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2024 | OriginalPaper | Buchkapitel

Chatbot-XAI—The New Age Artificial Intelligence Communication Tool for E-Commerce

verfasst von : Kavita Thapliyal, Manjul Thapliyal

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

Verlag: Springer Nature Switzerland

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Abstract

XAI chatbots in e-commerce refer to chatbots that are customized to use natural language processing (NLP) and machine learning (ML) algorithms to recognise and comprehend customer queries and deliver personalized and tailored recommendations and assistance to customers during online shopping. The primary benefit of XAI chatbots in ecommerce is that they can support and clarify their decision-making process and procedures to customers more clearly and helps in building trust and transparency, by decreasing the possibility for errors or biases. Today XAI chatbot can explain why it recommends and proposes a particular product to his customer based on the prior preferences, previous purchases, and browsing history. This chapter aims to provide an overview of how XAI chatbots can be used as a tool in ecommerce to improve customer experience and increase sales. Overall, XAI chatbots have the potential to revolutionize the ecommerce industry however, they must be designed and implemented carefully to ensure they are ethical, secure, and compliant with privacy regulations. The chapter will in detail delve into the technical aspects of XAI chatbots, including the machine learning algorithms and natural language processing techniques used to build them. With the help of detailed pictorial representation, it will exhibit the importance of transparency and interpretability in XAI chatbots with various techniques and approaches of explaining the chatbot's decision-making process to customers. Overall, this chapter will provide a comprehensive overview of XAI chatbots as a tool in ecommerce and their potential impact on the industry.

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Literatur
1.
Zurück zum Zitat Charmet, H. C. T. F. (2022). Explainable artificial intelligence for cybersecurity: A literature survey. Springer. Charmet, H. C. T. F. (2022). Explainable artificial intelligence for cybersecurity: A literature survey. Springer.
3.
Zurück zum Zitat Saeed, C. O. W. (2023). Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities. Elsevier. Saeed, C. O. W. (2023). Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities. Elsevier.
4.
Zurück zum Zitat Menon, S. G. S. (2021, Dec 20). XAI is critical to ensure transparency. Analyticsindiamag.com. Menon, S. G. S. (2021, Dec 20). XAI is critical to ensure transparency. Analyticsindiamag.com.
5.
Zurück zum Zitat Rajabi, K. E. E. (2022). Knowledge-graph-based explainable AI: A systematic review. Sage. Rajabi, K. E. E. (2022). Knowledge-graph-based explainable AI: A systematic review. Sage.
6.
Zurück zum Zitat AKM, P. M. (2023). Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research. Elsevier. AKM, P. M. (2023). Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research. Elsevier.
7.
Zurück zum Zitat Laato, M. T. A. N. I. M. M. S. (2022). How to explain AI systems to end users: A systematic literature review and research agenda. Emerald. Laato, M. T. A. N. I. M. M. S. (2022). How to explain AI systems to end users: A systematic literature review and research agenda. Emerald.
9.
Zurück zum Zitat Bishop, C. (2023, April 20). Chatbots vs. conversational AI: What’s the difference?. Zendesk Blog. Bishop, C. (2023, April 20). Chatbots vs. conversational AI: What’s the difference?. Zendesk Blog.
10.
Zurück zum Zitat Venkataraman, V. A review of Explainable AI (XAI) concepts, techniques, and challenges. Deloitte. Venkataraman, V. A review of Explainable AI (XAI) concepts, techniques, and challenges. Deloitte.
11.
Zurück zum Zitat IBM. What is logistic regression. IBM. IBM. What is logistic regression. IBM.
13.
Zurück zum Zitat Guleria, M. S. P. (2022). Explainable AI and machine learning: Performance evaluation and explainability of classifiers on educational data mining inspired career counselling. Springer. Guleria, M. S. P. (2022). Explainable AI and machine learning: Performance evaluation and explainability of classifiers on educational data mining inspired career counselling. Springer.
14.
Zurück zum Zitat Hulstaert, L. (2019). Black-box vs. white-box models. Towards Data Science. Hulstaert, L. (2019). Black-box vs. white-box models. Towards Data Science.
17.
Zurück zum Zitat de Bruijn, M. W. M. J. H. (2022). The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making. Elsevier. de Bruijn, M. W. M. J. H. (2022). The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making. Elsevier.
18.
Zurück zum Zitat Tulchinsky, A. Why Explainable AI (XAI) is the future of marketing and e-commerce. The Future of Commerce. Tulchinsky, A. Why Explainable AI (XAI) is the future of marketing and e-commerce. The Future of Commerce.
19.
Zurück zum Zitat Gartner. Digital Commerce—Top Challenges, Trends and Proven Next Steps Strategy. [Online]. Gartner. Digital Commerce—Top Challenges, Trends and Proven Next Steps Strategy. [Online].
20.
Zurück zum Zitat UNEXT. (2023 March 14). Artificial Intelligence and Machine Learning for E-Commerce. U Next. UNEXT. (2023 March 14). Artificial Intelligence and Machine Learning for E-Commerce. U Next.
24.
Zurück zum Zitat Meske, E. B. C. Explainable artificial intelligence: Objectives, stakeholders, and future research opportunities. Taylor and Francis. Meske, E. B. C. Explainable artificial intelligence: Objectives, stakeholders, and future research opportunities. Taylor and Francis.
25.
Zurück zum Zitat Sonawane, N. (2022, June 5). Challenges of Explainable AI (XAI) and how to overcome them. Enterprise Talk. Sonawane, N. (2022, June 5). Challenges of Explainable AI (XAI) and how to overcome them. Enterprise Talk.
28.
Zurück zum Zitat Kale, T. N. A. (2023). Provenance documentation to enable explainable and trustworthy AI: A literature review. MIT Press Direct. Kale, T. N. A. (2023). Provenance documentation to enable explainable and trustworthy AI: A literature review. MIT Press Direct.
29.
Zurück zum Zitat Fly, A. (2020). Is explainable AI (xAI) the next step, or just hype. Towards Data Science. Fly, A. (2020). Is explainable AI (xAI) the next step, or just hype. Towards Data Science.
30.
Zurück zum Zitat Mobyen. (2022). Theoretical background of explainable artificial intelligence. Scholarly Community Encyclopedia. Mobyen. (2022). Theoretical background of explainable artificial intelligence. Scholarly Community Encyclopedia.
32.
Zurück zum Zitat E. A. S. R. J. N. I. A. P. M. A. Plamen P. Angelov. (2021). Explainable artificial intelligence: An analytical review. Wires. E. A. S. R. J. N. I. A. P. M. A. Plamen P. Angelov. (2021). Explainable artificial intelligence: An analytical review. Wires.
Metadaten
Titel
Chatbot-XAI—The New Age Artificial Intelligence Communication Tool for E-Commerce
verfasst von
Kavita Thapliyal
Manjul Thapliyal
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-55615-9_6

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