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Artificial intelligence: The light and the darkness

Author

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  • Grewal, Dhruv
  • Guha, Abhijit
  • Satornino, Cinthia B.
  • Schweiger, Elisa B.

Abstract

That artificial intelligence (AI) has the potential to provide significant benefits is generally accepted by both practitioners and scholars. However, the dark side of AI is less discussed, and less understood. In this paper, the authors first classify the wellspring of AI benefits in both B2C and B2B settings. In B2C settings AI benefits are primarily via customized experiences, while B2B AI benefits are manifested via business efficiencies. Next, guided by the relationship marketing literature, the authors identify the drivers of the dark side of AI - lack of trust and power asymmetries, with lack of trust being a stronger factor in B2C settings and power asymmetries being a stronger factor in B2B settings. Finally, the authors provide an organizing framework for understanding both the bright side and the dark side of AI, in both B2C settings and B2B settings. This paper is differentiated from prior work by its focus on B2B settings (most focus on B2C settings), and by its focus on the dark side of AI (most focus on the bright side of AI).

Suggested Citation

  • Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    • Handle: RePEc:eee:jbrese:v:136:y:2021:i:c:p:229-236
    DOI: 10.1016/j.jbusres.2021.07.043
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    1. Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
    2. Verónica H. Villena & Christopher W. Craighead, 2017. "On the Same Page? How Asymmetric Buyer–Supplier Relationships Affect Opportunism and Performance," Production and Operations Management, Production and Operations Management Society, vol. 26(3), pages 491-508, March.
    3. Arun Rai, 2020. "Explainable AI: from black box to glass box," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 137-141, January.
    4. Matthew J. Schneider & Sharan Jagpal & Sachin Gupta & Shaobo Li & Yan Yu, 2018. "A Flexible Method for Protecting Marketing Data: An Application to Point-of-Sale Data," Marketing Science, INFORMS, vol. 37(1), pages 153-171, January.
    5. Aguirre, Elizabeth & Mahr, Dominik & Grewal, Dhruv & de Ruyter, Ko & Wetzels, Martin, 2015. "Unraveling the Personalization Paradox: The Effect of Information Collection and Trust-Building Strategies on Online Advertisement Effectiveness," Journal of Retailing, Elsevier, vol. 91(1), pages 34-49.
    6. Paschen, Jeannette & Wilson, Matthew & Ferreira, João J., 2020. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel," Business Horizons, Elsevier, vol. 63(3), pages 403-414.
    7. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
    8. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    9. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
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    Cited by:

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    2. Abhijit Guha & Timna Bressgott & Dhruv Grewal & Dominik Mahr & Martin Wetzels & Elisa Schweiger, 2023. "How artificiality and intelligence affect voice assistant evaluations," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 843-866, July.
    3. Qian, Lixian & Yin, Juelin & Huang, Youlin & Liang, Ya, 2023. "The role of values and ethics in influencing consumers’ intention to use autonomous vehicle hailing services," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Jameel, Alaa S. & Harjan, Sinan Abdullah & Ahmad, Abd Rahman, 2023. "Behavioral Intentions to use Artificial Intelligence Among Managers in Small and Medium Enterprises," OSF Preprints w69yh, Center for Open Science.
    5. Dhiman, Neeraj & Jamwal, Mohit & Kumar, Ajay, 2023. "Enhancing value in customer journey by considering the (ad)option of artificial intelligence tools," Journal of Business Research, Elsevier, vol. 167(C).
    6. Satornino, Cinthia B. & Grewal, Dhruv & Guha, Abhijit & Schweiger, Elisa B. & Goodstein, Ronald C., 2023. "The perks and perils of artificial intelligence use in lateral exchange markets," Journal of Business Research, Elsevier, vol. 158(C).
    7. Xusen Cheng & Xiao Lin & Xiao-Liang Shen & Alex Zarifis & Jian Mou, 2022. "The dark sides of AI," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 11-15, March.
    8. Pervaiz Akhtar & Arsalan Mujahid Ghouri & Haseeb Ur Rehman Khan & Mirza Amin ul Haq & Usama Awan & Nadia Zahoor & Zaheer Khan & Aniqa Ashraf, 2023. "Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions," Annals of Operations Research, Springer, vol. 327(2), pages 633-657, August.

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