In a Quasi-Social Relationship With ChatGPT. An Autoethnography on Engaging With Prompt-Engineered LLM Personas

As conversational AI like ChatGPT becomes more sophisticated, understanding emerging quasi-social relationships with it is crucial. Through analytical autoethnography, we explore the nuances of these relationships with two autobiographically designed ChatGPT personas to augment the social needs of the first author: the Endless Enthusiast (always responding positively and encouragingly) and the Socratic Tutor (asking questions to stimulate critical thinking). After six weeks of interaction, we find that for a successful relationship, the non-human counterpart must be authentic about its machine nature and limitations. Using deception to appear more human-like makes the relationship fail. We thus suggest designing machine relationships as complementary to human-human relationships. For authentic interactions, humans should be in control, with the machine authentically assuming a role that "naturally" fits machines. Here, the unique qualities of machines in social interactions offer promising starting points for designing such roles.

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Publication Details

Journal
Nordic Conference on Human-Computer Interaction
Published
2024-09-30
DOI
https://doi.org/10.1145/3679318.3685501
Citations
4
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.60
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article

In a Quasi-Social Relationship With ChatGPT. An Autoethnography on Engaging With Prompt-Engineered LLM Personas

Marc Hassenzahl, Robin Neuhaus, Matthias Laschke, Eva Krapp
4 citations
Nordic Conference on Human-Computer Interaction
AI in Service Interactions
0.60
article

In a Quasi-Social Relationship With ChatGPT. An Autoethnography on Engaging With Prompt-Engineered LLM Personas

Marc Hassenzahl, Robin Neuhaus, Matthias Laschke, Eva Krapp
article en
4 citations

Abstract

As conversational AI like ChatGPT becomes more sophisticated, understanding emerging quasi-social relationships with it is crucial. Through analytical autoethnography, we explore the nuances of these relationships with two autobiographically designed ChatGPT personas to augment the social needs of the first author: the Endless Enthusiast (always responding positively and encouragingly) and the Socratic Tutor (asking questions to stimulate critical thinking). After six weeks of interaction, we find that for a successful relationship, the non-human counterpart must be authentic about its machine nature and limitations. Using deception to appear more human-like makes the relationship fail. We thus suggest designing machine relationships as complementary to human-human relationships. For authentic interactions, humans should be in control, with the machine authentically assuming a role that "naturally" fits machines. Here, the unique qualities of machines in social interactions offer promising starting points for designing such roles.

Nordic Conference on Human-Computer Interaction
University of Siegen (DE)
Reduced inequalities
Openalex Percentile: Top 35%
AI in Service Interactions
0.60
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