Understanding the impact and design of AI teammate etiquette

References

• Abdelwahab, O., & Elmaghraby, A. (2018, July). Deep learning based vs. Markov chain based text generation for cross domain adaptation for sentiment classification. In 2018 IEEE International Conference on Information Reuse and Integration (IRI) (pp. 252–255). https://doi.org/10.1109/IRI.2018.00046
   Google Scholar
• Adinolf, S., & Turkay, S. (2018, October). Toxic behaviors in esports games: Player perceptions and coping strategies. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts (pp. 365–372). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/3270316.3271545
   Google Scholar
• Alan, A. T., Costanza, E., Ramchurn, S. D., Fischer, J., Rodden, T., & Jennings, N. R. (2016). Tariff agent: Interacting with a future smart energy system at home. ACM Transactions on Computer- Human Interaction (TOCHI), 23(4), 1–28. https://doi.org/10.1145/2943770
   Google Scholar
• Atoyan, H., Duquet, J. -R., & Robert, J. -M. (2006). Trust in new decision aid systems. In Proceedings of the 18th conference on l’interaction homme-machine, Montreal Canada, (pp. 115–122).
   Google Scholar
• Babel, F., Kraus, J. M., & Baumann, M. (2021). Development and testing of psychological conflict resolution strategies for assertive robots to resolve human–robot goal conflict. Frontiers in Robotics and AI, 7. https://doi.org/10.3389/frobt.2020.591448
   Google Scholar
• Baker, A. L., Phillips, E. K., Ullman, D., & Keebler, J. R. (2018, November). Toward an understanding of trust repair in human-robot interaction: Current research and future directions. ACM Transactions on Interactive Intelligent Systems, 8(4), 30:1–30:30. https://doi.org/10.1145/3181671
   Google Scholar
• Bansal, G., Nushi, B., Kamar, E., Lasecki, W. S., Weld, D. S., & Horvitz, E. (2019). Beyond accuracy: The role of mental models in human-ai team performance. In Proceedings of the aaai conference on human computation and crowdsourcing, Stevenson Washington, USA, (Vol. 7, pp. 2–11).
   Google Scholar
• Bergstrom, N., Kanda, T., Miyashita, T., Ishiguro, H., & Hagita, N. (2008). Modeling of natural human-robot encounters. In 2008 ieee/rsj international conference on intelligent robots and systems, Madrid, Spain, (pp. 2623–2629).
   Google Scholar
• Bhatti, S., Demir, M., Cooke, N. J., & Johnson, C. J. (2021). Assessing communication and trust in an ai teammate in a dynamic task environment. In 2021 ieee 2nd international conference on human-machine systems (ichms), Magdeburg, Germany, (pp. 1–6).
   Google Scholar
• Bickmore, T., & Cassell, J. (2005). Social dialongue with embodied conversational agents. In van Kuppevel, J, Dybkjaer, L, & Bernsen, N. (eds.). Advances in natural multimodal dialogue systems, (pp. 23–54). Springer.
   Google Scholar
• Bliese, P. D. (2000). Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis.
   Google Scholar
• Braun, V., & Clarke, V. (2012). Thematic analysis. American Psychological Association.
   Google Scholar
• Chakraborti, T., Kambhampati, S., Scheutz, M., & Zhang, Y. (2017). Ai challenges in human-robot cognitive teaming. arXiv preprint arXiv 170704775.
   Google Scholar
• Chen, J. Y. C., & Barnes, M. J. (2014, February). Human–agent teaming for multirobot control: A review of human factors issues. IEEE Transactions on Human-Machine Systems, 44(1), 13–29. https://doi.org/10.1109/THMS.2013.2293535
   Web of Science ®Google Scholar
• Chiou, E. K., Demir, M., Buchanan, V., Corral, C. C., Endsley, M. R., Lematta, G. J., McNeese, N. J. (2022). Towards human–robot teaming: Tradeoffs of explanation-based communication strategies in a virtual search and rescue task. International Journal of Social Robotics, 14(5), 1117–1136. https://doi.org/10.1007/s12369-021-00834-1
   Google Scholar
• Chiou, E. K., & Lee, J. D. (2021). Trusting automation: Designing for responsivity and resilience. Human Factors: The Journal of the Human Factors and Ergonomics Society, 65(1), 00187208211009995. https://doi.org/10.1177/00187208211009995
   Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Academic press.
