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2024 | OriginalPaper | Buchkapitel

Introduction to Explainable AI (XAI) in E-Commerce

verfasst von : Meenu Chaudhary, Loveleen Gaur, Gurinder Singh, Anam Afaq

Erschienen in: Role of Explainable Artificial Intelligence in E-Commerce

Verlag: Springer Nature Switzerland

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Abstract

In the ever-evolving landscape of technology, companies strive for innovation to maintain competitiveness. Artificial Intelligence (AI) has permeated every sector, and in the realm of e-commerce (EC), its impact is notably evident. Various AI applications, such as recommendation systems, fake filters, and fraud detection, have greatly benefited the EC industry. However, a lingering issue is the challenge of understanding and explaining the outcomes generated by AI algorithms, which, in turn, affects their trustworthiness. In addressing this concern, there’s an ongoing discourse regarding the ethics and privacy implications of AI, prompting additional research endeavors. The objective is to enhance the trustworthiness and ethical standing of AI systems. This has led to the resurgence of Explainable AI (XAI), a domain focused on making AI results more comprehensible to users. The prevailing challenge lies in the fact that existing technologies often fall short in providing detailed explanations of how algorithms arrive at specific results or recommendations. Specifically in e-commerce, where decisions often demand immediate action, the integration of XAI systems becomes crucial. These systems aim to provide instant justifications, filling the gap left by current technologies that struggle to offer thorough explanations of the decision-making process behind AI-generated results or recommendations.

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Literatur
1.
Zurück zum Zitat Gielens, K., & Steenkamp, J. B. E. (2019). Branding in the era of digital (dis) intermediation. International Journal of Research in Marketing, 36(3), 367–384.CrossRef Gielens, K., & Steenkamp, J. B. E. (2019). Branding in the era of digital (dis) intermediation. International Journal of Research in Marketing, 36(3), 367–384.CrossRef
2.
Zurück zum Zitat Tan, F. T. C., Pan, S. L., & Zuo, M. (2019). Realising platform operational agility through information technology–enabled capabilities: A resource-interdependence perspective. Information Systems Journal, 29(3), 582–608.CrossRef Tan, F. T. C., Pan, S. L., & Zuo, M. (2019). Realising platform operational agility through information technology–enabled capabilities: A resource-interdependence perspective. Information Systems Journal, 29(3), 582–608.CrossRef
3.
Zurück zum Zitat Khrais, L. T., & Azizi, T. A. (2020). Analyzing consumer attitude toward mobile payment technology and its role in booming the e-commerce business. Talent Development and Excellence, 12. Khrais, L. T., & Azizi, T. A. (2020). Analyzing consumer attitude toward mobile payment technology and its role in booming the e-commerce business. Talent Development and Excellence12.
4.
Zurück zum Zitat Areiqat, A. Y., Hamdan, A., Alheet, A. F., & Alareeni, B. (2021). Impact of artificial intelligence on E-commerce development. In The Importance of New Technologies and Entrepreneurship in Business Development: In The Context of Economic Diversity in Developing Countries: The Impact of New Technologies and Entrepreneurship on Business Development (pp. 571–578). Springer International Publishing. Areiqat, A. Y., Hamdan, A., Alheet, A. F., & Alareeni, B. (2021). Impact of artificial intelligence on E-commerce development. In The Importance of New Technologies and Entrepreneurship in Business Development: In The Context of Economic Diversity in Developing Countries: The Impact of New Technologies and Entrepreneurship on Business Development (pp. 571–578). Springer International Publishing.
5.
Zurück zum Zitat Gururaj, P. (2021). Artificial intelligence-application in the field of e-commerce. Int. J. Res.-Granthaalayah, 9, 170–177. Gururaj, P. (2021). Artificial intelligence-application in the field of e-commerce. Int. J. Res.-Granthaalayah, 9, 170–177.
6.
Zurück zum Zitat Firschein, O., Fischler, M. A., Coles, L. S., & Tenenbaum, J. M. (1973, August). Forecasting and assessing the impact of artificial intelligence on society. In IJCAI (Vol. 5, No. 1, pp. 105–120). Firschein, O., Fischler, M. A., Coles, L. S., & Tenenbaum, J. M. (1973, August). Forecasting and assessing the impact of artificial intelligence on society. In IJCAI (Vol. 5, No. 1, pp. 105–120).
