Navigating the Human-Machine Boundary

Introduction

The Rise of Emotive AI, Special issue of P sychology & Marketing; Deadline 31 Oct 2024

INTEREST CATEGORY: CONSUMER BEHAVIOR
POSTING TYPE: Calls: Journals

Posted by: Zhibin Lin

Call for Papers

Navigating the Human-Machine Boundary: The Rise of Emotive AI

Submission Window: August 31, 2024 to October 31, 2024

The application of artificial intelligence (AI) in marketing and consumer research is a growing area of interest (Mariani et al., 2022; Mehta et al., 2022), characterized by diversity and multifaceted perspectives. Research has ranged from exploring customer emotional attachments and relationships with AI technologies, in particular, service robots (Filieri et al., 2022; Pentina et al., 2023), to examining consumer trust in voice-based AI systems (Pitardi & Marriott, 2021), analyzing electronic word-of-mouth marketing using AI (Oc et al., 2023), and investigating emotional responses to AI-based service failures (Pavone et al., 2023). Existing research also covers AI applications within the tourism and hospitality sector by looking into tourism products and travel services (Kargar & Lin, 2021; Zheng et al., 2020). Apart from the empirical research examines consumer engagement with AI technologies (Hollebeek et al., 2019; Hollebeek & Belk, 2021; Hollebeek et al., 2024), some work also looks at advancing theory in marketing and AI (Ameen et al., 2022) and providing AI implementing frameworks (Huang & Rust, 2022; Wu & Monfort, 2023).

The rapidly growing social and emotional intelligence of AI starts to blur the lines between humans and machines (Pentina et al., 2023; Zhu et al., 2023). Emotive AI could transform industries by improving customer experiences through tailored interactions (Mariani et al., 2022; Mehta et al., 2022). In healthcare, it may enhance diagnostic accuracy, patient engagement, and satisfaction by providing personalized and emotional support. In education, adaptive learning systems could promote student success via emotional scaffolding. Emotive AI enables computers to better understand and respond to human emotions and social dynamics (Filieri et al., 2022).

However, the ascent of emotive AI forces us to be cautious of its influence on human identity, autonomy, privacy, and equality (De Freitas et al., 2023). This on the other hand brings monumental ethical consideration and existential inquiries about the relationship between emotive AI and human well-being (Hollebeek et al., 2024; Zhu et al., 2023), raising concerns about manipulation, isolation, inequality, and the erosion of what makes us human. As the distinction between creator and creation fades, difficult philosophical questions also emerge about the ethics of marketing and consumption of AI (Hollebeek & Belk, 2021). This complex duality of AI underscores the urgent need for research to address concerns about threats of emotive AI, in particular, responding to irresponsible AI promotion and adoption (Davenport et al., 2020; Huang & Rust, 2022).

With technological innovation outpacing ethical foresight, guidelines for equitable, transparent and accountable AI systems are indispensable (Wang & Hang, 2021). As emotive AI systems become increasingly adopted, it is crucial we understand their potential opportunities as well as pitfalls in order to promote their ethical and responsible use (Kargar & Lin, 2021; Zheng et al., 2020). This special issue aims to bridge knowledge gaps across disciplines to uphold human values and inform responsible policymaking amidst AI’s coming of age (Oc et al., 2023; Weng et al., 2021). We strive to place human dignity and autonomy at the center while navigating emerging implications around trust, autonomy, identity, and ethics (Kim, Giroux, & Lee, 2021). By fostering interdisciplinary insights on emotive AI, this special issue aspires to cover crucial issues around its influence on human relationships and well-being. At the same time, we look to tap into its potential to improve decision-making and collaboration in many facets of life.

Articles considered for this Special Issue may focus on topics including, but not limited to:

Bonding, User Experience & Trust:

      • Can an emotional connection to AI transcend mere satisfaction, leading to deeper human-AI engagement and emotional dependence?
      • Can users develop genuine trust and build long-term, reliable relationships with emotive AI?
      • Could AI companions with emotional capabilities strengthen social bonds or contribute to social isolation?
      • How can we ensure technology enhances, rather than erodes, our real-world connections?

Choice Architecture & Co-creation:

      • How can we leverage AI’s emotional intelligence to nudge users towards healthier choices and ethical consumption patterns, without infringing on autonomy?
      • Can human-AI partnerships lead to breakthroughs in areas like personalized healthcare and creative expression?

Cultural Identity & Expression:

      • Will AI with emotional intelligence homogenize cultural expressions or offer unique tools for identity exploration?
      • How can AI facilitate cultural understanding and appreciation?

Ethical Consideration, Responsible Innovation & Policy Challenges:

      • What novel ethical frameworks will be needed to ensure responsible AI consumption?
      • How can we overcome the technical and ethical challenges of developing emotionally safe and responsible AI, navigating complex issues like data privacy and algorithmic bias?
      • Can flexible yet robust regulations effectively balance innovation with ethical considerations of emotive AI consumption?
      • How can we mitigate discriminatory patterns of emotive AI when it comes to multicultural society and its impact on consumer acculturation?
      • As AI becomes more emotionally adept, how can we maintain human control and decision-making within AI attachment?