   Google Scholar
• Culley, K. E., & Madhavan, P. (2013). A note of caution regarding anthropomorphism in hci agents. Computers in Human Behavior, 29(3), 577–579. https://doi.org/10.1016/j.chb.2012.11.023
   Web of Science ®Google Scholar
• Cummings, L. L., & Bromiley, P. (1996). The organizational trust inventory (oti). Trust in Organizations: Frontiers of Theory and Research, 302(330), 39–52.
   Google Scholar
• Dautenhahn, K., Walters, M., Woods, S., Koay, K. L., Nehaniv, C. L., Sisbot, A., Siméon, T. (2006). How may i serve you? a robot companion approaching a seated person in a helping context. In Proceedings of the 1st acm sigchi/sigart conference on human-robot interaction, Salt Lake City, Utah, USA. (pp. 172–179).
   Google Scholar
• Demir, M., McNeese, N. J., Cooke, N. J., Ball, J. T., Myers, C., & Frieman, M. (2015, September). Synthetic Teammate Communication and Coordination with Humans. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 59(1), 951–955. Publisher: SAGE Publications Inc https://doi.org/10.1177/1541931215591275
   Google Scholar
• de Visser, E. J., Pak, R., & Neerincx, M. A. (2017, March). Trust Development and Repair in Human- Robot Teams. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (pp. 103–104). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3029798.3038409
   Google Scholar
• Dillon, A., & Watson, C. (1996). User analysis in hci—the historical lessons from individual differences research. International Journal of Human-Computer Studies, 45(6), 619–637. https://doi.org/10.1006/ijhc.1996.0071
   Web of Science ®Google Scholar
• Dzindolet, M. T., Peterson, S. A., Pomranky, R. A., Pierce, L. G., & Beck, H. P. (2003). The role of trust in automation reliance. International Journal of Human-Computer Studies, 58(6), 697–718. https://doi.org/10.1016/S1071-5819(03)00038-7
   Web of Science ®Google Scholar
• Ezer, N., Bruni, S., Cai, Y., Hepenstal, S. J., Miller, C. A., & Schmorrow, D. D. (2019). Trust engineering for human-ai teams. In Proceedings of the human factors and ergonomics society annual meeting, Seattle, Washington, USA, (Vol. 63, pp. 322–326).
   Google Scholar
• Flathmann, C., McNeese, N., & Canonico, L. B. (2019). Using human-agent teams to purposefully design multi-agent systems. In Proceedings of the human factors and ergonomics society annual meeting, Seattle, Washington, USA, (Vol. 63, pp. 1425–1429).
   Google Scholar
• Flathmann, C., Schelble, B. G., Zhang, R., & McNeese, N. J. (2021). Modeling and guiding the creation of ethical human-ai teams. In Proceedings of the 2021 aaai/acm conference on ai, ethics, and society (pp. 469–479).
   Google Scholar
• Følstad, A., Nordheim, C. B., & Bjørkli, C. A. (2018). What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview Study. In S. S. Bodrunova (Ed.), Internet Science (pp. 194–208). Springer International Publishing. https://doi.org/10.1007/978-3-030-01437-716
   Google Scholar
• Gavin, H. (2008). Thematic analysis. Understanding Research Methods and Statistics in Psychology, 273–282.