7.
Zurück zum Zitat Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2020). Artificial intelligence in business: From research and innovation to market deployment. Procedia Computer Science, 167, 2200–2210.CrossRef Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2020). Artificial intelligence in business: From research and innovation to market deployment. Procedia Computer Science, 167, 2200–2210.CrossRef
8.
Zurück zum Zitat Shyna, K., & Vishal, M. (2017). A study on artificial intelligence E-commerce. International Journal of Advances in Engineering and Scientific Research, 4(4), 62–68. Shyna, K., & Vishal, M. (2017). A study on artificial intelligence E-commerce. International Journal of Advances in Engineering and Scientific Research, 4(4), 62–68.
9.
Zurück zum Zitat Chaudhary, M., Gaur, L., & Chakrabarti, A. (2022, April). Comparative analysis of entropy weight method and c5 classifier for predicting employee churn. In 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM) (pp. 232–236). IEEE. Chaudhary, M., Gaur, L., & Chakrabarti, A. (2022, April). Comparative analysis of entropy weight method and c5 classifier for predicting employee churn. In 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM) (pp. 232–236). IEEE.
10.
Zurück zum Zitat Rana, J., Gaur, L., Singh, G., Awan, U., & Rasheed, M. I. (2021). Reinforcing customer journey through artificial intelligence: A review and research agenda. International Journal of Emerging Markets, 17(7), 1738–1758.CrossRef Rana, J., Gaur, L., Singh, G., Awan, U., & Rasheed, M. I. (2021). Reinforcing customer journey through artificial intelligence: A review and research agenda. International Journal of Emerging Markets, 17(7), 1738–1758.CrossRef
11.
Zurück zum Zitat Chaudhary, M., Gaur, L., Chakrabarti, A., & Jhanjhi, N. Z. (2023). Unravelling the Barriers of human resource analytics: Multi-criteria decision-making approach. Journal of Survey in Fisheries Sciences, 306–321. Chaudhary, M., Gaur, L., Chakrabarti, A., & Jhanjhi, N. Z. (2023). Unravelling the Barriers of human resource analytics: Multi-criteria decision-making approach. Journal of Survey in Fisheries Sciences, 306–321.
12.
Zurück zum Zitat Khrais, L. T. (2020). Role of artificial intelligence in shaping consumer demand in E-commerce. Future Internet, 12(12), 226.CrossRef Khrais, L. T. (2020). Role of artificial intelligence in shaping consumer demand in E-commerce. Future Internet, 12(12), 226.CrossRef
13.
Zurück zum Zitat Afaq, A., Gaur, L., Singh, G., & Dhir, A. (2021). COVID-19: Transforming air passengers’ behaviour and reshaping their expectations towards the airline industry. Tourism Recreation Research, 1–9. Afaq, A., Gaur, L., Singh, G., & Dhir, A. (2021). COVID-19: Transforming air passengers’ behaviour and reshaping their expectations towards the airline industry. Tourism Recreation Research, 1–9.
14.
Zurück zum Zitat Van Lent, M., Fisher, W., & Mancuso, M. (2004, July). An explainable artificial intelligence system for small-unit tactical behavior. In Proceedings of the National Conference on Artificial Intelligence (pp. 900–907). AAAI Press; MIT Press; 1999. Van Lent, M., Fisher, W., & Mancuso, M. (2004, July). An explainable artificial intelligence system for small-unit tactical behavior. In Proceedings of the National Conference on Artificial Intelligence (pp. 900–907). AAAI Press; MIT Press; 1999.
15.
Zurück zum Zitat Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., & Yang, G. Z. (2019). XAI—Explainable artificial intelligence. Science Robotics, 4(37), eaay7120. Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., & Yang, G. Z. (2019). XAI—Explainable artificial intelligence. Science Robotics, 4(37), eaay7120.
16.
Zurück zum Zitat Barocas, S., Friedler, S., Hardt, M., Kroll, J., Venka-Tasubramanian, S., & Wallach, H. (2018). The FAT-ML workshop series on fairness, accountability, and transparency in machine learning. cit. on, 7. Barocas, S., Friedler, S., Hardt, M., Kroll, J., Venka-Tasubramanian, S., & Wallach, H. (2018). The FAT-ML workshop series on fairness, accountability, and transparency in machine learning. cit. on, 7.
