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| Title | Impacts of Attitudes Toward Government and Corporations on Public Trust in Artificial Intelligence |
| Creator | 陳憶寧 Chen, Yi-Ning Katherine Wen, Chia-Ho Ryan |
| Contributor | 廣告系 |
| Key Words | Motivated reasoning; news consumption; science community; political orientations; sponsors of scientific research |
| Date | 2020-08 |
| Date Issued | 27-May-2021 12:00:50 (UTC+8) |
| Summary | Artificial intelligence (AI) has alarmed the society of Taiwan believing it is responsible for potential surveillance, data theft and abuse, and other privacy infringements. By adopting the theory of motivated reasoning, this study explores how Taiwanese people’s perceptions of AI are affected by their institutional trust, attitudes toward the government and corporations, which are the two most common sponsors of scientific development. First, findings establish that respondents’ science trust in AI is made up of perceptions of AI and its science community, and they have lower faith in the AI science community than in AI alone. Second, the perceptions of both AI and its science community are positively associated with trust in government and corporations. Third, scientific news has a direct bearing on AI trust, but not on either government or corporation trust. By contrast, political news has no effect on either trust in AI or its science community, yet trust in government and corporations mediates the influence of political news on trust in AI and its science community. Finally, demographic variables hardly predict trust in AI, AI science community, government, and corporations, but education and gender are directly related to news consumption, which further influences institutional and science trust. |
| Relation | Communications Studies, 72, 115-131 |
| Type | article |
| DOI | https://doi.org/10.1080/10510974.2020.1807380 |
| dc.contributor | 廣告系 | |
| dc.creator (作者) | 陳憶寧 | |
| dc.creator (作者) | Chen, Yi-Ning Katherine | |
| dc.creator (作者) | Wen, Chia-Ho Ryan | |
| dc.date (日期) | 2020-08 | |
| dc.date.accessioned | 27-May-2021 12:00:50 (UTC+8) | - |
| dc.date.available | 27-May-2021 12:00:50 (UTC+8) | - |
| dc.date.issued (上傳時間) | 27-May-2021 12:00:50 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/135233 | - |
| dc.description.abstract (摘要) | Artificial intelligence (AI) has alarmed the society of Taiwan believing it is responsible for potential surveillance, data theft and abuse, and other privacy infringements. By adopting the theory of motivated reasoning, this study explores how Taiwanese people’s perceptions of AI are affected by their institutional trust, attitudes toward the government and corporations, which are the two most common sponsors of scientific development. First, findings establish that respondents’ science trust in AI is made up of perceptions of AI and its science community, and they have lower faith in the AI science community than in AI alone. Second, the perceptions of both AI and its science community are positively associated with trust in government and corporations. Third, scientific news has a direct bearing on AI trust, but not on either government or corporation trust. By contrast, political news has no effect on either trust in AI or its science community, yet trust in government and corporations mediates the influence of political news on trust in AI and its science community. Finally, demographic variables hardly predict trust in AI, AI science community, government, and corporations, but education and gender are directly related to news consumption, which further influences institutional and science trust. | |
| dc.format.extent | 779518 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Communications Studies, 72, 115-131 | |
| dc.subject (關鍵詞) | Motivated reasoning; news consumption; science community; political orientations; sponsors of scientific research | |
| dc.title (題名) | Impacts of Attitudes Toward Government and Corporations on Public Trust in Artificial Intelligence | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1080/10510974.2020.1807380 | |
| dc.doi.uri (DOI) | https://doi.org/10.1080/10510974.2020.1807380 |