感知就是现实?了解用户对聊天机器人推断性格特征和自我报告性格特征的看法

Lingyao (Ivy) Yuan , Tianjun Sun , Alan R. Dennis , Michelle Zhou
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摘要

人工智能(AI)可以从网络行为中推断出一个人的性格,这为传统的自我报告性格评估提供了一个有趣的替代方案。最近有研究将人工智能推断出的个性与传统评估得出的个性进行了比较,发现两者之间存在明显差异(元分析发现,人工智能推断出的个性与调查得出的个性之间的平均相关性为 0.3)。一个重要但尚未回答的问题是,用户如何看待这两种方法得出的人格。用户认为哪种方法更准确,使用起来更令人满意?为了回答这个问题,我们使用这两种方法对 595 名参与者进行了性格评估,然后询问用户这两套结果与他们的匹配程度,以及他们的满意度和使用意向。参与者表示,尽管两种方法报告的人格分数不同,但两种结果同样适合他们。用户对两种方法的满意度相同,但更倾向于使用调查问卷,这可能是因为调查问卷花费的时间更少。我们的研究结果表明,两种方法都能测量用户性格的不同方面,而且两种方法都可能有用。我们讨论了人工智能推断与传统自我报告性格的利弊,并指出了人工智能推断性格评估的未来研究方向及其在现实世界应用中的意义。
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Perception is reality? Understanding user perceptions of chatbot-inferred versus self-reported personality traits

Artificial Intelligence (AI) can infer one's personality from online behavior, which offers an interesting alternative to traditional, self-reported personality assessments. Recent studies comparing AI-inferred personality to personality derived from traditional assessments have found noticeable differences between the two (meta-analyses have found mean correlations of 0.3 between AI-inferred personality and personality from surveys). One important but unanswered question is how users perceive their personality derived from both methods. Which do users perceive to be more accurate, and more satisfying to use? To answer this question, we used both methods to conduct personality assessments of 595 participants and then asked users how well the two sets of results fit them, as well as their satisfaction and intention to use them. Participants reported that both results fit them equally well, even though the two methods reported different personality scores. Users were equally satisfied with both methods but were more likely to use the survey, likely because it took less time. Our findings imply that both methods measure different aspects of user personality, and both may be useful. We discuss the pros and cons of AI-inferred versus traditional, self-reported personality and indicate future research directions of AI-inferred personality assessment and the implications of their use for real-world applications.

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