Design Foundations for AI Assisted Decision-Making: A Self Determination Theory Approach

被引:0
作者
de Vreede, Triparna [1 ]
Raghavan, Mukhunth [1 ]
de Vreede, Gert-Jan [1 ]
机构
[1] Univ S Florida, Tampa, FL 33620 USA
来源
PROCEEDINGS OF THE 54TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES | 2021年
关键词
ARTIFICIAL-INTELLIGENCE; INFORMATION-SYSTEMS; USER ENGAGEMENT; SATISFACTION; PERFORMANCE; COMPETENCE; EFFICACY; MOTIVATIONS; VALIDATION; FRAMEWORK;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:166 / 175
页数:10
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