Generative AI and human-robot interaction: implications and future agenda for business, society and ethics

被引:18
|
作者
Obrenovic, Bojan [1 ]
Gu, Xiao [2 ]
Wang, Guoyu [2 ]
Godinic, Danijela [3 ]
Jakhongirov, Ilimdorjon [4 ]
机构
[1] Zagreb Sch Econ & Management, Zagreb 10000, Croatia
[2] Commun Univ Zhejiang, Media Literacy Res Inst, Hangzhou 310018, Zhejiang, Peoples R China
[3] Univ Zagreb, Fac Humanities & Social Sci, Zagreb 10000, Croatia
[4] Ferghana Polytech Inst, Ferghana 150107, Uzbekistan
关键词
Generative AI; HRI; Human-robot interaction; Anthropomorphism; Humanoid robot; Robot; ChatGPT; Scientometric analyses; ANTHROPOMORPHISM; INTELLIGENCE; INTERFACE; TRUST;
D O I
10.1007/s00146-024-01889-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The revolution of artificial intelligence (AI), particularly generative AI, and its implications for human-robot interaction (HRI) opened up the debate on crucial regulatory, business, societal, and ethical considerations. This paper explores essential issues from the anthropomorphic perspective, examining the complex interplay between humans and AI models in societal and corporate contexts. We provided a comprehensive review of existing literature on HRI, with a special emphasis on the impact of generative models such as ChatGPT. The scientometric study posits that due to their advanced linguistic capabilities and ability to mimic human-like behavior, generative AIs like ChatGPT will continue to grow in popularity in pair with human rational empathy, tendency for personification and their advanced linguistic capabilities and ability to mimic human-like behavior. As they blur the boundaries between humans and robots, these models introduce fresh moral and philosophical dilemmas. Our research aims to extrapolate key trends and unique factors in HRI and to elucidate the technical aspects of generative AI that enhance its effectiveness in this field compared to traditional rule-based AI systems. We further discuss the challenges and limitations of applying generative AI in HRI, providing a future research agenda for AI optimization in diverse applications, including education, entertainment, and healthcare.
引用
收藏
页码:677 / 690
页数:14
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