Perceptions of the Impact of High-Level-Machine-Intelligence from University Students in Taiwan: The Case for Human Professions, Autonomous Vehicles, and Smart Homes

Su-Yen Chen and Chiachun Lee
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Su-Yen Chen: Institute of Learning Sciences and Technologies, National Tsing Hua University, Hsinchu 30013, Taiwan
Chiachun Lee: Institute of Learning Sciences and Technologies, National Tsing Hua University, Hsinchu 30013, Taiwan

Sustainability, 2019, vol. 11, issue 21, 1-14

Abstract: There is a “timing optimism” that artificial general intelligence will be achieved soon, but some literature has suggested that people have mixed feelings about its overall impact. This study expanded their findings by investigating how Taiwanese university students perceived the overall impact of high-level-machine-intelligence (HLMI) in three areas: a set of 12 human professions, autonomous vehicles, and smart homes. Respondents showed a relatively more positive attitude, with a median answer of “on balance good”, toward HLMI’s development corresponding to those occupations having a higher probability of automation and computerization, and a less positive attitude, with a median of “more or less neutral”, toward professions involving human judgment and social intelligence, and especially creativity, which had a median of “on balance bad”. On the other hand, they presented a highly positive attitude toward the AI application of the smart home, while they demonstrated relatively more reservation toward autonomous vehicles. Gender, area of study, and a computer science background were found as predictors in many cases, whereas traffic benefits, and safety and regulation concerns, among others, were found as the most significant predictors for the overall impact of autonomous vehicles, with comfort and support benefits being the most significant predictor for smart homes. Recommendations for educators, policy makers, and future research were provided.

Keywords: artificial intelligence; technological unemployment; autonomous vehicles; smart home; perceptions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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