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Position: AI Safety Should Prioritize the Future of Work
EconomicsProceedings of the 42nd International Conference on Machine Learning (ICML 2025), PMLR 267

Position: AI Safety Should Prioritize the Future of Work

S. Hazra, B. P. Majumder, et al.

Current AI safety efforts often focus on content filtering and existential risks, but this research conducted by Sanchaita Hazra, Bodhisattwa Prasad Majumder, and Tuhin Chakrabarty highlights a neglected threat: the transformation of work and widening inequality. The paper calls for pro-worker global governance, collective licensing, and fair compensation for data used in training models to enable a just transition to meaningful labor with human agency.... show more
Abstract
Current efforts in AI safety prioritize filtering harmful content, preventing manipulation of human behavior, and eliminating existential risks in cybersecurity or biosecurity. While pressing, this narrow focus overlooks critical human-centric considerations that shape the long-term trajectory of a society. In this position paper, we identify the risks of overlooking the impact of AI on the future of work and recommend comprehensive transition support towards the evolution of meaningful labor with human agency. Through the lens of economic theories, we highlight the intertemporal impacts of AI on human livelihood and the structural changes in labor markets that exacerbate income inequality. Additionally, the closed-source approach of major stakeholders in AI development resembles rent-seeking behavior through exploiting resources, breeding mediocrity in creative labor, and monopolizing innovation. To address this, we argue in favor of a robust international copyright anatomy supported by implementing collective licensing that ensures fair compensation mechanisms for using data to train AI models. We strongly recommend a pro-worker framework of global AI governance to enhance shared prosperity and economic justice while reducing technical debt.
Publisher
Proceedings of the 42nd International Conference on Machine Learning (ICML 2025), PMLR 267
Published On
Authors
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty
Tags
AI safetyfuture of worklabor marketsincome inequalitycollective licensingcopyright governancepro-worker AI governance
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