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

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...

The authority gap: why meaningful human control fails at the tier where it is signed

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

Artificial Intelligence (AI) is rapidly transforming organizations, raising a fundamental organizational and economic question: when will a human employee be replaced by AI? We present an analytical model for studying Human--AI Task Allocation (HAT) in hierarchical organizations. A central feature of the HAT model is t...

Shifting the Unit of Safety: From Model to System in the Generative and Agentic Era

For a decade, responsible AI at internet scale rested on a reassuring assumption: that risk lives primarily in a model, it is a unit you can isolate, and that privacy, fairness and safety is therefore something you certify at model level, before launch. At LinkedIn, where AI shapes access to jobs and economic opportuni...

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

As artificial intelligence (AI) becomes deeply embedded in organizational cognition and decision-making, a profound paradox emerges: AI significantly enhances operational efficiency while systematically eroding the generation and retention of innovation drivers. This study introduces the institutional interface as a me...

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.