   Google Scholar
• Gillespie, N., & Dietz, G. (2009, January), Trust Repair After an Organization-Level Failure. Academy of Management Review, 34(1), 127–145. Publisher: Academy of Management https://doi.org/10.5465/amr.2009.35713319
   Web of Science ®Google Scholar
• Gombolay, M., Bair, A., Huang, C., & Shah, J. (2017, June), Computational design of mixed- initiative human–robot teaming that considers human factors: Situational awareness, work- load, and workflow preferences. The International Journal of Robotics Research, 36(5–7), 597–617. Publisher: SAGE Publications Ltd STMhttps://doi.org/10.1177/0278364916688255
   Web of Science ®Google Scholar
• Goodrich, M. A., Morse, B. S., Gerhardt, D., Cooper, J. L., Quigley, M., Adams, J. A., & Humphrey, C. (2008). Supporting wilderness search and rescue using a camera-equipped mini uav. Journal of Field Robotics, 25(1–2), 89–110. https://doi.org/10.1002/rob.20226
   Web of Science ®Google Scholar
• Grawitch, M. J., & Munz, D. C. (2004). Are your data nonindependent? a practical guide to evaluating nonindependence and within-group agreement. Understanding Statistics, 3(4), 231–257. https://doi.org/10.1207/s15328031us0304_2
   Google Scholar
• Grover, S., Sengupta, S., Chakraborti, T., Mishra, A. P., & Kambhampati, S. (2020, November), RADAR: Automated task planning for proactive decision support. Human–Computer Interaction, 35(5–6), 387–412. Publisher: Taylor & Francis eprint https://doi.org/10.1080/07370024.2020.1726751
   Web of Science ®Google Scholar
• Haring, K. S., Satterfield, K. M., Tossell, C. C., De Visser, E. J., Lyons, J. R., Mancuso, V. F., Funke, G. J. (2021). Robot authority in human-robot teaming: Effects of human-likeness and physical embodiment on compliance. Frontiers in Psychology, 12, 625713. https://doi.org/10.3389/fpsyg.2021.625713
   PubMedGoogle Scholar
• Hart, S. G., & Staveland, L. E. (1988, January). Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. In P. A. Hancock & N. Meshkati Eds., Advances in Psychology Vol. 52 (pp. 139–183). North-Holland. https://doi.org/10.1016/S0166-41150862386-9
   Google Scholar
• Hinds, P. J., Roberts, T. L., & Jones, H. (2004). Whose job is it anyway? a study of human-robot interaction in a collaborative task. Human–Computer Interaction, 19(1–2), 151–181.
   Web of Science ®Google Scholar
• Homewood, S. (2016, May). Maintaining relationships with our devices. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 273–276). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/2851581.2889467
   Google Scholar
• Horwitz, S. K. (2005). The compositional impact of team diversity on performance: Theoretical considerations. Human Resource Development Review, 4(2), 219–245. https://doi.org/10.1177/1534484305275847
   Google Scholar
• Horwitz, S. K., & Horwitz, I. B. (2007). The effects of team diversity on team outcomes: A meta- analytic review of team demography. Journal of Management, 33(6), 987–1015. https://doi.org/10.1177/0149206307308587
   Web of Science ®Google Scholar
• Inkpen, K., Chancellor, S., De Choudhury, M., Veale, M., & Baumer, E. P. S. (2019, May). Where is the human? Bridging the gap between AI and HCI. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1–9). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3290607.3299002
   Google Scholar
• James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating within-group interrater reliability with and without response bias. The Journal of Applied Psychology, 69(1), 85. https://doi.org/10.1037/0021-9010.69.1.85
   Web of Science ®Google Scholar
• Jones, H., & Hinds, P. (2002). Extreme work teams: Using swat teams as a model for coordinating distributed robots. In Proceedings of the 2002 acm conference on computer supported cooperative work, New Orleans, Louisiana, USA, (pp. 372–381).
   Google Scholar
• Jung, M. F., Martelaro, N., & Hinds, P. J. (2015). Using robots to moderate team conflict: The case of repairing violations. In Proceedings of the tenth annual acm/ieee international conference on human-robot interaction, Portland, Oregon, USA, (pp. 229–236).
   Google Scholar
• Karreman, D., Utama, L., Joosse, M., Lohse, M., van Dijk, B., & Evers, V. (2014). Robot etiquette: How to approach a pair of people? In Proceedings of the 2014 acm/ieee international conference on human-robot interaction, Bielefeld, Germany, (pp. 196–197).
   Google Scholar
• Koay, K. L., Walters, M. L., May, A., Dumitriu, A., Christianson, B., Burke, N., & Dautenhahn, K. (2013). Exploring robot etiquette: Refining a hri home companion scenario based on feedback from two artists who lived with robots in the uh robot house. In International conference on social robotics, Bristol, UK, (pp. 290–300).
   Google Scholar
• Law, T., & Scheutz, M. (2021). Trust: Recent concepts and evaluations in human-robot interaction. In Nam, C., & Lyons, J. Trust in human-robot interaction, (pp. 27–57). Elsevier.
   Google Scholar
• Liao, Q. V., Gruen, D., & Miller, S. (2020, April). Questioning the AI: Informing design practices for explainable ai user experiences. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–15). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3313831.3376590
   Google Scholar
• Looi, Q. E., & See, S. L. (2012). Applying politeness maxims in social robotics polite dialogue. In Proceedings of the seventh annual acm/ieee international conference on human-robot interaction, Boston, Massachusetts, USA, (pp. 189–190).
