Female Gendering of Artificial Intelligence in Travel: A Social Interaction Perspective
Yujia Chen, Hui Li, Tao Xue
- Year
- 2023
- Citations
- 5
Abstract
Implementing artificial intelligence enables the travel industry to improve efficiency, attract customers, and enhance their experiences. However, the typically biased social perceptions of humans are now applied to artificial intelligence, which has reinforced its female gendering in the industry. Nevertheless, the mechanism of its gendering process remains unclear. Guided by the gender theory, this study has explored how gendering is constructed through the social interaction perspective. Sixteen respondents who interacted with service robots or virtual assistants during their trip were recruited and interviewed via Zoom. Our findings suggest that the female gendering of artificial intelligence can be mapped from human-human to human-artificial intelligence interaction. Four main factors related to the social construction of the gendering process are identified. The findings contribute to understanding human-technology interaction and help tourism practitioners find a more cost-effective way to integrate human-technology collaboration strategies into their daily operations.
Keywords
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