A Prospective Macroergonomic Framework to Mitigate Deskilling and Cognitive Load in Advanced-AI Services

Aldi Adi Pratama

Authors

Aldi Adi Pratama Universitas Indonesia

Keywords:

Cognitive Deskilling, Friction-by-Design, Macroergonomic Work System Design (MWSD), Sociotechnical Systems, Superintelligence

Abstract

Advanced artificial intelligence (AI) may reshape knowledge-intensive service work by increasing reliance on automated judgment and the demand to verify AI-generated outputs. This prospective conceptual study examines potential risks of cognitive deskilling and verification-related cognitive load without assuming that artificial superintelligence (ASI) currently exists. Using Macroergonomic Analysis and Design (MEAD), Sociotechnical Systems Theory, and a structured narrative synthesis of selected scholarly and policy documents from the International Labour Organization, the International Organization for Standardization, and the World Economic Forum, the study proposes a Macroergonomic Work System Design (MWSD) framework. The framework connects organizational governance (performance indicators and human accountability), interface design (calibrated friction and uncertainty cues), and operational practices (unassisted reasoning exercises and fatigue management). An intervention crosswalk identifies potential risk mechanisms, hypothesized outcomes, and candidate indicators for future evaluation. These interventions remain design propositions rather than empirically demonstrated solutions; suggested operating thresholds are illustrative and require context-specific calibration. Further studies should assess feasibility, unintended workload effects, and performance outcomes across knowledge-intensive service settings.

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