Chatbot Revolution: Exploring Emerging Trends and Future Directions in Conversational Artificial Intelligence
Keywords:
Artificial intelligence (AI), Chatbot, ChatGPT, Natural Language Processing.Abstract
The rise of chatbots has greatly simplified various aspects of human life by offering automated responses to user queries, reducing the reliance on human involvement. Utilizing natural language processing, these chatbots have become transformative tools across a range of sectors, including customer service, education, and e-commerce. This paper examines the evolution of conversational Artificial intelligence (AI), particularly focusing on chatbots, from the introduction of ELIZA in 1966 to the modern advancements exemplified by ChatGPT, highlighting a trajectory of notable technological progress and application diversification. However, the paper also acknowledges ongoing challenges. Limitations in context understanding and memory, present since the early days, can still lead to repetitive or nonsensical responses. While modern chatbots have made significant progress, they continue to grapple with the complexities of human language and emotions, potentially leading to misunderstandings. Additionally, ethical considerations around privacy, security, and responsible AI use are paramount as AI integration deepens. Through this historical lens, both similarities and differences in chatbots' development, capabilities, and applications are revealed over time. Ultimately, the progression from ELIZA to ChatGPT underscores significant strides in chatbot technology, transitioning from rudimentary pattern matching to sophisticated, context-aware interactions driven by advanced AI.
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Ina. (2023, July 26). The History Of Chatbots – From ELIZA to ChatGPT. AI-chatbot Software for Complex Requirements. https://onlim.com/en/the-history-of-chatbots/
Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45.
Raj, S. (2019). Building Chatbots with Python. Packt Publishing Ltd.
Arkin, J., Walter, M. R., Boteanu, A., Napoli, M. E., Biggie, H., Kress-Gazit, H., & Howard, T. (2017). Contextual awareness: Understanding monologic natural language instructions for autonomous robots. 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). https://doi.org/10.1109/ROMAN.2017.8172349
Nartey, F., Amavi, F. A., & Nyameamah, I. (2019). An Approach for Building Natural Language Database using Pattern Matching Technique. International Journal of Computer Applications, 975, 8887. https://doi.org/10.5120/ijca2019919720
Aakur, S. N., & Sarkar, S. (2023). Leveraging Symbolic Knowledge Bases for Commonsense Natural Language Inference Using Pattern Theory. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/TPAMI.2023.3287837
Wallace, R. S. (2003). The Elements of AIML Style. ALICE AI Foundation.
Prasetya, S. A., Erwin, A., & Galinium, M. (2018). Implementing Indonesian Language Chatbot for Ecommerce Site Using Artificial Intelligence Markup Language (AIML). Journal of Technology and Systems, https://dx.doi.org/10.25105/pakar.v0i0.2652
Nursetyo, A., Setiadi, D., & Subhiyakto, E. R. (2018). Smart Chatbot System for E-Commerce Assistance based on AIML. 2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), https://dx.doi.org/10.1109/ISRITI.2018.8864349
Omari, R. M., & Mohammadian, M. (2016). Rule-based fuzzy cognitive maps and natural language processing in machine ethics. Journal of Information, Communication and Ethics in Society. https://dx.doi.org/10.1108/JICES-10-2015-0034
Omari, R. M., & Mohammadian, M. (2016). Rule-based fuzzy cognitive maps and natural language processing in machine ethics. Journal of Information, Communication and Ethics in Society. https://dx.doi.org/10.1108/JICES-10-2015-0034
Saoudi, Y., & Gammoudi, M. Trends and challenges of Arabic Chatbots: Literature review. Journal of Computer and Communications, https://dx.doi.org/10.5455/jjcit.71-1685381801
Chan, C., & Li, F. (2023). Developing a natural language-based AI-chatbot for social work training: an illustrative case study. Journal of Technology in Human Services. https://dx.doi.org/10.1080/17525098.2023.2176901
Alekseev, D. S., Shagalova, P., & Sokolova, E. Development of a Chatbot Using Machine Learning Algorithms to Automate Educational Processes.
Nischal, C. N., Sachin, T., Vivek, B., & Taranath, K. G. (2020). Developing a Chatbot Using Machine Learning.
Hamzah, W. M. A. F. W., Yusof, M. K., Ismail, I., Makhtar, M., Nawang, H., & Aziz, A. (2022). Multiclass Intent Classification for Chatbot Based on Machine Learning Algorithm.
Christian Chukwuemeke, E., Nicholas, O., Tochukwu, Ebu Jacob Sunday, Otuole Uchechukwu Emmanuel, Ekwunife Onyeka, Enofe Prince, & Ohiocheoya Regbenien. (2023). Design And Implementation of a Departmental Enquiry Chatbot Based On Natural Language Processing (NLP) .https://www.irjmets.com/uploadedfiles/paper//issue_10_october_2023/45387/final/fin_irjmets1698379965.pdf
Gupta, V., Joshi, V., Jain, A., & Garg, I. (2023). Chatbot for Mental health support using NLP. https://dx.doi.org/10.1109/INCET57972.2023.10170573
Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning With Applications, 2, 100006. https://doi.org/10.1016/j.mlwa.2020.100006
Colby, K.M., 1981. Modeling a Paranoid Mind. Behavioral and Brain Sciences, 4 (04), pp. 515-534.
Dr.Sbaitso or: How I Learned to Stop Worrying and Love the ChatGPT | by Rasim Avci | Medium. (n.d.). Retrieved June 10, 2024, from https://medium.com/@rasim.avci/how-i-stopped-worrying-and-learned-to-love-the-chatgpt-d389932153ba
Thiebes, S. (2020, March 2). A Brief History of Chatbots. Interaction Design Foundation [IDF]. Retrieved from https://www.interaction-design.org/literature/topics/chatbots
Labadze, L., Grigolia, M. & Machaidze, L. Role of AI chatbots in education: systematic literature review. Int J Educ Technol High Educ 20, 56 (2023). https://doi.org/10.1186/s41239-023-00426-1
Liu, Y., Zheng, H., Liu, Z., & Li, S. (2016, December). A Survey of Chatbot Technology and Applications. Journal of Artificial Intelligence Research
Ollestad, M. (2017, February 14). A Brief History of Virtual Assistants. Lifewire. https://www.lifewire.com/virtual-assistants-4138533
Huang, X., Li, Y., Piao, Y., Jiang, L., Hou, L., He, J., ... & Peng, J. (2018, July 16). Conversational Question Answering with Deep Learning. arXiv preprint arXiv:1807.06422. https://arxiv.org/abs/1807.06422
Purewal, S. J. (2016, October 4). The difference between Google Now and Google Assistant. CNET. https://www.cnet.com/tech/mobile/the-difference-between-google-now-and-google-assistant/#google_vignette
Bellotti, F., Peruzzini, S., Válaszka, A., & Raubal, M. (2017). Envisioning Conversational AI for the Future Workplace. ACM Transactions on Computer-Human Interaction (TOCHI), 24(4), 1-41. Retrieved from https://dl.acm.org/doi/10.1145/3133233
OpenAI. (2023). ChatGPT. Retrieved from https://chat.openai.com/chat
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