17.
Zurück zum Zitat Afaq, A., Gaur, L., & Singh, G. (2023). Social CRM: Linking the dots of customer service and customer loyalty during COVID-19 in the hotel industry. International Journal of Contemporary Hospitality Management, 35(3), 992–1009.CrossRef Afaq, A., Gaur, L., & Singh, G. (2023). Social CRM: Linking the dots of customer service and customer loyalty during COVID-19 in the hotel industry. International Journal of Contemporary Hospitality Management, 35(3), 992–1009.CrossRef
18.
Zurück zum Zitat Wilburn, K. M., & Wilburn, H. R. (2018). The impact of technology on business and society. Global Journal of Business Research, 12(1), 23–39. Wilburn, K. M., & Wilburn, H. R. (2018). The impact of technology on business and society. Global Journal of Business Research, 12(1), 23–39.
20.
Zurück zum Zitat Chaudhary, M., Gangele, A., Naved, M., Gaur, L., & Singh, G. (2022, November). The function of driver categorisation in the ride-hailing industry: A study on on-demand transport. In 2022 3rd International Conference on Computation, Automation and Knowledge Management (ICCAKM) (pp. 1–6). IEEE. Chaudhary, M., Gangele, A., Naved, M., Gaur, L., & Singh, G. (2022, November). The function of driver categorisation in the ride-hailing industry: A study on on-demand transport. In 2022 3rd International Conference on Computation, Automation and Knowledge Management (ICCAKM) (pp. 1–6). IEEE.
22.
Zurück zum Zitat Anshu, K., Gaur, L., & Singh, G. (2022). Impact of customer experience on attitude and repurchase intention in online grocery retailing: A moderation mechanism of value Co-creation. Journal of Retailing and Consumer Services, 64, 102798.CrossRef Anshu, K., Gaur, L., & Singh, G. (2022). Impact of customer experience on attitude and repurchase intention in online grocery retailing: A moderation mechanism of value Co-creation. Journal of Retailing and Consumer Services, 64, 102798.CrossRef
23.
Zurück zum Zitat Afaq, A., & Gaur, L. (2021, November). The rise of robots to help combat covid-19. In 2021 International Conference on Technological Advancements and Innovations (ICTAI) (pp. 69–74). IEEE. Afaq, A., & Gaur, L. (2021, November). The rise of robots to help combat covid-19. In 2021 International Conference on Technological Advancements and Innovations (ICTAI) (pp. 69–74). IEEE.
24.
Zurück zum Zitat Khalid, O., Khan, S. U., & Zomaya, A. Y. (Eds.). (2019). Big data recommender systems: Algorithms, architectures, big data, security and trust (Vol. 1). Institution of Engineering and Technology. Khalid, O., Khan, S. U., & Zomaya, A. Y. (Eds.). (2019). Big data recommender systems: Algorithms, architectures, big data, security and trust (Vol. 1). Institution of Engineering and Technology.
25.
Zurück zum Zitat Sorbán, K. (2021). Ethical and legal implications of using AI-powered recommendation systems in streaming services. Információs Társadalom: Társadalomtudományi Folyóirat, 21(2), 63–82.CrossRef Sorbán, K. (2021). Ethical and legal implications of using AI-powered recommendation systems in streaming services. Információs Társadalom: Társadalomtudományi Folyóirat, 21(2), 63–82.CrossRef
26.
Zurück zum Zitat Sharma, S., Singh, G., Gaur, L., & Afaq, A. (2022). Exploring customer adoption of autonomous shopping systems. Telematics and Informatics, 73, 101861.CrossRef Sharma, S., Singh, G., Gaur, L., & Afaq, A. (2022). Exploring customer adoption of autonomous shopping systems. Telematics and Informatics, 73, 101861.CrossRef
27.
Zurück zum Zitat Lundberg, H., Mowla, N. I., Abedin, S. F., Thar, K., Mahmood, A., Gidlund, M., & Raza, S. (2022). Experimental analysis of trustworthy in-vehicle intrusion detection system using explainable artificial intelligence (XAI). IEEE Access, 10, 102831–102841.CrossRef Lundberg, H., Mowla, N. I., Abedin, S. F., Thar, K., Mahmood, A., Gidlund, M., & Raza, S. (2022). Experimental analysis of trustworthy in-vehicle intrusion detection system using explainable artificial intelligence (XAI). IEEE Access, 10, 102831–102841.CrossRef
28.
