Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research
A. Tolzin, and A. Janson. Hawaii International Conference on System Sciences (HICSS), Maui, Hawaii, USA, (2023)
Abstract
Human-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future.
%0 Conference Paper
%1 ls_leimeister
%A Tolzin, Antonia
%A Janson, Andreas
%B Hawaii International Conference on System Sciences (HICSS)
%C Maui, Hawaii, USA
%D 2023
%K common_ground conversational_agent human-agent_interaction itegpub pub_aja pub_ato systematic_review u3bpub
%T Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research
%U https://pubs.wi-kassel.de/wp-content/uploads/2022/10/JML_890.pdf
%X Human-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future.
@inproceedings{ls_leimeister,
abstract = {Human-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future.},
added-at = {2022-10-06T16:54:14.000+0200},
address = {Maui, Hawaii, USA},
author = {Tolzin, Antonia and Janson, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/2b980ee1cc08c2048950296804ebde4db/ls_leimeister},
booktitle = {Hawaii International Conference on System Sciences (HICSS)},
eventdate = {3-6 Jan 2023},
eventtitle = {Hawaii International Conference on System Sciences (HICSS)},
interhash = {52f6fa2c5255030f5dad96d60dd07a8f},
intrahash = {b980ee1cc08c2048950296804ebde4db},
keywords = {common_ground conversational_agent human-agent_interaction itegpub pub_aja pub_ato systematic_review u3bpub},
timestamp = {2022-10-10T17:00:04.000+0200},
title = {Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research},
url = {https://pubs.wi-kassel.de/wp-content/uploads/2022/10/JML_890.pdf},
venue = {Maui, Hawaii, USA},
year = 2023
}