Skip to content

The structural corruption of human-in-the-loop: how AI competence undermines its own safety architecture

Jul 2026 · AI and Ethics · Vol 6 · 1 citation · 24 references
Computer Science

TL;DR

The Bloom-Delegation Ladder is introduced as a framework for mapping which cognitive capacities have been delegated to AI systems and which remain as the basis for human oversight, and demonstrates that HITL, absent structural intervention, tends to transition from a guarantee of safety to an illusion of safety.

View source

Similar papers

Sep 2026

Calculated inefficiency: sustaining human supervisory competence as an ethical design objective for hybrid human-AI systems

The construct of calculated inefficiency is developed, defined as the structural property of a hybrid information system in which human interventions in automatable processes are maintained at levels above what pure efficiency optimisation would select, regardless of whether that maintenance was deliberately architecte...

Mohamed El Louadi, Maher Kallel · 0 citations
Jul 2026

The Human-AI Substitution Principle: When will you be replaced by AI in your organization?

The HAT model identifies structural conditions under which middle-management roles exhibit elevated vulnerability to automation, and shows that the vulnerability of highly skilled workers depends on a skill threshold shaped by organizational depth, baseline costs, and risk differentials.

Bonny Banerjee, Shreya Singh · 0 citations
Open access Sep 2026

The paradox of efficiency: institutional interfaces, residuals, and the erosion of innovation drivers in AI-augmented organizations

The institutional interface is introduced as a meso-level analytical lens for examining how specific configurations of AI design choices, human–AI interaction protocols, and organizational norms produce systematic biases, and the concept of residuals is introduced to capture the cognitive, behavioral, and value-laden e...

Tian-Yuan Yang · 0 citations
Preprint Aug 2026

The Benchmark Trap: Structures of Power and Injustice in AI Evaluations

It is argued that current benchmarking practices may perpetuate systematic harms affecting various actors in AI research, aligning with four of Iris Marion Young's theories of oppression and structural injustice.

Jason Branford, Angelie Kraft · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.