Zurück zum Zitat Cirqueira, D., Nedbal, D., Helfert, M., & Bezbradica, M. (2020). Scenario-based requirements elicitation for user-centric explainable AI: A case in fraud detection. In Machine Learning and Knowledge Extraction: 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25–28, 2020, Proceedings 4 (pp. 321–341). Springer International Publishing. Cirqueira, D., Nedbal, D., Helfert, M., & Bezbradica, M. (2020). Scenario-based requirements elicitation for user-centric explainable AI: A case in fraud detection. In Machine Learning and Knowledge Extraction: 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25–28, 2020, Proceedings 4 (pp. 321–341). Springer International Publishing.
29.
Zurück zum Zitat Yang, G., Ye, Q., & Xia, J. (2022). Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond. Information Fusion, 77, 29–52.CrossRef Yang, G., Ye, Q., & Xia, J. (2022). Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond. Information Fusion, 77, 29–52.CrossRef
30.
Zurück zum Zitat Cirqueira, D., Helfert, M., & Bezbradica, M. (2021, July). Towards design principles for user-centric explainable AI in fraud detection. In Artificial Intelligence in HCI: Second International Conference, AI-HCI 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings (pp. 21–40). Springer International Publishing. Cirqueira, D., Helfert, M., & Bezbradica, M. (2021, July). Towards design principles for user-centric explainable AI in fraud detection. In Artificial Intelligence in HCI: Second International Conference, AI-HCI 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings (pp. 21–40). Springer International Publishing.
31.
Zurück zum Zitat Liao, Q. V., & Varshney, K. R. (2021). Human-centered explainable ai (xai): From algorithms to user experiences. arXiv preprint arXiv:2110.10790. Liao, Q. V., & Varshney, K. R. (2021). Human-centered explainable ai (xai): From algorithms to user experiences. arXiv preprint arXiv:​2110.​10790.
32.
Zurück zum Zitat Rodrigues, V. F., Policarpo, L. M., da Silveira, D. E., da Rosa Righi, R., da Costa, C. A., Barbosa, J. L. V., Antunes, R. S., Scorsatto, R., & Arcot, T. (2022). Fraud detection and prevention in e-commerce: A systematic literature review. Electronic Commerce Research and Applications, 101207. Rodrigues, V. F., Policarpo, L. M., da Silveira, D. E., da Rosa Righi, R., da Costa, C. A., Barbosa, J. L. V., Antunes, R. S., Scorsatto, R., & Arcot, T. (2022). Fraud detection and prevention in e-commerce: A systematic literature review. Electronic Commerce Research and Applications, 101207.
33.
Zurück zum Zitat Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE access, 6, 52138–52160.CrossRef Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE access, 6, 52138–52160.CrossRef
35.
Zurück zum Zitat Loveleen Gaur, Mansi Ratta, Adesh Gaur (2022), Future of DeepFakes and Ectypes In: Deepfakes. CRC Press, 9781003231493 Loveleen Gaur, Mansi Ratta, Adesh Gaur (2022), Future of DeepFakes and Ectypes In: Deepfakes. CRC Press, 9781003231493
38.
Zurück zum Zitat Gaur, L., Jhanjhi, N. Z., Bakshi, S., & Gupta, P. (2022). Analyzing consequences of artificial intelligence on jobs using topic modeling and keyword extraction. In 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 435–440). https://doi.org/10.1109/ICIPTM54933.2022.9754064. Gaur, L., Jhanjhi, N. Z., Bakshi, S., & Gupta, P. (2022). Analyzing consequences of artificial intelligence on jobs using topic modeling and keyword extraction. In 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 435–440). https://​doi.​org/​10.​1109/​ICIPTM54933.​2022.​9754064.
39.
Zurück zum Zitat Gaur, L., Bhandari, M., Razdan, T., Mallik, S., & Zhao, Z. (2022). Explanation-driven deep learning model for prediction of brain tumour status using MRI image data. Frontiers in Genetics, 13, 822666.CrossRef Gaur, L., Bhandari, M., Razdan, T., Mallik, S., & Zhao, Z. (2022). Explanation-driven deep learning model for prediction of brain tumour status using MRI image data. Frontiers in Genetics, 13, 822666.CrossRef
40.
