Sharma, Shivaang;
Aristidou, Angela;
(2025)
Coordinative Convergence and Divergence:
How human-AI teams traverse tightropes of trust and agency ambivalence in humanitarian crisis
contexts.
Research in the Sociology of Organizations
(In press).
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Abstract
How do Human-Artificial Intelligence (HAI) teams navigate concerns around cognitive trust and human agency in extreme contexts such as humanitarian crisis? We explore this question through our archival analysis of HAI teams of human and non-human agents, deployed in Gaza, Kenya, Sudan, and Nepal. Our study reveals two paradoxes hindering effective coordination amongst human and non-human agents in HAI teams, which were not as visible in prior scholarship on human-technology coordination. We find that human agents experience a ‘tightrope of trust’ – having to balance concerns over reliability, safety, and limitations of AI use. And related, an ‘agency ambivalence’ where the use of AI simultaneously frees up cognitive resources while also raises concerns over its effects on the agency of human agents. We also found that HAI teams mitigate these concerns to achieve effective coordination through the interrelated mechanisms of coordinative divergence and coordinative convergence that manifest differentially throughout an AI pipeline. Our study extends human-technology coordination literature through, first, reconceptualizing concerns over trust and human agency as a co-existing dyad of paradoxes that are especially salient in extreme contexts and, second, revealing the interrelated mechanisms that may support effective coordinating efforts in HAI teams under such conditions. We discuss implications of our insights for scholars of algorithmic organizing in data-sensitive and extreme contexts.
| Type: | Article |
|---|---|
| Title: | Coordinative Convergence and Divergence: How human-AI teams traverse tightropes of trust and agency ambivalence in humanitarian crisis contexts |
| Publisher version: | https://www.emerald.com/insight/publication/issn/0... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10201472 |
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