arXiv 2407.015452024-07cs.CYcs.AIecon.GNq-fin.EC

在史密斯“看不见的手”的阴影下：智能时代的经济稳定与社会福祉风险

In the Shadow of Smith`s Invisible Hand: Risks to Economic Stability and Social Wellbeing in the Age of Intelligence

Brain and Mind Centre, University of Sydney, Camperdown, Australia（悉尼大学脑与心灵中心）；Mental Wealth Initiative, University of Sydney, Camperdown, Australia（悉尼大学心理财富倡议）；Computer Simulation & Advanced Research Technologies (CSART), Sydney, Australia（悉尼计算机模拟与先进研究技术）；Santa Fe Institute, Santa Fe, New Mexico, USA（圣菲研究所）；School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, Australia（西澳大学计算机、数据与数学科学学院）；Baker Institute for Public Policy, Rice University, Houston, Texas, USA（赖斯大学贝克公共政策研究所）；Meadows Mental Health Policy Institute, Dallas, Texas, USA（达拉斯心理健康政策研究所）；University of Technology Sydney, Broadway, Sydney, Australia（悉尼技术大学）；Visiting Professor in Practice, London School of Economics Grantham Institute, London, UK（伦敦经济学院格兰塔姆研究所访问教授）；Swiss Tropical and Public Health Institute & University of Basel, Switzerland（瑞士热带与公共卫生研究所及巴塞尔大学）；Business School, University of Sydney, Sydney, Australia（悉尼大学商学院）

Jo-An Occhipinti, William Hynes, Ante Prodan, Harris A. Eyre, Roy Green, Sharan Burrow, Marcel Tanner, John Buchanan, Goran Ujdur, Frederic Destrebecq, Christin… 展开作者

Jo-An Occhipinti, William Hynes, Ante Prodan, Harris A. Eyre, Roy Green, Sharan Burrow, Marcel Tanner, John Buchanan, Goran Ujdur, Frederic Destrebecq, Christine Song, Steven Carnevale, Ian B. Hickie, Mark Heffernan

备注：: 10 pages, 5 figures, 1 table, an Appendix

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AI总结：

本文通过系统动力学模型研究生成式AI资本深化对就业与消费的影响，发现即使温和的AI资本替代也可能显著加剧劳动力利用不足并降低收入与消费，强调需政府干预以保障经济稳定和社会福祉。

摘要：

工作对社会繁荣和心理健康至关重要，它提供经济安全、身份认同、人生目标和社会融入。生成式人工智能（AI）的出现引发了关于工作岗位被取代的激烈讨论。一些人认为，许多新的工作和行业将会出现以抵消这种取代，而另一些人则预见经济生产率将与人类投入广泛脱钩，从而以前所未有的规模威胁就业。本研究探讨了这两种情况可能同时成立的条件，并考察了一种自我强化的衰退压力循环的可能性，这种循环将需要持续的政府干预来维持就业保障和经济稳定。研究开发了一个系统动力学模型，对AI资本深化对经济中劳动力利用不足和需求的影响进行事前分析。结果表明，即使AI资本与劳动力之比温和上升，到2050年代中期，劳动力利用不足也可能增加到当前水平的两倍，人均可支配收入下降26%（95%区间，20.6% - 31.8%），消费指数下降21%（95%区间，13.6% - 28.3%）。为了防止因估计的利用不足增加而导致人均可支配收入下降，新工作岗位创造率至少需要提高10.8倍。结果证明了存在一个AI资本与劳动力之比阈值的可行性，超过该阈值后，即使很高的新工作岗位创造率也无法阻止消费下降。这一精确阈值将因经济体而异，凸显了针对具体情境开展实证研究的紧迫性。本研究强调，政府、公民组织和企业需要共同努力，确保向AI主导型经济平稳过渡，以维护各国的“心智财富”。

英文摘要：

Work is fundamental to societal prosperity and mental health, providing financial security, identity, purpose, and social integration. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupling of economic productivity from human input threatening jobs on an unprecedented scale. This study explores the conditions under which both may be true and examines the potential for a self-reinforcing cycle of recessionary pressures that would necessitate sustained government intervention to maintain job security and economic stability. A system dynamics model was developed to undertake ex ante analysis of the effect of AI-capital deepening on labour underutilisation and demand in the economy. Results indicate that even a moderate increase in the AI-capital-to-labour ratio could increase labour underutilisation to double its current level, decrease per capita disposable income by 26% (95% interval, 20.6% - 31.8%), and decrease the consumption index by 21% (95% interval, 13.6% - 28.3%) by mid-2050. To prevent a reduction in per capita disposable income due to the estimated increase in underutilization, at least a 10.8-fold increase in the new job creation rate would be necessary. Results demonstrate the feasibility of an AI-capital- to-labour ratio threshold beyond which even high rates of new job creation cannot prevent declines in consumption. The precise threshold will vary across economies, emphasizing the urgent need for empirical research tailored to specific contexts. This study underscores the need for governments, civic organisations, and business to work together to ensure a smooth transition to an AI- dominated economy to safeguard the Mental Wealth of nations.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。