Teams are increasingly the locus of our work and leisure, with the study of such groups still important for human flourishing. This essay focuses on four aspects of studying team diversity: topics (e.g., language, human-AI teams), theory, multidisciplinary approaches, and funding/conducting such research. Not only are different types of heterogeneity fruitful to study, but the next decade could see a diversity of theories, approaches, and ways to support such research.
AggarwalI.WoolleyA. W. (2013). Do you see what I see? The effect of members’ cognitive styles on team processes and errors in task execution. Organizational Behavior and Human Decision Processes, 122, 92–99. http://dx.doi.org/10.1016/j.obhdp.2013.04.003
2.
BellS. T. (2007). Deep-level composition variables as predictors of team performance: A meta-analysis. Journal of Applied Psychology, 92, 595–615.
BonsignoreE.NanduriD. K.BlinderE.LinY.DwivediU.GuhaM. L.TareM.KacorriH. (2026). Participatory AI: Children and families co-designing and collaborating with AI systems. In: PaletzS. B. F.DubrowS. (Eds.), AI in teams (pp. 171–195). Emerald Publishing.
5.
BraunerE.BoosM.KolbeM. (Eds.) (2018). The Cambridge handbook of group interaction analyses. Cambridge University Press.
6.
CarterB. M.PaletzS. B. F.CampbellS. G.O’RourkeP.CarrawayM. J.VahlkampS. H.SchwartzJ. (2026). There is no “AI” in teams: A multi-disciplinary framework for AIs to work in human teams. In: BonnerB.BaumannM. (Eds.), Research handbook on group decision making. Research Handbooks on Social Psychology Series. Edward Elgar.
7.
ColellaA.BoehmS. A. (2026). Disability and employment in transition: Challenges, innovations, and opportunities. Annual Review of Organizational Psychology and Organizational Behavior, 13, 277–307. https://doi.org/10.1146/annurev-orgpsych-110622-055845
8.
CookeN. J.CohenM. C.FazioW. C.InderbergL. H.JohnsonC. J.LemattaG. J.PeelM.TeoA. (2023). From teams to teamness: Future directions in the science of team cognition. Human Factors, 66(6), 1669–1680. https://doi.org/10.1177/00187208231162449
9.
CookeN. J.GormanJ. C.MyersC. W.DuranJ. L. (2013). Interactive team cognition. Cognitive Science, 37, 255–285.
10.
CroninM. A.WeingartL. R.TodorovaG. (2011). Dynamics in groups: Are we there yet?Academy of Management Annals, 5(1), 571–612.
11.
FangZ.AhrnsbrakR.RekitoA. (2024). Evidence mounts that about 7% of US adults have had long COVID. JAMA Data Brief, 332(1), 5–6. https://doi.org/10.1001/jama.2024.11370
12.
FioreS. M. (2008). Interdisciplinarity as teamwork: How the science of teams can inform team science. Small Group Research, 39(3), 251–277. https://doi.org/10.1177/1046496408317797
13.
FioreS. M. (2025). Social science and social AI: Developing artificial social intelligence to support teams. The International FLAIRS Conference Proceedings, 38(1), 139096. https://doi.org/10.32473/flairs.38.1.139096
14.
FioreS. M.RosenM. A.Smith-JentschK. A.SalasE.LetskyM.WarnerN. (2010). Toward an understanding of macrocognition in teams: Predicting processes in complex collaborative contexts. Human Factors, 52, 203–224. https://doi.org/10.1177/0018720810369807
15.
FoxJ.PearceK. E.MassanariA. L.RilesJ. M.SzulcŁ.RanjitY. S.TrevisanF.SorianoC. R. R.VitakJ.AroraP.AhnS. J. (G.)AlperM.GambinoA.GonzalezC.LynchT.WilliamsonL. D.GonzalesA. L. (2021). Open science, closed doors? Countering marginalization through an agenda for ethical, inclusive research in communication. Journal of Communication, 71(5), 764–784. https://doi.org/10.1093/joc/jqab029
16.
GaneshK.LazarA. (2021). The work of workplace disclosure: Invisible chronic conditions and opportunities for design. Proceedings of the ACM on Human-Computer Interaction, 5, CSCW1, 1–26.