   Google Scholar
• Lounsbury, J. W., Smith, R. M., Levy, J. J., Leong, F. T., & Gibson, L. W. (2009, March). Personality characteristics of business majors as defined by the big five and narrow personality traits. Journal of Education for Business, 84(4), 200–205. https://doi.org/10.3200/JOEB.84.4.200-205
   Google Scholar
• Lucas, G. M., Gratch, J., King, A., & Morency, L. -P. (2014). It’s only a computer: Virtual humans increase willingness to disclose. Computers in Human Behavior, 37, 94–100. https://doi.org/10.1016/j.chb.2014.04.043
   Web of Science ®Google Scholar
• Lyons, J. B., Aldin Hamdan, I., & Vo, T. Q. (2023). Explanations and trust: What happens to trust when a robot partner does something unexpected? Computers in Human Behavior, 138, 107473. https://doi.org/10.1016/j.chb.2022.107473
   Web of Science ®Google Scholar
• Madhavan, P., & Wiegmann, D. A. (2007). Similarities and differences between human–human and human–automation trust: An integrative review. Theoretical Issues in Ergonomics Science, 8(4), 277–301. https://doi.org/10.1080/14639220500337708
   Google Scholar
• McNeese, N., Demir, M., Chiou, E., Cooke, N., & Yanikian, G. (2019). Understanding the role of trust in human-autonomy teaming. Hawaii International Conference on Social Systems, Maui, HI, USA. https://doi.org/10.24251/HICSS.2019.032
   Google Scholar
• McNeese, N. J., Demir, M., Cooke, N. J., & Myers, C. (2018, March). Teaming with a Synthetic Teammate: Insights into Human-Autonomy Teaming. Human Factors: The Journal of the Human Factors and Ergonomics Society, 60(2), 262–273. Publisher: SAGE Publications Inc https://doi.org/10.1177/0018720817743223
   PubMed Web of Science ®Google Scholar
• McNeese, N. J., Schelble, B. G., Canonico, L. B., & Demir, M. (2021). Who/What is my teammate? team composition considerations in human–ai te aming. IEEE Transactions on Human-Machine Systems, 51(4), 288–299. https://doi.org/10.1109/THMS.2021.3086018
   Web of Science ®Google Scholar
• Meyer, J., Miller, C., Hancock, P., De Visser, E. J., & Dorneich, M. (2016). Politeness in machine- human and human-human interaction. In Proceedings of the human factors and ergonomics society annual meeting, Washington, DC, USA, (Vol. 60, pp. 279–283).
   Google Scholar
• Miller, C. A. (2002). Definitions and dimensions of etiquette. In Proc. aaai fall symposium on etiquette and human-computer work. North Falmount, MA, USA.
   Google Scholar
• Miller, C. A. (2005). Trust in adaptive automation: The role of etiquette in tuning trust via analogic and affective methods. In Proceedings of the 1st international conference on augmented cognition (pp. 22–27).
   Google Scholar
• Miller, C. A. (2011). Relationships and etiquette with technical systems. In Whitworth, B., & de Moor, A.Virtual communities: Concepts, methodologies, tools and applications, (pp. 1618–1633). IGI Global.
   Google Scholar
• Mishra, P., & Hershey, K. A. (2004). Etiquette and the design of educational technology. Communications of the ACM, 47(4), 45–49. https://doi.org/10.1145/975817.975843
   Web of Science ®Google Scholar
• Moreno, K. N., Person, N. K., Adcock, A. B., Eck, R., Jackson, G. T., & Marineau, J. C. (2002). Etiquette and efficacy in animated pedagogical agents: The role of stereotypes. Aaai symposium on personalized agents, cape cod, Cape Cod, MA, USA, ma.
   Google Scholar
• Musick, G., O’neill, T. A., Schelble, B. G., McNeese, N. J., & Henke, J. B. (2021). What happens when humans believe their teammate is an ai? an investigation into humans teaming with autonomy. Computers in Human Behavior, 122, 106852. https://doi.org/10.1016/j.chb.2021.106852
   Web of Science ®Google Scholar
• Neustaedter, C., & Greenberg, S. (2012, May). Intimacy in long-distance relationships over video chat. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 753–762). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/2207676.2207785
   Google Scholar
• Ogden, B., & Dautenhahn, K. (2000). Robotic etiquette: Structured interaction in humans and robots. In Procs sirs 2000, 8th symp on intelligent robotic systems Reading, UK.
