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Computational Creativity in Marketing and Service: Applications, Acceptance, and Challenges
Authors: Christine Marie Auer (LMU Munich, Germany), Silke Bartsch (LMU Munich, Germany), Daniel Zimmermann (LMU Munich, Germany)
Artificial intelligence (AI) will shape the future of service in extraordinary ways (Wirtz et al., 2018). AI-based tools are increasingly affordable and can be empathetic, emotional and creative (Huang & Rust, 2018; IBM, 2018). They utilize what were previously considered distinctively “human” traits at an unprecedented rate and quality. This paper takes an outlook on computational creativity (CC) for marketing and service. It incorporates literature research and qualitative interviews in a threefold objective: Examining how CC is useful for marketing and service, how the acceptance of CC by consumers, marketers and service providers can be improved, and what potential challenges arise. The literature analysis provides definitions of AI, human creativity and CC (Siemon et al., 2015; Runco & Jaeger, 2012; Riedl, 2014; Colton and Wiggins, 2012), and categorizes the latter into "systems for artistic production" and "efforts for creative problem solving" (Besold et al., 2015a, p. 1). Based on an outline of current trends in marketing and service (Vargo & Lusch, 2017) and a discussion of the potential of CC applications in these fields, the first research question is derived: “(RQ1) How can machine-generated creativity be useful for marketing and service?”. The next section discusses human perceptions of CC. Drawing on anthropomorphism literature (Mori, MacDorman & Kageki, 2012; Epley, Waytz & Cacioppo, 2007), it leads to the second research question: “(RQ2) How can [CC’s] acceptance by consumers, marketers and service providers be improved?” The third part looks into AI-malfunctions (Bright, 2016), machine integration (Davis, 2013) and human replacement (Pophal, 2017), and introduces the final research question: “(RQ3) How can potential challenges that come with implementing [CC’s] use in practice be addressed?” Additionally, this paper presents findings from qualitative interviews with experts from the fields of computer science, service, marketing and media, law and academia as well as with consumers. While CC provides autonomous creative solutions, these are still costly and face social resistance from marketers and consumers. Additionally, marketing and service professionals want to leave strategic matters in human hands and players with limited data access and more stringent privacy laws are disadvantaged regarding AI and CC applications. The subsequent research agenda opens up topics on applied aspects, brings into focus questions for consumer research and psychology as well as political, ethical and regulatory issues. By investigating AI for advertising and customer engagement, this paper reflects the MSI’s research priorities of 2018-2020 (MSI, 2018, p. 7) and is the first to address the potential of AI for content creation and creative problem-solving. It contributes to current research by examining possible application areas, by shedding light on the acceptance of AI usage for creative tasks from a company and a consumer perspective, by demonstrating key challenges, and by stimulating future research.