when human-in-the-loop amplifies the risk of misalignment

Human-in-the-loop (HITL) approaches are commonly proposed to address alignment challenges arising from the use of large language models (LLMs) in ethics oversight. This paper argues that, paradoxically, HITL itself can amplify the risk of misalignment. Using the example of protocol triage in research ethics oversight, I demonstrate how reliance on imperfect proxies (observable stand-ins for ethical principles) creates a fundamental proxy–target gap in ethics use-cases. While human reviewers are intended to supply phenomenological and causal judgments necessary to bridge this gap, their involvement inadvertently introduces new vulnerabilities: hallucination, over-reliance, reward hacking, and sycophancy. Each vulnerability arises directly from the interaction between human feedback signals and model optimization strategies. I outline key mitigation techniques, including retrieval grounding, calibration drills, structured prompting, and adversarial debate, explaining their distinct costs and benefits. Effective HITL oversight therefore demands specialized reviewer competencies. Reviewers must recognize model vulnerabilities, understand mitigation trade-offs, and strategically deploy mitigations to preserve justificational alignment without sacrificing efficiency gains.