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Psychological variables of a person (e.g., cognitive abilities, personality traits, emotional states, and preferences) are valuable information that can be utilized by social robots to offer personalized human–robot interaction. These variables are often latent and inferred indirectly from a third-person perspective based on an individual’s behavioral manifestations (e.g., facial emotion expressions), and hence the true values of inferred psychological variables remain unknown to a robot observer. Although earlier studies have employed robot-administered psychological tests to infer psychological variables based on an individual’s first-person responses, these tests were formally presented and could be tedious to some users. To leverage the validity and reliability of well-established psychological tests for user profiling with ease, the present study examined the possibility of asynchronously embedding psychological test questions into casual human–robot conversations. In our experiment using a big-five personality inventory, the verbal responses from users to these asynchronous test questions were then compared with the written responses to the same personality test. The personality measures estimated from the two approaches correlated strongly in a young adult population but only moderately in an older population. These findings demonstrate the validity of the proposed asynchronous method for psychological testing in human–agent interactions and suggest some caveats when this testing method is applied to older adults or other special populations.

Asynchronously Embedding Psychological Test Questions into Human–Robot Conversations for User Profiling