GreeneD.BeardN.CleggT.WeightE. (2023). The visible body and the invisible organization: Information asymmetry and college athletics data. Big Data & Society, 10(1), 1–12. https://doi.org/10.1177/20539517231179197
19.
HallK. L.VogelA. L.HuangG. C.SerranoK. J.RiceE. L.TsakraklidesS. P.FioreS. M. (2018). The science of team science: A review of the empirical evidence and research gaps on collaboration in science. American Psychologist, 73(4), 532–548.
20.
KaneA. A.EmichK. (2025). The value of small samples to groups and teams research: Accumulating knowledge across philosophies of science. Group & Organization Management, 50(5–6), 1703–1735. https://doi.org/10.1177/10596011241282703
21.
KaneA. A.PaletzS. B. F.DiepM.HajkowskiA.PorterA. A. (2025). Virtual collaborative analysis: Effects of an entity-based versus a simple AI summarizer. Small Group Research, 56(5), 821–863. https://doi.org/10.1177/10464964251361563
22.
KaneA. A.van SwolL. M. (2022). Harnessing a language analysis perspective to uncover emergent group processes. In DehghaniM.BoydR. L. (Eds.), Handbook of language analysis in psychology (pp. 125–140). Guilford Press.
23.
KeatingC. T.Sowden-CarvalhoS.O’DonoghueH.CookJ. L. (2026). Mismatching expressions: Spatiotemporal and kinematic differences in autistic and non-autistic facial expressions. Autism Research, 19, e70157.
24.
KimR.RobersonL.RussoM.BrigantiP. (2019). Language diversity, nonnative accents, and their consequences at the workplace: Recommendations for individuals, teams, and organizations. Journal of Applied Behavioral Science, 55(1), 73–95. https://doi.org/10.1177/0021886318800997
25.
KimY. J.EngelD.WoolleyA. W.LinJ. Y.-T.McArthurN.MaloneT. W. (2017). What makes a strong team? Using collective intelligence to predict team performance in League of Legends. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW’17) (pp. 2316–2329). ACM Press. http://dx.doi.org/10.1145/2998181.2998185
26.
Lehmann-WillenbrockN.HungH.KeytonJ. (2017). New frontiers in analyzing dynamic group interactions: Bridging social and computer science. Small Group Research, 48(5), 519–531. https://doi.org/10.1177/1046496417718941
27.
MallickR.FlathmannC.DuanW.SchelbleB. G.McNeeseN. J. (2024). What you say vs. what you do: Utilizing positive emotional expressions to relay AI teammate intent within human-AI teams. International Journal of Human-Computer Studies, 192, 103355. https://doi.org/10.1016/j.ijhcs.2024.103355
28.
MannixE.NealeM. A. (2005). What differences make a difference? The promise and reality of diverse teams in organizations. Psychological Science in the Public Interest, 6, 1–2.
29.
MathieuJ. E.GallagherP. T.DomingoM. A.KlockE. A. (2019). Embracing complexity: Reviewing the past decade of team effectiveness research. Annual Review of Organizational Psychology and Organizational Behavior, 6, 17–46.
30.
Miron-SpektorE.ErezM.NavehE. (2011). The effect of conformist and attentive-to-detail members on team innovation: Reconciling the innovation paradox. Academy of Management Journal, 54(4), 740–760.
31.
NarayananA.KapoorS. (2024). AI snake oil: What artificial intelligence can do, what it can’t, and how to tell the difference. Princeton University Press.
32.
NgueajioM. K.WashingtonG. (2022). Hey ASR system! Why aren’t you more inclusive? In: ChenJ. Y. C.FragomeniG.DegenH.NtoaS. (Eds.), HCI International 2022 – Late Breaking Papers: Interacting with eXtended Reality and Artificial Intelligence. HCII 2022. Lecture Notes in Computer Science (vol. 13518). Springer, Cham. https://doi.org/10.1007/978-3-031-21707-4_30
33.
OlsenS. H.CorkS. J.AndersP.PadrónR.PetersonA.StrausserA.JaegerP. T. (2022). The disability tax and the accessibility tax: The extra intellectual, emotional, and technological labor and financial expenditures required of disabled people in a world gone wrong. . .and mostly online. Including Disability, 1, 51–86.
