TY - GEN
T1 - Design foundations for AI assisted decision-making
T2 - 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
AU - de Vreede, Triparna
AU - Raghavan, Mukhunth
AU - de Vreede, Gert Jan
N1 - Publisher Copyright:
© 2021 IEEE Computer Society. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Progress of technology and processing power has enabled the advent of sophisticated technology including Artificial Intelligence (AI) agents. AI agents have penetrated society in many forms including conversation agents or chatbots. As these chatbots have a social component to them, is it critical to evaluate the social aspects of their design and its impact on user outcomes. This study employs Social Determination Theory to examine the effect of the three motivational needs on user interaction outcome variables of a decision-making chatbot. Specifically, this study looks at the influence of relatedness, competency, and autonomy on user satisfaction, engagement, decision efficiency, and decision accuracy. A carefully designed experiment revealed that all three needs are important for user satisfaction and engagement while competency and autonomy is associated with decision accuracy. These findings highlight the importance of considering psychological constructs during AI design. Our findings also offer useful implications for AI designers and organizations that plan on using AI assisted chatbots to improve decision-making efforts.
AB - Progress of technology and processing power has enabled the advent of sophisticated technology including Artificial Intelligence (AI) agents. AI agents have penetrated society in many forms including conversation agents or chatbots. As these chatbots have a social component to them, is it critical to evaluate the social aspects of their design and its impact on user outcomes. This study employs Social Determination Theory to examine the effect of the three motivational needs on user interaction outcome variables of a decision-making chatbot. Specifically, this study looks at the influence of relatedness, competency, and autonomy on user satisfaction, engagement, decision efficiency, and decision accuracy. A carefully designed experiment revealed that all three needs are important for user satisfaction and engagement while competency and autonomy is associated with decision accuracy. These findings highlight the importance of considering psychological constructs during AI design. Our findings also offer useful implications for AI designers and organizations that plan on using AI assisted chatbots to improve decision-making efforts.
UR - http://www.scopus.com/inward/record.url?scp=85108351917&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85108351917&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85108351917
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 166
EP - 175
BT - Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
A2 - Bui, Tung X.
Y2 - 4 January 2021 through 8 January 2021
ER -