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From General Intelligence to Sustainable Adaptation: A Critical Review of Large-Scale AI Empowering People’s Livelihood

Author

Listed:
  • Jiayi Li

    (Party School of the CPC Central Committee, National Academy of Governance, Beijing 100089, China)

  • Peiying Zhang

    (Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China)

Abstract

The advent of large-scale AI models (LAMs) marks a pivotal shift in technological innovation with profound societal implications. While demonstrating unprecedented potential to enhance human well-being by fostering efficiency and accessibility in critical domains like medicine, agriculture, and education, their rapid deployment presents a double-edged sword. This progress is accompanied by significant, often under-examined, sustainability costs, including large environmental footprints, the risk of exacerbating social inequities via algorithmic bias, and challenges to economic fairness. This paper provides a balanced and critical review of LAMs’ applications across five key livelihood domains, viewed through the lens of sustainability science. We systematically analyze the inherent trade-offs between their socio-economic benefits and their environmental and social costs. We conclude by arguing for a paradigm shift towards ‘Sustainable AI’ and provide actionable, multi-stakeholder recommendations for aligning artificial intelligence with the long-term goals of a more equitable, resilient, and environmentally responsible world.

Suggested Citation

  • Jiayi Li & Peiying Zhang, 2025. "From General Intelligence to Sustainable Adaptation: A Critical Review of Large-Scale AI Empowering People’s Livelihood," Sustainability, MDPI, vol. 17(20), pages 1-26, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:20:p:9051-:d:1769872
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    References listed on IDEAS

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