What HMC Teaches Us About Authenticity

Author:

Etzrodt Katrin1ORCID,Kim Jihyun2ORCID,van der Goot Margot3ORCID,Prahl Andrew4ORCID,Choi Mina5ORCID,Craig Matthew6ORCID,Marco Dehnert Marco7ORCID,Engesser Sven1ORCID,Frehmann Katharina8ORCID,Grande Luis9ORCID,Leo-Liu Jindong10ORCID,Liu Diyi11ORCID,Mooshammer Sandra1ORCID,Rambukkana Nathan12ORCID,Rogge Ayanda1ORCID,Sikströma Pieta13ORCID,Son Rachel14ORCID,Wilkenfeld Nan15ORCID,Xu Kun14ORCID,Zhang Renwen16ORCID,Zhu Ying6ORCID,Edwards Chad17ORCID

Affiliation:

1. TUD Dresden University of Technology

2. University of Central Florida

3. University of Amsterdam

4. Nanyang Technological University

5. Sejong University

6. Kent State University

7. University of Arkansas

8. University of Düsseldorf

9. Drexel University

10. The Chinese University of Hong Kong

11. University of Oxford

12. Wilfrid Laurier University

13. University of Jyväskylä

14. University of Florida

15. UC Santa Barbara

16. National University of Singapore

17. Western Michigan University

Abstract

This paper delves into what the application of authenticity to Human-Machine Communication (HMC) can teach us about authenticity and us as HMC researchers and as a com- munity. Inspired by the 2023 pre-conference “HMC: Authenticity in communicating with machines,” two central questions guide the discussion: How does HMC contribute to our understanding of authentic communication with machines? And how can the concept of authenticity contribute to our sense of self as researchers within the HMC field? Through the collaborative effort of 22 authors, the paper explores the re-conceptualization of authenticity and presents recent areas of tension that guide the HMC research and community. With this paper we aim at offering a gateway for scholars to connect and engage with the evolving HMC field.

Publisher

Communication and Social Robotics Labs

Reference257 articles.

1. Banks, J., & Koban, K. (2022). A kind apart: The limited application of human race and sex

2. stereotypes to a humanoid social robot. International Journal of Social Robotics. https://

3. doi.org/10.1007/s12369-022-00900-2

4. Baxter, P., Kennedy, J., Senft, E., Lemaignan, S., & Belpaeme, T. (2016). From characterising

5. three years of HRI to methodology and reporting recommendations. 2016 11th ACM/

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