Zurück zum Zitat Ekhart, N. (2022). Taking down malicious webshops: Designing Explainable AI against growing e-commerce fraud. Ekhart, N. (2022). Taking down malicious webshops: Designing Explainable AI against growing e-commerce fraud.
41.
Zurück zum Zitat Yılmaz Benk, G., Badur, B., & Mardikyan, S. (2022). A new 360° framework to predict customer lifetime value for multi-category E-commerce companies using a multi-output deep neural network and explainable artificial intelligence. Information, 13(8), 373.CrossRef Yılmaz Benk, G., Badur, B., & Mardikyan, S. (2022). A new 360° framework to predict customer lifetime value for multi-category E-commerce companies using a multi-output deep neural network and explainable artificial intelligence. Information, 13(8), 373.CrossRef
42.
Zurück zum Zitat Chaudhary, M., Gaur, L., & Chakrabarti, A. (2022, November). Detecting the employee satisfaction in retail: A Latent Dirichlet Allocation and Machine Learning approach. In 2022 3rd International Conference on Computation, Automation and Knowledge Management (ICCAKM) (pp. 1–6). IEEE. Chaudhary, M., Gaur, L., & Chakrabarti, A. (2022, November). Detecting the employee satisfaction in retail: A Latent Dirichlet Allocation and Machine Learning approach. In 2022 3rd International Conference on Computation, Automation and Knowledge Management (ICCAKM) (pp. 1–6). IEEE.
43.
Zurück zum Zitat Matuszelański, K., & Kopczewska, K. (2022). Customer churn in retail E-commerce business: Spatial and machine learning approach. Journal of Theoretical and Applied Electronic Commerce Research, 17(1), 165–198.CrossRef Matuszelański, K., & Kopczewska, K. (2022). Customer churn in retail E-commerce business: Spatial and machine learning approach. Journal of Theoretical and Applied Electronic Commerce Research, 17(1), 165–198.CrossRef
44.
Zurück zum Zitat Waltl, B., & Vogl, R. (2018). Increasing transparency in algorithmic-decision-making with explainable AI. Datenschutz und Datensicherheit-DuD, 42(10), 613–617.CrossRef Waltl, B., & Vogl, R. (2018). Increasing transparency in algorithmic-decision-making with explainable AI. Datenschutz und Datensicherheit-DuD, 42(10), 613–617.CrossRef
45.
Zurück zum Zitat Hulsen, T. (2023). Explainable Artificial Intelligence (XAI) in Healthcare. Hulsen, T. (2023). Explainable Artificial Intelligence (XAI) in Healthcare.
46.
Zurück zum Zitat Ferreira, J. J., & Monteiro, M. S. (2020). What are people doing about XAI user experience? A survey on AI explainability research and practice. In Design, User Experience, and Usability. Design for Contemporary Interactive Environments: 9th International Conference, DUXU 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part II 22 (pp. 56–73). Springer International Publishing. Ferreira, J. J., & Monteiro, M. S. (2020). What are people doing about XAI user experience? A survey on AI explainability research and practice. In Design, User Experience, and Usability. Design for Contemporary Interactive Environments: 9th International Conference, DUXU 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part II 22 (pp. 56–73). Springer International Publishing.
47.
Zurück zum Zitat Islam, A. S., Ahmed, S., & Khan, R. H. (2022, March). A review on e-commerce system in bangladesh: An empirical study. In Proceedings of the 2nd International Conference on Computing Advancements (pp. 269–276). Islam, A. S., Ahmed, S., & Khan, R. H. (2022, March). A review on e-commerce system in bangladesh: An empirical study. In Proceedings of the 2nd International Conference on Computing Advancements (pp. 269–276).
48.
