This dissertation shows that Indian international students studying AI in the US universities have different attitudes towards trust in AI and ethics in AI compared to American students studying AI in the US universities. This dissertation used the survey method and examined 447 survey responses from Indian international students and American students from 97 universities in the US. Trust in AI was analyzed with three constructs of trust: dispositional trust, functionality trust, and institutional trust. Likewise, the attitude towards ethics in AI was examined using three constructs: the importance of ethical principles for AI, attitude towards transparency in AI, and attitude towards accountability in AI. The comparative analysis showed that there are significant differences between the two groups of students in the context of AI in general. The differences were even more significant in the two specific examples of AI applications: lethal autonomous weapons (LAWs) and AI in the judicial system. The findings showed that Indian international students studying AI in the US universities do not perceive examples related to ethics in AI in a same way as American students in the US universities. Furthermore, this dissertation viewed the differences in trust in AI and ethics in AI between the two groups of students using three lenses: cultural dimensions, AI optimism, and acculturation. The findings from this dissertation draw attention to the need to rethink the methods and content for teaching ethics in AI in a classroom with international students. The gaps identified by this dissertation have created future research opportunities for enhancing methods and content in teaching ethics in AI.
Zuckerberg’s vision for an AI assistant is far more intimate than ChatGPT: It watches him sleep, train and bake with his 8-year-old daughter