0 Contact Us

Exploring Advantages and Challenges of Chatbot Integration in Human-Robot Interaction

Bobby Lukose*, Jayanthiladevi**

*-** Department of Computer Science & Data Science, Srinivas University, Karnataka, India.

Periodicity:October - December'2023
DOI : https://doi.org/10.26634/jse.18.2.20376

Abstract

The integration of chatbot technology into human-robot interaction has emerged as a transformative approach to foster seamless communication and elevate user experiences. This paper explores the convergence of chatbots with robotics, elucidating the benefits and challenges encountered in this integration. By enabling natural language processing capabilities, chatbots facilitate more intuitive and interactive communication between users and robots. This paper examines the advantages of this integration, such as 24/7 availability, scalability, and improved efficiency, while highlighting challenges such as contextual understanding limitations, language dependencies, and ethical concerns regarding data privacy. Moreover, it delves into the implications of leveraging chatbots in diverse applications, including customer service, healthcare, and education. By comprehensively analyzing the landscape of chatbot integration in human-robot interaction, this paper aims to provide insights into maximizing the advantages while mitigating the challenges, thereby paving the way for more effective and engaging interactions between humans and robots.

Keywords

Chatbot Integration, Human-Robot Interaction, Robotics, User Experience, Natural Language Processing.

How to Cite this Article?

Lukose, B., and Jayanthiladevi. (2023). Exploring Advantages and Challenges of Chatbot Integration in Human-Robot Interaction. i-manager’s Journal on Software Engineering, 18(2), 10-15. https://doi.org/10.26634/jse.18.2.20376

References

[1]. Bavaresco, R., Silveira, D., Reis, E., Barbosa, J., Righi, R., Costa, C., ... & Moreira, C. (2020). Conversational agents in business: A systematic literature review and future research directions. Computer Science Review, 36, 100239.

[2]. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, (pp. 610-623).

[3]. Daniel, G., Cabot, J., Deruelle, L., & Derras, M. (2020). Xatkit: A multimodal low-code chatbot development framework. IEEE Access, 8, 15332-15346.

[4]. Følstad, A., & Brandtzaeg, P. B. (2020). Users' experiences with chatbots: Findings from a questionnaire study. Quality and User Experience, 5(1), 3.

[5]. Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304-316.

[6]. Gorwa, R., & Guilbeault, D. (2020). Unpacking the social media bot: A typology to guide research and policy. Policy & Internet, 12(2), 225-248.

[7]. Hobert, S., & Berens, F. (2020). Small talk conversations and the long-term use of chatbots in educational settings–experiences from a field study. In Chatbot Research and Design: Third International Workshop, CONVERSATIONS 2019, Amsterdam, The (pp. 260-272). Springer International Publishing.

[8]. Hsieh, T. Y., Chaudhury, B., & Cross, E. S. (2020, March). Human-robot cooperation in prisoner dilemma games: people behave more reciprocally than prosocially toward robots. In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 257-259).

[9]. Jain, M., Kumar, P., Kota, R., & Patel, S. N. (2018, June). Evaluating and informing the design of chatbots. In Proceedings of the 2018 Designing Interactive Systems Conference, (pp. 895-906).

[10]. Kim, S., Lee, J., & Gweon, G. (2019, May). Comparing data from chatbot and web surveys: Effects of platform and conversational style on survey response quality. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, (pp. 1-12).

[11]. Kretzschmar, K., Tyroll, H., Pavarini, G., Manzini, A., Singh, I., & NeurOx Young People's Advisory Group. (2019). Can your phone be your therapist? Young people's ethical perspectives on the use of fully automated conversational agents (chatbots) in mental health support. Biomedical Informatics Insights, 11, 1178222619829083.

[12]. Laban, G., & Araujo, T. (2019, November). Working together with conversational agents: the relationship of perceived cooperation with service performance evaluations. In International Workshop on Chatbot Research and Design (pp. 215-228). Cham: Springer International Publishing.

[13]. Laban, G., & Araujo, T. (2020, October). The effect of personalization techniques in users' perceptions of conversational recommender systems. In Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents, (pp. 1-3).

[14]. Liao, Q. V., Geyer, W., Muller, M., & Khazaen, Y. (2020). Conversational interfaces for information search. Understanding and Improving Information Search: A Cognitive Approach, 267-287.

[15]. Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. E., ... & Staab, S. (2020). Bias in data driven artificial intelligence systems: An introductory survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3), e1356.

[16]. Paikens, P., Znotins, Barzdins, G. (2020). Human-inthe-loop conversation agent for customer service. In Natural Language Processing and Information Systems: 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, Saarbrücken, Germany, (pp. 277-284). Springer International Publishing.

[17]. Pérez, J. Q., Daradoumis, T., & Puig, J. M. M. (2020). Rediscovering the use of chatbots in education: A systematic literature review. Computer Applications in Engineering Education, 28(6), 1549-1565.

[18]. Perski, O., Crane, D., Beard, E., & Brown, J. (2019). Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study. Digital Health, 5, 20552076198806 76.

[19]. Ruane, E., Birhane, A., & Ventresque, A. (2019, December). Conversational AI: Social and Ethical Considerations. In AICS, 2563, 104-115.

[20]. Wolff, R.M., Hobert, S., Masuch, K., & Schumann, M. (2020). Chatbots at digital workplaces–a groundedtheory approach for surveying application areas and objectives. Pacific Asia Journal of the Association for Information Systems, 12(2), 3.

If you have access to this article please login to view the article or kindly login to purchase the article

Username/Email

Password

Forgot password?

Remember me

Don't have an account? Sign Up

Purchase Instant Access

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.

Alert

Full Article Now Not Available

Submit New Paper Track Paper Status Buy Journal Track Your Subscription Journal Archive

Authors Institutions/Librarians Agents Conferences

About Us Contact FAQ Terms and Conditions Privacy Policy Refund & cancellation Policy