Zurück zum Zitat Bradley, C., Wu, D., Tang, H., Singh, I., Wydant, K., Capps, B., Wong, K., Agostinelli, F., Irvi, M., Srivastava, B., & Srivastava, B. (2022, November). Explainable artificial intelligence (XAI) user interface design for solving a Rubik’s Cube. In HCI International 2022–Late Breaking Posters: 24th International Conference on Human-Computer Interaction, HCII 2022, Virtual Event, June 26–July 1, 2022, Proceedings, Part II (pp. 605–612). Springer Nature Switzerland. Bradley, C., Wu, D., Tang, H., Singh, I., Wydant, K., Capps, B., Wong, K., Agostinelli, F., Irvi, M., Srivastava, B., & Srivastava, B. (2022, November). Explainable artificial intelligence (XAI) user interface design for solving a Rubik’s Cube. In HCI International 2022–Late Breaking Posters: 24th International Conference on Human-Computer Interaction, HCII 2022, Virtual Event, June 26–July 1, 2022, Proceedings, Part II (pp. 605–612). Springer Nature Switzerland.
49.
Zurück zum Zitat Antoniadi, A. M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B. A., & Mooney, C. (2021). Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: A systematic review. Applied Sciences, 11(11), 5088.CrossRef Antoniadi, A. M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B. A., & Mooney, C. (2021). Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: A systematic review. Applied Sciences, 11(11), 5088.CrossRef
50.
Zurück zum Zitat Ravi, M., Negi, A., & Chitnis, S. (2022, April). A comparative review of expert systems, recommender systems, and explainable AI. In 2022 IEEE 7th International conference for Convergence in Technology (I2CT) (pp. 1–8). IEEE. Ravi, M., Negi, A., & Chitnis, S. (2022, April). A comparative review of expert systems, recommender systems, and explainable AI. In 2022 IEEE 7th International conference for Convergence in Technology (I2CT) (pp. 1–8). IEEE.
51.
Zurück zum Zitat Ahmed, I., Jeon, G., & Piccialli, F. (2022). From artificial intelligence to explainable artificial intelligence in industry 4.0: A survey on what, how, and where. IEEE Transactions on Industrial Informatics, 18(8), 5031–5042.CrossRef Ahmed, I., Jeon, G., & Piccialli, F. (2022). From artificial intelligence to explainable artificial intelligence in industry 4.0: A survey on what, how, and where. IEEE Transactions on Industrial Informatics, 18(8), 5031–5042.CrossRef
52.
Zurück zum Zitat Gaur, L., Afaq, A., Singh, G., & Dwivedi, Y. K. (2021). Role of artificial intelligence and robotics to foster the touchless travel during a pandemic: A review and research agenda. International Journal of Contemporary Hospitality Management, 33(11), 4079–4098.CrossRef Gaur, L., Afaq, A., Singh, G., & Dwivedi, Y. K. (2021). Role of artificial intelligence and robotics to foster the touchless travel during a pandemic: A review and research agenda. International Journal of Contemporary Hospitality Management, 33(11), 4079–4098.CrossRef
53.
Zurück zum Zitat Wolofsky, S. (2020). What’s Your Privacy Worth on the Global Tech Market? Weighing the Cost of Protecting Consumer Data against the Risk That New Legislation May Stifle Competition and Innovation during this global, technological revolution. Fordham Int’l LJ, 44, 1149. Wolofsky, S. (2020). What’s Your Privacy Worth on the Global Tech Market? Weighing the Cost of Protecting Consumer Data against the Risk That New Legislation May Stifle Competition and Innovation during this global, technological revolution. Fordham Int’l LJ, 44, 1149.
54.
Zurück zum Zitat Brendel, A. B., Mirbabaie, M., Lembcke, T. B., & Hofeditz, L. (2021). Ethical management of artificial intelligence. Sustainability, 13(4), 1974.CrossRef Brendel, A. B., Mirbabaie, M., Lembcke, T. B., & Hofeditz, L. (2021). Ethical management of artificial intelligence. Sustainability, 13(4), 1974.CrossRef
55.
Zurück zum Zitat Suresh, A., & Rani, N. J. (2020). Consumer perception towards artificial intelligence in E-commerce with reference to Chennai city, India. Journal of Information Technology and Economic Development, 11(1), 1–14. Suresh, A., & Rani, N. J. (2020). Consumer perception towards artificial intelligence in E-commerce with reference to Chennai city, India. Journal of Information Technology and Economic Development, 11(1), 1–14.
Metadaten
Titel
Introduction to Explainable AI (XAI) in E-Commerce
verfasst von
Meenu Chaudhary
Loveleen Gaur
Gurinder Singh
Anam Afaq
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-55615-9_1

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