Shadows across cultures: exploring the dark side of anthropomorphized agents

Shadows across cultures: exploring the dark side of anthropomorphized agents
Rehan Husain, Shalini Nath Tripathi
Journal of Consumer Marketing, Vol. ahead-of-print, No. ahead-of-print, pp.-

This study aims to delve into the cultural differences between developing and developed countries pertaining to the negative behavioral fallouts of adopting anthropomorphized humanoids or robots. The underlying motivation (for the study) lies in the fact that these countries are at the vanguard of artificial intelligence development and deployment, albeit with varying levels of development and acceptance.

The research framework used in this study is guided by the computers as social actors framework, expectancy disconfirmation theory and is supported by the uncanny valley theory. The data was collected in two contexts using probabilistic sampling technique, N= = 782 (n₁ = 393 respondents: developed country i.e. USA and n₂ = 389 respondents: developing country i.e. India). The partial least square analysis was carried out for the proposed model’s validation and hypotheses testing.

This study shows that in developed countries, the consumers have high preinteraction expectations while they express comparatively more dark behavior than respondents from developing countries. Consumers in developed countries focus on anthropomorphic knowledge and design cues, while in developing countries, they pay attention to utility and functionality. Finally, the results also suggest that female respondents from developed countries exhibit more resilience toward anthropomorphized agents in adopting and expressing dark behavior.

The present research makes essential contributions to anthropomorphism literature. First, this study explored impact of the interaction effect on the dark side, a rather under-explored domain in regret literature. Second, this study provides evidence for cross-cultural variations pertaining to the dark side impacts. Finally, this study adds to impact of demographic variables, showing that gender played a significant role in moderating relationships in the proposed model.

​This study aims to delve into the cultural differences between developing and developed countries pertaining to the negative behavioral fallouts of adopting anthropomorphized humanoids or robots. The underlying motivation (for the study) lies in the fact that these countries are at the vanguard of artificial intelligence development and deployment, albeit with varying levels of development and acceptance. The research framework used in this study is guided by the computers as social actors framework, expectancy disconfirmation theory and is supported by the uncanny valley theory. The data was collected in two contexts using probabilistic sampling technique, N= = 782 (n1 = 393 respondents: developed country i.e. USA and n2 = 389 respondents: developing country i.e. India). The partial least square analysis was carried out for the proposed model’s validation and hypotheses testing. This study shows that in developed countries, the consumers have high preinteraction expectations while they express comparatively more dark behavior than respondents from developing countries. Consumers in developed countries focus on anthropomorphic knowledge and design cues, while in developing countries, they pay attention to utility and functionality. Finally, the results also suggest that female respondents from developed countries exhibit more resilience toward anthropomorphized agents in adopting and expressing dark behavior. The present research makes essential contributions to anthropomorphism literature. First, this study explored impact of the interaction effect on the dark side, a rather under-explored domain in regret literature. Second, this study provides evidence for cross-cultural variations pertaining to the dark side impacts. Finally, this study adds to impact of demographic variables, showing that gender played a significant role in moderating relationships in the proposed model. Read More