Systematic Review: Trust-Building Factors and Implications for Conversational Agent Design

ABSTRACT Off-the-shelf conversational agents are permeating people’s everyday lives. In these artificial intelligence devices, trust plays a key role in users’ initial adoption and successful utilization. Factors enhancing trust toward conversational agents include appearances, voice features, and communication styles. Synthesizing such work will be useful in designing evidence-based, trustworthy conversational agents appropriate for various contexts. We conducted a systematic review of the experimental studies that investigated the effect of conversational agents’ and users’ characteristics on trust. From a full-text review of 29 articles, we identified five agent design-themes affecting trust toward conversational agents: social intelligence of the agent, voice characteristics and communication style, look of the agent, non-verbal communication, and performance quality. We also found that participants’ demographic, personality, or use context moderate the effect of these themes. We discuss implications for designing trustworthy conversational agents and responsibilities around on stereotypes and social norm building through agent design.

[1]  Kien Hoa Ly,et al.  A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods , 2017, Internet interventions.

[2]  Manfred Tscheligi,et al.  Interacting with embodied agents that can see: how vision-enabled agents can assist in spatial tasks , 2006, NordiCHI '06.

[3]  Sean Andrist,et al.  Effects of Culture on the Credibility of Robot Speech: A Comparison between English and Arabic , 2015, 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[4]  Manfred Tscheligi,et al.  I would choose the other card: humanoid robot gives an advice , 2009, HRI '09.

[5]  V B CERVIN,et al.  PERSUASIVENESS AND PERSUASIBILITY AS RELATED TO INTELLIGENCE AND EXTRAVERSION. , 1965, The British journal of social and clinical psychology.

[6]  J. H. Davis,et al.  An Integrative Model Of Organizational Trust , 1995 .

[7]  Joonhwan Lee,et al.  It Sounds Like A Woman: Exploring Gender Stereotypes in South Korean Voice Assistants , 2019, CHI Extended Abstracts.

[8]  James L. Szalma,et al.  A Meta-Analysis of Factors Influencing the Development of Trust in Automation , 2016, Hum. Factors.

[9]  Ilaria Torre,et al.  Trust in artificial voices: A "congruency effect" of first impressions and behavioural experience , 2018, APAScience.

[10]  B. J. Fogg,et al.  Credibility and computing technology , 1999, CACM.

[11]  Angelo Cangelosi,et al.  Priming Anthropomorphism: Can the credibility of humanlike robots be transferred to non-humanlike robots? , 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[12]  Brian Scassellati,et al.  Effects of form and motion on judgments of social robots' animacy, likability, trustworthiness and unpleasantness , 2016, Int. J. Hum. Comput. Stud..

[13]  D. Moher,et al.  Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement , 2009, BMJ : British Medical Journal.

[14]  Jessie Y. C. Chen,et al.  A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction , 2011, Hum. Factors.

[15]  S. Shyam Sundar,et al.  Are specialist robots better than generalist robots? , 2011, 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  Wolfgang Minker,et al.  Human After All: Effects of Mere Presence and Social Interaction of a Humanoid Robot as a Co-Driver in Automated Driving , 2016, AutomotiveUI.

[17]  Pei-Luen Patrick Rau,et al.  Effects of communication style and culture on ability to accept recommendations from robots , 2009, Comput. Hum. Behav..

[18]  Willem F. G. Haselager,et al.  Do Robot Performance and Behavioral Style a ↵ ect Human Trust ? A Multi-Method Approach , 2014 .

[19]  Luc Wijnen,et al.  "It's not my Fault!": Investigating the Effects of the Deceptive Behaviour of a Humanoid Robot , 2017, HRI.

[20]  Kun-Pyo Lee,et al.  Once a Kind Friend is Now a Thing: Understanding How Conversational Agents at Home are Forgotten , 2019, Conference on Designing Interactive Systems.

[21]  Nicole C. Krämer,et al.  Empathy for Everyone?: The Effect of Age When Evaluating a Virtual Agent , 2018, HAI.

[22]  Timothy W. Bickmore,et al.  Establishing and maintaining long-term human-computer relationships , 2005, TCHI.

[23]  Clifford Nass,et al.  Source Orientation in Human-Computer Interaction , 2000, Commun. Res..

[24]  E. C. Tupes,et al.  Personality characteristics related to leadership behavior in two types of small group situational problems. , 1958 .

[25]  Gordon L. Patzer,et al.  Source credibility as a function of communicator physical attractiveness , 1983 .

[26]  Juliane Junker Agents for Games and Simulations, Trends in Techniques, Concepts and Design [AGS 2009, The First International Workshop on Agents for Games and Simulations, May 11, 2009, Budapest, Hungary] , 2009, AGS.

[27]  Jodi Forlizzi,et al.  "Hey Alexa, What's Up?": A Mixed-Methods Studies of In-Home Conversational Agent Usage , 2018, Conference on Designing Interactive Systems.

[28]  Cynthia Breazeal,et al.  How smart are the smart toys?: children and parents' agent interaction and intelligence attribution , 2018, IDC.

[29]  Abigail Sellen,et al.  "Like Having a Really Bad PA": The Gulf between User Expectation and Experience of Conversational Agents , 2016, CHI.

[30]  Autumn P. Edwards,et al.  “Why Aren’t You a Sassy Little Thing”: The Effects of Robot-Enacted Guilt Trips on Credibility and Consensus in a Negotiation , 2016 .

[31]  Clifford Nass,et al.  The media equation - how people treat computers, television, and new media like real people and places , 1996 .

[32]  Roger K. Moore Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction , 2016, IWSDS.

[33]  J. G. Holmes,et al.  Trust in close relationships. , 1985 .

