. In the Wason task, in which participants must determine whether a rule is true by checking a series of cards containing letters and numbers, AIs and humans make similar mistakes. For example, instead of testing information that might support a rule, they test contrasting conditions that do not provide the information they need.
Interestingly, when abstract rules are replaced with socially meaningful ones, such as people’s age and alcohol consumption, Masters and humans perform better. Research suggests that Masters, like humans, need formal training to improve their logical thinking.
Source: Ferra
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