   Google Scholar
• O’neill, T., McNeese, N., Barron, A., & Schelble, B. (2022). Human–autonomy teaming: A review and analysis of the empirical literature. Human Factors: The Journal of the Human Factors and Ergonomics Society, 64(5), 904–938. https://doi.org/10.1177/0018720820960865
   PubMed Web of Science ®Google Scholar
• Parasuraman, R., & Miller, C. A. (2004). Trust and etiquette in high-criticality automated systems. Communications of the ACM, 47(4), 51–55. https://doi.org/10.1145/975817.975844
   Web of Science ®Google Scholar
• Parasuraman, R., & Riley, V. (1997, June). Humans and automation: Use, misuse, disuse, abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society, 39(2), 230–253. Publisher: SAGE Publications Inc https://doi.org/10.1518/001872097778543886
   Web of Science ®Google Scholar
• Pipitone, A., Geraci, A., D’amico, A., Seidita, V., & Chella, A. (2021). Robot’s inner speech effects on trust and anthropomorphic cues in human-robot cooperation. arXiv preprint arXiv 210909388.
   Google Scholar
• Ramos, G., Meek, C., Simard, P., Suh, J., & Ghorashi, S. (2020, November). Interactive machine teaching: A human-centered approach to building machine-learned models. Human–Computer Interaction, 35(5–6), 413–451. https://doi.org/10.1080/07370024.2020.1734931
   Web of Science ®Google Scholar
• Rentsch, J. R., & Klimoski, R. J. (2001). Why do ‘great minds’ think alike?: Antecedents of team member schema agreement. Journal of Organizational Behavior, 22(2), 107–120. https://doi.org/10.1002/job.81
   Web of Science ®Google Scholar
• Salas, E., Dickinson, T. L., Converse, S. A., & Tannenbaum, S. I. (1992). Toward an Understanding of Team Performance and Training. In Sweezy, R. W., Salas, E. (eds.). Teams: Their Training and Performance.
   Google Scholar
• Salas, E., Sims, D. E., & Burke, C. S. (2005, October). Is there a “Big Five” in Teamwork? Small Group Research, 36(5), 555–599. Publisher: SAGE Publications Inc https://doi.org/10.1177/1046496405277134
   Web of Science ®Google Scholar
• Schelble, B. G., Flathmann, C., & McNeese, N. (2020). Towards meaningfully integrating human- autonomy teaming in applied settings. In Proceedings of the 8th international conference on human-agent interaction, Melbourne, Australia, (pp. 149–156).
   Google Scholar
• Schiaffino, S., & Amandi, A. (2006). Polite personal agents. IEEE Intelligent Systems, 21(1), 12–19. https://doi.org/10.1109/MIS.2006.15
   Google Scholar
• Schulte, A., Donath, D., & Lange, D. S. (2016). Design Patterns for Human-Cognitive Agent Teaming. In D. Harris (Ed.), Engineering Psychology and Cognitive Ergonomics (pp. 231–243). Springer International Publishing. https://doi.org/10.1007/978-3-319-40030-324
   Google Scholar
• Seeber, I., Bittner, E., Briggs, R. O., De Vreede, T., De Vreede, G. -J., Elkins, A., Maier, R., Merz, A. B., Oeste-Reiß, S., Randrup, N., Schwabe, G., & Söllner, M. (2020). Machines as teammates: A research agenda on ai in team collaboration. Information & Management, 57(2), 103174. https://doi.org/10.1016/j.im.2019.103174
   Web of Science ®Google Scholar
• Shklovski, I., Kraut, R., & Cummings, J. (2008, April). Keeping in touch by technology: Maintaining friendships after a residential move. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 807–816). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/1357054.1357182.
   Google Scholar
• Sierhuis, M., Bradshaw, J. M., Acquisti, R., Van Hoof, R., & Jeffers, R. (2003). Human-agent teamwork and adjustable autonomy in practice. In Proceedings of the Seventh International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS). Nara, Japan, Citeseer.
