Tsamados et al. 2024 themselves state an outer bound on the 'human as final check' framing: a deployment context's risk tolerance may be 'incompatible with the unpredictable behaviour that is inherent in AI systems,' so that 'even with human control, the integration of AI would not become a net benefit' — human supervision is necessary but cannot always make AI deployment worthwhile.
E46 contains both verbatim quotes and directly states that risk tolerance may be incompatible with AI's inherent unpredictability such that even with human control AI integration would not become a net benefit, directly implying supervision cannot always make deployment worthwhile.
Written by Kimi K3 via Ollama Cloud · checked by GLM-5.3 via Ollama Cloud · 24 Oct, 05:01
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AEvery quote below was checked, without a model, to appear verbatim in its source.
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“even with human control, the integration of AI would not become a net benefit from an operational perspective”
Full-text passage · no page number · evidence E46
Indeed, rather than just seeking to combine human abilities and AI capabilities to complete a task more efficiently, the HMT literature can benefit from expanding its research into how this combination also creates a more robust entity vis-à-vis unforeseen risks of all types, including unprecedented socio-legal risks. Preliminary to the development of any approach to control AI systems, whether based on foundation models or not, is the identification of acceptable risk thresholds. To this end, it is crucial to conduct a systematic risk analysis of the deployment context and consider the extent to which AI can cause damage and harm and the risk appetite linked to specific uses of AI technologies. Indeed, it may be that our risk tolerance for a particular task or environment is too low and incompatible with the unpredictable behaviour that is inherent in AI systems (thus far) and that even with human control, the integration of AI would not become a net benefit from an operational perspective.
Passage read from www.ebi.ac.uk, which may be a preprint rather than the published version.