A sociotechnical history of an AI video chatbot: Mapping AI chatbot innovation trajectory for information policy design

Authors

  • Catherine McGowan Rutgers University

DOI:

https://doi.org/10.21900/j.alise.2024.1734

Keywords:

AI Chatbot, digital resurrection, patent citation network, AI afterlife, innovation trajectory

Abstract

This study traces the patent citation network of U.S. Patent 11,107,465 Natural Conversation Storytelling System (Gustman et al, 2021) to map the innovation trajectory of AI Chatbots. This patented AI video chatbot enables the reanimation or digital resurrection of humans in video form. As GLAMs continue to experiment with new technologies such as historical figure chatbots to increase engagement through gamification and empathy, a critical examination of technologies that are designed to appear human-like is warranted as they often skirt credibility, accuracy, and likely insert bias. Furthermore, the rise of generative AI tools and the propensity for producing hallucinations (Christensen et al, 2024) increases ethical issues for the implications on humans and truth (Ranalli, 2022; Stahl and Eke, 2024).

Patent citation network analysis is frequently conducted as a competitive strategy for mapping the trajectory of technological development and patented inventions (Érdi et al, 2013; Jain et al, 2020). Drawing from this method, innovation trajectory routes or pathways will be traced through the patent citations to identify the most prominent or critical patents in the AI video chatbot innovation trajectory and analyze which features of technical innovation are retained across its pathway. These methods are frequently utilized to understand changes, patterns, and development in innovation to predict economically viable futures and can be utilized to predict the needs for information policy (Frohmann, 1995) by understanding the implications asymmetrical power on society.

References

Christensen, J., Hansen, J. M., & Wilson, P. (2024). Understanding the role and impact of generative artificial intelligence (ai) hallucination within consumers’ tourism decision-making processes. Current Issues in Tourism, 1–16. https://doi.org/10.1080/13683500.2023.2300032

Érdi, P., Makovi, K., Somogyvári, Z., Strandburg, K., Tobochnik, J., Volf, P., & Zalányi, L. (2013). Prediction of emerging technologies based on analysis of the US patent citation network. Scientometrics, 95(1), 225–242. https://doi.org/10.1007/s11192-012-0796-4

Frohmann, B. (1995). Taking information policy beyond information science: applying the actor network theory. Connectedness: Information, Systems, People, Organizations.

Gaia, G., Boiano, S., Borda, A. (2019). Engaging museum visitors with ai: The case of chatbots. In: Giannini, T., Bowen, J. (eds) Museums and digital culture. Springer Series on Cultural Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-97457-6_1

Gustman, S., Smith, S., Maio-Smith, H., Campbell, J., Jones, A. (2021). Natural conversation storytelling system (U.S. Patent No. 11,107,465). U.S. Patent and Trademark Office.

Jain, R., Tripathi, M., Agarwal, V., & Murthy, J. (2020). Patent data analytics for technology benchmarking: R-based implementation. World Patent Information, 60, 101952. https://doi.org/10.1016/j.wpi.2020.101952

Ranalli, R. (2022, June 13). Is there a human right to truth?. Harvard Kennedy School. https://www.hks.harvard.edu/faculty-research/policy-topics/human-rights/there-human-right-truth

Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT – Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700.https://doi.org/10.1016/j.ijinfomgt.2023.102700

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Published

2024-10-16

Issue

Section

Works in Progress Posters