   Google Scholar
• Sin, J., & Munteanu, C. (2020, November). An empirically grounded sociotechnical perspective on designing virtual agents for older adults. Human–Computer Interaction, 35(5–6), 481–510. Publisher: Taylor & Francis https://doi.org/10.1080/07370024.2020.1731690
   Web of Science ®Google Scholar
• Skantze, G. (2021). Turn-taking in conversational systems and human-robot interaction: A review. Computer Speech & Language, 67, 101178. https://doi.org/10.1016/j.csl.2020.101178
   Web of Science ®Google Scholar
• Svikhnushina, E., & Pu, P. (2020). Social and emotional etiquette of chatbots: A qualitative approach to understanding user needs and expectations. arXiv preprint arXiv 200613883.
   Google Scholar
• Textor, C., Zhang, R., Lopez, J., Schelble, B. G., McNeese, N. J., Freeman, G., de Visser, E. J. (2022). Exploring the relationship between ethics and trust in human–artificial intelligence teaming: A mixed methods approach. Journal of Cognitive Engineering and Decision Making, 16(4), 252–281. https://doi.org/10.1177/15553434221113964
   Web of Science ®Google Scholar
• Thomas, J., & Vaughan, R. (2018, October). AfteR you: Doorway negotiation for human-robot and robot-robot interaction. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3387–3394). ( ISSN: 2153-0866) https://doi.org/10.1109/IROS.2018.8594034
   Google Scholar
• Thomas, J., & Vaughan, R. (2019, November). Right of way, assertiveness and social recognition in human-robot doorway interaction. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 333–339). ( ISSN: 2153-0866) https://doi.org/10.1109/IROS40897.2019.8967862
   Google Scholar
• Traeger, M. L., Strohkorb Sebo, S., Jung, M., Scassellati, B., & Christakis, N. A. (2020). Vulnerable robots positively shape human conversational dynamics in a human–robot team. Proceedings of the National Academy of Sciences, 117(12), 6370–6375.
   Google Scholar
• Trinh, T. Q., Schroeter, C., Kessler, J., & Gross, H. -M. (2015). “Go ahead, please”: Recognition and resolution of conflict situations in narrow passages for polite mobile robot navigation. In International conference on social robotics, Paris, France, (pp. 643–653).
   Google Scholar
• Türkay, S., Formosa, J., Adinolf, S., Cuthbert, R., & Altizer, R. (2020, April). SeE no evil, hear no evil, speak no evil: How collegiate players define, experience and cope with toxicity. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–13). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/3313831.3376191
   Google Scholar
• Van Pinxteren, M. M., Pluymaekers, M., & Lemmink, J. G. (2020). Human-like communication in conversational agents: A literature review and research agenda. Journal of Service Management, 31(2), 203–225. https://doi.org/10.1108/JOSM-06-2019-0175
   Web of Science ®Google Scholar
• Walters, M. L., Dautenhahn, K., Woods, S. N., & Koay, K. L. (2007). Robotic etiquette: Results from user studies involving a fetch and carry task. In 2007 2nd acm/ieee international conference on human-robot interaction (hri), Arlington, Virginia, USA. (pp. 317–324).
   Google Scholar
• Wang, Y., Murray, R. C., Bao, H., & Rose, C. (2020). Agent-based dynamic collaboration support in a smart office space. In Proceedings of the 21th annual meeting of the special interest group on discourse and dialogue. Virtual. (pp. 257–260).
   Google Scholar
• Wiltshire, T. J., Barber, D., & Fiore, S. M. (2013). Towards modeling social-cognitive mechanisms in robots to facilitate human-robot teaming. In Proceedings of the human factors and ergonomics society annual meeting (Vol. 57, pp. 1278–1282). SAGE Publications Sage CA: Los Angeles, CA. https://doi.org/10.1177/1541931213571283
   Google Scholar
• Xu, W. (2019, June). Toward human-centered AI: A perspective from human-computer interaction. Interactions, 26(4), 42–46. https://doi.org/10.1145/3328485
   Google Scholar
• Zhang, T., Zhu, B., & Kaber, D. B. (2010). Setting etiquette expectations Hayes, C., Miller , C. (eds.). Human-Computer Etiquette, (pp. 231–259). CRC Press.
   Google Scholar
• Zheng, Y. (2019, September). A course on applied ai and data science: Recommender systems. In Proceedings of the 20th Annual SIG Conference on Information Technology Education (pp. 43–48). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/3349266.3351405
   Google Scholar