The article "The Dark Side of Artificial Intelligence in Services" by Daniel Belanche, Russell W. Belk, Luis V. Casaló, and Carlos Flavián explores the potential negative impacts of AI implementation in service industries. The authors propose a three-part conceptual model inspired by Belanche et al. (2020a), focusing on AI design, customer features, and service interaction characteristics. They identify key factors and research gaps within each category, emphasizing the need to address the darker side of AI. In the section on AI design, the authors discuss the human aesthetics of AI, the identification and disclosure of AI, information bias and discrimination, responsibility, and the quality of communication. They highlight issues such as the uncanny valley effect, the misuse of AI for surveillance, the lack of transparency in AI decision-making, and the poor communication quality of AI-driven services. The customer section addresses the loss of privacy, cybersecurity, greater dependence and loss of human skills, social isolation, and customer tiers and engagement with technology. The authors warn about the increasing reliance on AI leading to privacy invasions, the need for better cybersecurity measures, the potential for social isolation, and the varying reactions of customers to AI-driven services. The service encounters section examines information misuse, employment replacement and social inequalities, the lack of emotion and empathy, the lack of consciousness and moral concern, and the lack of life purpose and life destruction. The authors discuss how AI can misuse customer data, replace human workers, lack emotional and empathetic responses, and lack the moral and conscious understanding of humans. Overall, the article provides a comprehensive overview of the potential negative consequences of AI in service industries, emphasizing the need for careful consideration and regulation to mitigate these impacts.The article "The Dark Side of Artificial Intelligence in Services" by Daniel Belanche, Russell W. Belk, Luis V. Casaló, and Carlos Flavián explores the potential negative impacts of AI implementation in service industries. The authors propose a three-part conceptual model inspired by Belanche et al. (2020a), focusing on AI design, customer features, and service interaction characteristics. They identify key factors and research gaps within each category, emphasizing the need to address the darker side of AI. In the section on AI design, the authors discuss the human aesthetics of AI, the identification and disclosure of AI, information bias and discrimination, responsibility, and the quality of communication. They highlight issues such as the uncanny valley effect, the misuse of AI for surveillance, the lack of transparency in AI decision-making, and the poor communication quality of AI-driven services. The customer section addresses the loss of privacy, cybersecurity, greater dependence and loss of human skills, social isolation, and customer tiers and engagement with technology. The authors warn about the increasing reliance on AI leading to privacy invasions, the need for better cybersecurity measures, the potential for social isolation, and the varying reactions of customers to AI-driven services. The service encounters section examines information misuse, employment replacement and social inequalities, the lack of emotion and empathy, the lack of consciousness and moral concern, and the lack of life purpose and life destruction. The authors discuss how AI can misuse customer data, replace human workers, lack emotional and empathetic responses, and lack the moral and conscious understanding of humans. Overall, the article provides a comprehensive overview of the potential negative consequences of AI in service industries, emphasizing the need for careful consideration and regulation to mitigate these impacts.