[34]  David Griol,et al.  The Conversational Interface , 2016 .

[35]  Karl F. MacDorman,et al.  The Uncanny Valley [From the Field] , 2012, IEEE Robotics Autom. Mag..

[36]  Beste F. Yuksel,et al.  Brains or Beauty , 2017, ACM Trans. Internet Techn..

[37]  Christopher A. Bailey,et al.  Social interaction moderates human-robot trust-reliance relationship and improves stress coping , 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[38]  Jessica A. Chen,et al.  Conversational agents in healthcare: a systematic review , 2018, J. Am. Medical Informatics Assoc..

[39]  Cynthia Breazeal,et al.  Persuasive Robotics: The influence of robot gender on human behavior , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[40]  D. Wiegmann,et al.  Similarities and differences between human–human and human–automation trust: an integrative review , 2007 .

[41]  J. Cassell,et al.  Social Dialongue with Embodied Conversational Agents , 2005 .

[42]  C. Nass,et al.  Are Machines Gender Neutral? Gender‐Stereotypic Responses to Computers With Voices , 1997 .

[43]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004, Hum. Factors.

[44]  Benjamin R. Cowan,et al.  "What can i help you with?": infrequent users' experiences of intelligent personal assistants , 2017, MobileHCI.

[45]  David R. Ewoldsen,et al.  The MODE Model and Its Implications for Studying the Media , 2015 .

[46]  P. Costa,et al.  Personality in adulthood: a six-year longitudinal study of self-reports and spouse ratings on the NEO Personality Inventory. , 1988, Journal of personality and social psychology.

[47]  Cynthia Breazeal,et al.  Computationally modeling interpersonal trust , 2013, Front. Psychol..

[48]  Brian Scassellati,et al.  The Ripple Effects of Vulnerability: The Effects of a Robot’s Vulnerable Behavior on Trust in Human-Robot Teams , 2018, 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[49]  Yugo Hayashi,et al.  Can AI become Reliable Source to Support Human Decision Making in a Court Scene? , 2017, CSCW Companion.

[50]  Justine Cassell,et al.  Relational agents: a model and implementation of building user trust , 2001, CHI.

[51]  J. Cassell,et al.  Embodied conversational agents , 2000 .

[52]  Aaron C. Elkins,et al.  The Sound of Trust: Voice as a Measurement of Trust During Interactions with Embodied Conversational Agents , 2013 .

[53]  C. Nass,et al.  Machines and Mindlessness , 2000 .

[54]  C. Nass,et al.  When a Talking-Face Computer Agent Is Half-Human and Half-Humanoid: Human Identity and Consistency Preference. , 2007 .

[55]  Mark A. Neerincx,et al.  Persuasive robotic assistant for health self-management of older adults: Design and evaluation of social behaviors , 2010, Int. J. Hum. Comput. Stud..

[56]  Kerstin Dautenhahn,et al.  Would You Trust a (Faulty) Robot? Effects of Error, Task Type and Personality on Human-Robot Cooperation and Trust , 2015, 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[57]  Fuyuan Shen,et al.  Benefits for Me or Risks for Others: A Cross-Culture Investigation of the Effects of Message Frames and Cultural Appeals , 2013, Health communication.

[58]  Ning Wang,et al.  Trust calibration within a human-robot team: Comparing automatically generated explanations , 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[59]  Philipp Wintersberger,et al.  (Over)Trust in Automated Driving: The Sleeping Pill of Tomorrow? , 2019, CHI Extended Abstracts.

[60]  Rachel K. E. Bellamy,et al.  At Face Value , 2021, Bigger Than Life.

[61]  Elaheh Sanoubari,et al.  A need for trust in conversational interface research , 2019, CUI.

[62]  S. Shyam Sundar,et al.  Machine Heuristic: When We Trust Computers More than Humans with Our Personal Information , 2019, CHI.

[63]  Bruce A. MacDonald,et al.  People respond better to robots than computer tablets delivering healthcare instructions , 2015, Comput. Hum. Behav..

[64]  J. Cacioppo,et al.  On seeing human: a three-factor theory of anthropomorphism. , 2007, Psychological review.

[65]  C. V. Ramamoorthy,et al.  Phase Coherence in Conceptual Spaces for Conversational Agents , 2010 .

[66]  Izak Benbasat,et al.  Evaluating Anthropomorphic Product Recommendation Agents: A Social Relationship Perspective to Designing Information Systems , 2009, J. Manag. Inf. Syst..

[67]  Futoshi Naya,et al.  Differences in effect of robot and screen agent recommendations on human decision-making , 2005, Int. J. Hum. Comput. Stud..

[68]  J. Gilbert,et al.  Virtual agents in e‐commerce: representational characteristics for seniors , 2011 .

[69]  Catherine J. Stevens,et al.  Robot Pressure: The Impact of Robot Eye Gaze and Lifelike Bodily Movements upon Decision-Making and Trust , 2014, ICSR.

[70]  Elisabeth André,et al.  An empirical study on the trustworthiness of life-like interface agents , 1999, HCI.

[71]  Jaap Ham,et al.  The Influence of Social Cues and Controlling Language on Agent's Expertise, Sociability, and Trustworthiness , 2017, HRI.

[72]  Kristinn R. Thórisson,et al.  The Power of a Nod and a Glance: Envelope Vs. Emotional Feedback in Animated Conversational Agents , 1999, Appl. Artif. Intell..

[73]  Jean E. Fox,et al.  The effects of information accuracy on user trust and compliance , 1996, CHI Conference Companion.

[74]  Jay F. Nunamaker,et al.  Embodied Conversational Agent-Based Kiosk for Automated Interviewing , 2011, J. Manag. Inf. Syst..