Show notes
We explored the challenges and potential solutions for building trust, inclusion, and collaboration in tech-hybrid or remote teams.
A focus on how technology supports transparent communication and fosters connections in tech-enabled environments related to socio-technical teams. (Tech-hybrid teams blend humans and robotics, AI, or other modern technology as team members.)
In this Episode: Dr. Emi Baressi, Tom Bradshaw, special guests Keith and Daniel Edwards from the Houston RobotLab, Dr. Matt Lampe, Alexander Abney-King, Nic Krueger, Rich Cruz, Dr. Martha Grajdek
Visit us https://www.seboc.com/
Follow us on LinkedIn: https://bit.ly/sebocLI
Join an open-mic event: https://www.seboc.com/events
References:
Arslan, A., Cooper, C., Khan, Z., Golgeci, I., & Ali, I. (2022). Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower, 43(1), 75–88. https://doi.org/10.1108/IJM-01-2021-0052
Berretta, S., Tausch, A., Ontrup, G., Gilles, B., Peifer, C., & Kluge, A. (2023). Defining human-AI teaming the human-centered way: A scoping review and network analysis. Frontiers in Artificial Intelligence, 6, 1250725–1250725. https://doi.org/10.3389/frai.2023.1250725
Belanger, F., Collins, R. W., & Cheney, P. H. (2001). Technology Requirements and Work Group Communication for Telecommuters. Information Systems Research, 12(2), 155–176. https://doi.org/10.1287/isre.12.2.155.9695
Belling, S. (2021). PsychoWorkplacegenerationslogy of Remote Teams: Trust, People, and Connections. In Remotely Possible (pp. 59–73). Apress. https://doi.org/10.1007/978-1-4842-7008-0_5
Boccoli, G., Gastaldi, L., & Corso, M. (2024). Transformational leadership and work engagement in remote work settings: The moderating role of the supervisor’s digital communication skills. Leadership & Organization Development Journal, 45(7), 1240–1257. https://doi.org/10.1108/LODJ-09-2023-0490
Brock, J. K.-U., & von Wangenheim, F. (2019). Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. California Management Review, 61(4), 110–134. https://doi.org/10.1177/1536504219865226
Chin, J. H., Haring, K. S., & Kim, P. (2023). Understanding the neural mechanisms of empathy toward robots to shape future applications. Frontiers in neurorobotics, 17, 1145989. https://doi.org/10.3389/fnbot.2023.1145989
Ezer, N., Bruni, S., Cai, Y., Hepenstal, S. J., Miller, C. A., & Schmorrow, D. D. (2019). Trust Engineering for Human-AI Teams. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 63(1), 322–326. https://doi.org/10.1177/1071181319631264
Flathmann, C., Schelble, B. G., Rosopa, P. J., McNeese, N. J., Mallick, R., & Madathil, K. C. (2023). Examining the impact of varying levels of AI teammate influence on human-AI teams. International Journal of Human-Computer Studies, 177, 103061-. https://doi.org/10.1016/j.ijhcs.2023.103061
Fuchs, A., Passarella, A., & Conti, M. (2024). Optimizing Delegation in Collaborative Human-AI Hybrid Teams. ACM Transactions on Autonomous and Adaptive Systems. https://doi.org/10.1145/3687130
Guznov, S., Lyons, J., Pfahler, M., Heironimus, A., Woolley, M., Friedman, J., & Neimeier, A. (2020). Robot Transparency and Team Orientation Effects on Human-Robot Teaming. International Journal of Human-Computer Interaction, 36(7), 650–660. https://doi.org/10.1080/10447318.2019.1676519
Hagemann, V., Rieth, M., Suresh, A., & Kirchner, F. (2023). Human-AI teams—Challenges for a team-centered AI at work. Frontiers in Artificial Intelligence, 6, 1252897–1252897. https://doi.org/10.3389/frai.2023.1252897
Harris-Watson, A. M., Larson, L. E., Lauharatanahirun, N., DeChurch, L. A., & Contractor, N. S. (2023). Social perception in Human-AI teams: Warmth and competence predict receptivity to AI teammates. Computers in Human Behavior, 145, 107765-. https://doi.org/10.1016/j.chb.2023.107765
Hauptman, A. I., Schelble, B. G., Duan, W., Flathmann, C., & McNeese, N. J. (2024). Understanding the influence of AI autonomy on AI explainability levels in human-AI teams using a mixed methods approach. Cognition, Technology & Work, 26(3), 435–455. https://doi.org/10.1007/s10111-024-00765-7
Hauptman, A. I., Schelble, B. G., McNeese, N. J., & Madathil, K. C. (2023). Adapt and overcome: Perceptions of adaptive autonomous agents for human-AI teaming. Computers in Human Behavior, 138, 107451-. https://doi.org/10.1016/j.chb.2022.107451
Li, M., Kwon, M., & Sadigh, D. (2021). Influencing leading and following in human–robot teams. Autonomous Robots, 45(7), 959–978. https://doi.org/10.1007/s10514-021-10016-7
Ma, L. M., Ijtsma, M., Feigh, K. M., & Pritchett, A. R. (2022). Metrics for Human-Robot Team Design: A Teamwork Perspective on Evaluation of Human-Robot Teams. ACM Transactions on Human-Robot Interaction, 11(3), 1–36. https://doi.org/10.1145/3522581
Naikar, N., Brady, A., Moy, G., & Kwok, H.-W. (2023). Designing human-AI systems for complex settings: ideas from distributed, joint, and self-organising perspectives of sociotechnical systems and cognitive work analysis. Ergonomics, 66(11), 1669–1694. https://doi.org/10.1080/00140139.2023.2281898
Traeger, M. L., Sebo, S. 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. https://doi.org/10.1073/pnas.1910402117
You, S., & Robert, L. P. (2022). Team robot identification theory (TRIT): robot attractiveness and team identification on performance and viability in human–robot teams. The Journal of Supercomputing, 78(18), 19684–19706. https://doi.org/10.1007/s11227-022-04645-7