Who Likes Artificial Intelligence? Personality Predictors of Attitudes toward Artificial Intelligence.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2022-01-01 Epub Date: 2022-01-11 DOI:10.1080/00223980.2021.2012109
Jiyoung Park, Sang Eun Woo
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引用次数: 11

Abstract

We examined how individuals' personality relates to various attitudes toward artificial intelligence (AI). Attitudes were organized into two dimensions of affective components (positive and negative emotions) and two dimensions of cognitive components (sociality and functionality). For personality, we focused on the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, openness) and personal innovativeness in information technology. Based on a survey of 1,530 South Korean adults, we found that extraversion was related to negative emotions and low functionality. Agreeableness was associated with both positive and negative emotions, and it was positively associated with sociality and functionality. Conscientiousness was negatively related to negative emotions, and it was associated with high functionality, but also with low sociality. Neuroticism was related to negative emotions, but also to high sociality. Openness was positively linked to functionality, but did not predict other attitudes when other proximal predictors were included (e.g. prior use, personal innovativeness). Personal innovativeness in information technology consistently showed positive attitudes toward AI across all four dimensions. These findings provide mixed support for our hypotheses, and we discuss specific implications for future research and practice.

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谁喜欢人工智能?对人工智能态度的人格预测。
我们研究了个体的个性与对人工智能(AI)的各种态度之间的关系。态度分为情感成分(积极情绪和消极情绪)和认知成分(社会性和功能性)两个维度。在人格方面,我们关注的是五大人格特征(外向性、宜人性、尽责性、神经质、开放性)和个人在信息技术方面的创新能力。根据对1530名韩国成年人的调查,我们发现外向性与负面情绪和低功能有关。宜人性与积极情绪和消极情绪都相关,并且与社会性和功能性呈正相关。尽责性与负面情绪呈负相关,与高功能性相关,但也与低社会性相关。神经质与负面情绪有关,但也与高度社会性有关。开放性与功能性正相关,但当包括其他近端预测因素(例如,先前使用,个人创新)时,开放性并不能预测其他态度。个人在信息技术方面的创新在所有四个维度上始终表现出对人工智能的积极态度。这些发现为我们的假设提供了不同的支持,并讨论了对未来研究和实践的具体影响。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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