Ep. 232 - Building Trust and Inclusion in Tech-Hybrid Teams

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

  

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References:

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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

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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

 

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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

 

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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