Guest Editors:

Professor Zhibin Lin, Professor of Marketing, Durham University, UK.

Dr Qionglei Yu, Associate Professor in Marketing, Newcastle University, UK.

Professor Raffaele Filieri, Professor of Digital Marketing, Audencia Business School, France.

Professor Haiming Hang, Professor of Marketing, University of Bath, UK

Professor Weisha Wang, Professor of Marketing, Soochow University, China.

Professor Linda D. Hollebeek, the Teng Yew Huat Endowed Chair of Marketing, Sunway University, Malaysia.

Managing Editor:

Professor Zhibin Lin, Email: zhibin.lin@durham.ac.uk).
Please contact Professor Lin with any questions regarding this special issue.

Submission Deadline:October 31, 2024

To submit a manuscript, follow the manuscript submission guidelines outlined in the “Instructions for Authors” on the Psychology & Marketing website. Be sure to select the correct Special Issue and also mention it in the letter to the editor. The system will be open for submissions to the Special Issue from August 31, 2024 to October 31, 2024.

References

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Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing.Journal of the Academy of Marketing Science, 48, 24-42.

De Freitas, J., Uğuralp, A. K., Oğuz‐Uğuralp, Z., & Puntoni, S. (2023). Chatbots and mental health: Insights into the safety of generative ai.Journal of Consumer Psychology. (In press)

Filieri, R., Lin, Z., Li, Y., Lu, X., & Yang, X. (2022). Customer emotions in service robot encounters: A hybrid machine-human intelligence approach.Journal of Service Research, 25(4), 614-629.

Hang, H., & Chen, Z. (2022). How to realize the full potentials of artificial intelligence (AI) in digital economy? A literature review.Journal of Digital Economy, 1(3), 180-191.

Hollebeek, L. D., & Belk, R. (2021). Consumers’ technology-facilitated brand engagement and wellbeing: Positivist TAM/PERMA-vs. Consumer Culture Theory perspectives.International Journal of Research in Marketing, 38(2), 387-401.

Hollebeek, L. D., Menidjel, C., Sarstedt, M., Jansson, J., & Urbonavicius, S. (2024). Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further research.Psychology & Marketing.(In press)

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Huang, M. H., & Rust, R. T. (2022). A framework for collaborative artificial intelligence in marketing.Journal of Retailing, 98(2), 209-223.

Kargar, M., & Lin, Z. (2021). A socially motivating and environmentally friendly tour recommendation framework for tourist groups.Expert Systems with Applications, 180, 115083.

Kim, J., Giroux, M., & Lee, J. C. (2021). When do you trust AI? The effect of number presentation detail on consumer trust and acceptance of AI recommendations.Psychology and Marketing, 38(7), 1140–1155.

Mariani, M. M., Perez‐Vega, R., & Wirtz, J. (2022). AI in marketing, consumer research and psychology: A systematic literature review and research agenda.Psychology & Marketing, 39(4), 755-776.

Mehta, P., Jebarajakirthy, C., Maseeh, H. I., Anubha, A., Saha, R., & Dhanda, K. (2022). Artificial intelligence in marketing: A meta‐analytic review.Psychology & Marketing, 39(11), 2013-2038.

Oc, Y., Plangger, K., Sands, S., Campbell, C. L., & Pitt, L. (2023). Luxury is what you say: Analyzing electronic word-of-mouth marketing of luxury products using artificial intelligence and machine learning.Psychology and Marketing, 40(9), 1704–1719.

Pavone, G., Meyer-Waarden, L., & Munzel, A. (2023). Rage against the machine: experimental insights into customers’ negative emotional responses, attributions of responsibility, and coping strategies in artificial intelligence–based service failures.Journal of Interactive Marketing, 58(1), 52-71.

Pentina, I., Xie, T., Hancock, T., & Bailey, A. (2023). Consumer–machine relationships in the age of artificial intelligence: Systematic literature review and research directions.Psychology and Marketing, 40(8), 1593–1614.

Pitardi, V., & Marriott, H. R. (2021). Alexa, she’s not human but… Unveiling the drivers of consumers’ trust in voice-based artificial intelligence.Psychology and Marketing, 38(4), 626–642.

Wang, W., & Hang, H. (2021). Exploring the eudaimonic game experience through purchasing functional and non-functional items in MMORPGs.Psychology and Marketing, 38(10), 1847-1862.

Weng, L., Zhang, Q., Lin, Z., & Wu, L. (2021). Harnessing heterogeneous social networks for better recommendations: A grey relational analysis approach.Expert Systems with Applications, 174, 114771.

Wu, C. W., & Monfort, A. (2023). Role of artificial intelligence in marketing strategies and performance.Psychology and Marketing, 40(3), 484–496.

Zheng, W., Liao, Z., & Lin, Z. (2020). Navigating through the complex transport system: A heuristic approach for city tourism recommendation. Tourism management, 81, 104162.

Zhu, T., Lin, Z., & Liu, X. (2023). The future is now? Consumers’ paradoxical expectations of human-like service robots.Technological Forecasting and Social Change, 196, 122830.

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