34.
O’NeillT. A.McNeeseN. J.BarronA.SchelbeB. (2022). Human-autonomy teaming: A review and analysis of the empirical literature. Human Factors, 64(5), 904–938. https://doi.org/10.1177/0018720820960865
35.
PaletzS. B. F.DubrowS. (Eds.). (2026). AI in teams. In Series: Research on Managing Groups and Teams. Emerald Publishing.
36.
PaletzS. B. F.LitmanD.KaruzisV.JonesK. M.RahimiZ. (2023) Speaking similarly: Team personality composition and acoustic-prosodic entrainment. Small Group Research, 54(6), 860–898. https://doi.org/10.1177/10464964231178748
37.
PaletzS. B. F.PavisicI.Miron-SpektorE.LinC.-C. (2018). Diversity in creative teams: Reaching across cultures and disciplines. In KwanL. Y.-Y.LiouS.LeungA. K.-Y. (Eds.), Handbook of culture and creativity: Basic processes and applied innovations (pp. 169–206). Oxford University Press.
38.
PraslovaL. (2024) The canary code: A guide to neurodiversity, dignity, and intersectional belonging at work. Berrett-Koehler Publishers.
39.
SeboS.StollB.ScassellatiB.JungM. F. (2020). Robots in groups and teams: A literature review. Proceedings of the ACM on Human-Computer Interaction 4 (CSCW2), 1–36. Article 176. https://doi.org/10.1145/3415247
40.
ShneidermanB. (2022). Human-centered AI. Oxford University Press.
41.
SieboldC. L.PaletzS. B. F.Reiter-PalmonR.LewisS.MontE. (2025, October). Disability meets modality: A sociotechnical approach to team meetings. Proceedings of the ACM on Human-Computer Interaction, 9(7), CSCW399: 1–24. https://doi.org/10.1145/3757580
42.
StahlG. K.MaznevskiM. L.VoigtA.JonsenK. (2010). Unraveling the effects of cultural diversity in teams: A meta-analysis of research on multicultural work groups. Journal of International Business Studies, 41, 690–709.
43.
TraylorA. M.DinhJ. V.NgL. C.ReyesD. L.ChengS. K.CroitoruN. C.SalasE. (2024). It’s about the process, not the product: A meta-analytic investigation of team demographic diversity and processes. Organizational Psychology Review, 14(3), 478–516. https://doi.org/10.1177/20413866241245312
44.
ValenciaS.HuynhJ.JiangE. Y.WuY.WanT.ZhengZ.AdmoniH.BighamJ. P.PavelA. (2024). COMPA: Using conversation context to achieve common ground in AAC [Conference session]. Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI ‘24). https://doi.org/10.1145/3613904.3642762
45.
VanderheidenG.LazarJ.LazarA.KacorriH.JordanJ. B. (2022). Technology and disability: 50 years of Trace R&D Center contributions and lessons learned. Springer Nature.
46.
van KnippenbergD.De DreuC. K. W.HomanA. C. (2004). Work group diversity and group performance: An integrative model and research agenda. Journal of Applied Psychology, 89(6), 1008–1022. https://doi.org/10.1037/0021-9010.89.6.1008
47.
WildmanJ. L.NguyenD.ThayerA. L.Robbins-RothV. T.CarrollM.CarmodyK.FickeC.AkibM.AddisA. (2024). Trust in human-agent teams: A multilevel perspective and future research agenda. Organizational Psychology Review, 14(3), 373–402. https://doi.org/10.1177/20413866241253278
48.
YadavG. A.BrackenB. K.CookeN. J.DesrochersP.GormanJ. C.GrimmD. A. P.HuangL.KilcullenM.LiM.RojasE.RosenM.ScaliaM. J.WinderA.YinX.DoostE. Z.ZhouS. (2025). Bio-behavioral team dynamics measurement system: Multimodal sensing, dynamical systems modeling, and machine learning pipelines to predict and characterize team performance. Nonlinear Dynamics, Psychology, and Life Sciences, 29(4), 529–552.
