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Cited by 42AI in Service InteractionsInnovative Human-Technology InteractionSocial Robot Interaction and HRI

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

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De Vreede, Triparna, Raghavan, Mukhunth, De Vreede, Gert-Jan·2021·Proceedings of the Annual Hawaii International Conference on System Sciences
DOI 10.24251/hicss.2021.019
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Abstract

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.

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  • Previous studies assessing Basic Psychological Need Satisfaction in user experience design, automotive user interface design, or chatbot interaction have used individually adapted versions of existing scales.

    “Previous studies assessing BPN Satisfaction in broader user experience design contexts (e.g., Hassenzahl et al., 2010;Karapanos et al., 2015;Lallemand et al., 2014;Partala & Kallinen, 2012;Tuch et al., 2013), automotive user interface design (Stiegemeier et al., 2022), or during chatbot interaction (e.g., De Vreede et al., 2021;Jiménez-Barreto et al., 2021;Moradbakhti et al., 2022) have used”

    From Development and Validation of a Basic Psychological Needs Scale for Technology Use (2024) · cites this paper as De Vreede et al., 2021

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Cited by

Sorted by citations

Authors
De Vreede, T., Raghavan, M., & De Vreede, G.-J.
Affiliations
University of South Florida (US)
ORCID
Raghavan, Mukhunth
Venue
Proceedings of the Annual Hawaii International Conference on System Sciences
Publisher
Hawaii International Conference on System Sciences
Published
2021
ISSN
  • 1530-1605 (ISSN-L)
  • 2572-6862
DOI
10.24251/hicss.2021.019
OpenAlex
W3128956710
Cited by
42
References
9
Citations by year
2026: 8 · 2025: 10 · 2024: 12 · 2023: 9 · 2022: 2 · 2021: 1
FWCI
2.68
Type
conference paper
Language
en
Open access
Locations
  • Hawaii International Conference on System Sciences (HICSS) (publishedVersion)
  • ScholarSpace (University of Hawaii at Manoa) (submittedVersion, cc-by-nc-nd)
  • Journal of the Association for Information Systems (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
Keywords
AI-assisted decision-making, chatbots, self-determination theory, relatedness, autonomy, competence, user satisfaction, user engagement, decision accuracy, decision-making efficiency, AI design

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