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This research examines the contrasting artificial intelligence (AI) governance strategies of the European Union (EU) and China, focusing on the dichotomy between human-centric and state-driven policies. The EU's approach, exemplified by the EU AI Act, emphasizes transparency, fairness, and individual rights protection, enforcing strict regulations for high-risk AI applications to build public trust. Conversely, China's state-driven model prioritizes rapid AI deployment and national security, often at the expense of individual privacy, as seen through its flexible regulatory framework and substantial investment in AI innovation. By applying the United States' National Institute of Standards and Technology (NIST) AI Risk Management Framework's Map, Measure, Manage, and Govern functions, this study explores how both regions balance technological advancement with ethical oversight. The study ultimately suggests that a harmonized approach, integrating elements of both models, could promote responsible global AI development and regulation. 

Social-educational robotics, such as NAO humanoid robots with social, anthropomorphic, humanlike features, are tools for learning, education, and addressing developmental disorders (e.g., autism spectrum disorder or ASD) through social and collaborative robotic interactions and interventions. There are significant gaps at the intersection of social robotics and autism research dealing with how robotic technology helps ASD individuals with their social, emotional, and communication needs, and supports teachers who engage with ASD students. This research aims to (a) obtain new scientific knowledge on social-educational robotics by exploring the usage of social robots (especially humanoids) and robotic interventions with ASD students at high schools through an ASD student–teacher co-working with social robot–social robotic interactions triad framework; (b) utilize Business Model Canvas (BMC) methodology for robot design and curriculum development targeted at ASD students; and (c) connect interdisciplinary areas of consumer behavior research, social robotics, and human-robot interaction using customer discovery interviews for bridging the gap between academic research on social robotics on the one hand, and industry development and customers on the other. The customer discovery process in this research results in eight core research propositions delineating the contexts that enable a higher quality learning environment corresponding with ASD students’ learning requirements through the use of social robots and preparing them for future learning and workforce environments. 

Anthropomorphism in social robots amplifies the big five human personality traits (extraversion, conscientiousness, neuroticism, openness to experience, and agreeableness), consequently aiding with the social motivation needs of consumers (especially individuals with autism spectrum disorder or ASD). According to the social motivation theory of autism, consumers with ASD show deficits in orienting toward social stimuli, engaging with humans, and maintaining social relations. Robotic anthropomorphism has been found to be positively related to the big five human personality types and robot likeability in human-robot interaction (HRI) situations. This research focuses on the conversational approach of social robotics using service-dominant approach. Conversation-based perspectives have been studied extensively in organizational and management literature; however, these perspectives have not been utilized in the context of social robots, HRI, and autism.