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Five-level diagnostic taxonomy of human–AI teaming defined by observable affordances

Research Method · All research methods
Evidence · 2 claims (2 for) · 4 studies (2 causal, 2 review), q2–q4 · 0 of 4 report an effect size · 1 claim rests on one study

Description

The chapter proposes a diagnostic taxonomy of human–AI teaming with five levels: transactional, situational, operational, praxical, and synergistic. Each level 'introduces one additional affordance over the level beneath it', and 'the classification is functional and is intended to be coded from observable behaviour' such as whether the system surfaces state, accepts governance, revises durably from feedback, or co-reasons. Interaction types are querying, monitoring, governing, adapting, and co-reasoning; diagnosis proceeds top-down, classifying a system at the highest threshold it meets.

Accounts

  • Five-level diagnostic taxonomy of human–AI teaming defined by observable affordances: The chapter proposes a diagnostic taxonomy of human–AI teaming with five levels: transactional, situational, operational, praxical, and synergistic. Each level 'introduces one additional affordance over the level beneath it', and 'the classification is functional and is intended to be coded from observable behaviour' such as whether the system surfaces state, accepts governance, revises durably from feedback, or co-reasons. Interaction types are querying, monitoring, governing, adapting, and co-reasoning; diagnosis proceeds top-down, classifying a system at the highest threshold it meets. (Mutlu Cukurova (2026))
  • Five levels of teacher-AI teaming: transactional, situational, operational, praxical and synergistic: The chapter proposes an orthogonal conceptual framework of teacher-AI teaming focused on information flows, decisions and actions shared between teacher and AI, grounded in distributed cognition. The authors state: "we propose (1) transactional, (2) situational, (3) operational, (4) praxical and (5) synergistic levels of teaming, as shown in Fig. 8.1." Levels run from minimal request-response interactions to mutual co-adaptation, and the framework is validated against a systematic review of teacher-facing AI studies. The authors caution the levels "need not always follow a progressive ordered hierarchy" and that improving teaming level does not guarantee improving teaching performance. (Mutlu Cukurova et al. (2025))

Claims

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Key Sources

  • Mutlu Cukurova. (2026). What do you mean by 'human–AI collaboration'? Prerequisite functions and the affordances needed to achieve it. Submitted to the Handbook of AI and the Future of Education. https://orcid.org/0000-0001-5843-4854
  • Mutlu Cukurova, Wannapon Suraworachet, Qi Zhou, and Sahan Bulathwela. (2025). Towards Synergistic Teacher-AI Interactions with Generative Artificial Intelligence. https://arxiv.org/abs/2511.19580
Page metadata
Field Value
type research-method
id five-level-diagnostic-taxonomy-of-humanai-teaming-defined-by-observable-affordances
title Five-level diagnostic taxonomy of human–AI teaming defined by observable affordances
description The chapter proposes a diagnostic taxonomy of human–AI teaming with five levels: transactional, situational, operational, praxical, and synergistic.
status review
generated by process:settle-candidates on 2026-10-11
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