Teachers retain ultimate control over AI systems because professional responsibility cannot be delegated¶

Claim · All claims
Evidence · 1 study · qualitative r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Teachers maintain authority boundaries under which they retain ultimate control because professional responsibility cannot be delegated to AI. → Reichert 2026

Evidence¶

Reichert 2026¶

Reichert, H., Briceno, D., Tabarsi, B., Barnes, T. (2026). Human-Centered Design of LLM-Powered Educational Chatbots: A Study with Secondary Teachers. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2026. LNCS vol 16746. Springer, Cham. https://doi.org/10.1007/978-3-032-31048-4_32

q2 · i? · qualitative · r2

Qualitative finding from the study's analysis of how six secondary teachers conceptualized control and delegation in chatbot design; teachers drew authority boundaries retaining ultimate control. No effect size is reported for this qualitative theme.

"authority boundaries, in which teachers retain ultimate control because professional responsibility cannot be delegated"

Discussion¶

Related Claims¶

• Secondary teachers conceptualize LLM-powered chatbots as bounded experts operating under human supervision — a broader claim this one bears on
• AI-assisted ideation was conditionally acceptable when researchers retained decision-making authority, but problematic when it displaced conceptual labour — a broader claim this one bears on
• Because learning theories are not operationalized into system structures, pedagogical use of digital resources is delegated to teachers' judgment at the moment of use — related
• Judgement-bearing assistance is the central analytic pivot: delegating evaluation of quality and correctness is normatively more demanding than instrumental assistance — a broader claim this one bears on
• Teachers sought to preserve student thinking and authorship by bounding chatbot answer-giving and maintaining teacher control over scope — a narrower finding that bears on this claim
• High-level feedback on reasoning and synthesis should remain a human responsibility for the foreseeable future — possibly the same claim (merge candidate)
• Authority over assistance boundaries is highly centralized in system logic in LLM-based programming support systems — reports the opposite