Artificial Intelligence, Automation and Work: A Review

Newjin Bro P. J, Gini R
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Abstract

This paper summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment. Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace labor in tasks that it used to perform. This displacement effect tends to reduce the demand for labor and wages. But it is counteracted by a productivity effect, resulting from the cost savings generated by automation, which increase the demand for labor in non-automated tasks. The productivity effect is complemented by additional capital accumulation and the deepening of automation (improvements of existing machinery), both of which further increase the demand for labor. These countervailing effects are incomplete. Even when they are strong, automation in- creases output per worker more than wages and reduce the share of labor in national income. The more powerful countervailing force against automation is the creation of new labour-intensive tasks, which reinstates labor in new activities and tends to increase the labor share to counterbalance the impact of automation. Our framework also highlights the constraints and imperfections that slow down the adjustment of the economy and the labor market to automation and weaken the resulting productivity gains from this transformation: a mismatch between the skill requirements of new technologies, and the possibility that automation is being introduced at an excessive rate, possibly at the expense of other productivity-enhancing technologies. In this paper investigating various methods used in the existing work for the Artificial Intelligence.
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人工智能、自动化与工作:综述
本文总结了一个研究自动化和人工智能对劳动力、工资和就业需求影响的框架。我们的基于任务的框架强调了自动化带来的取代效应,因为机器和人工智能取代了过去由人工执行的任务。这种替代效应往往会降低对劳动力和工资的需求。但是,由于自动化所产生的成本节约,增加了非自动化任务对劳动力的需求,从而抵消了生产率的影响。生产力效应由额外的资本积累和自动化的深化(现有机器的改进)来补充,两者都进一步增加了对劳动力的需求。这些抵消效应是不完全的。即使它们很强大,自动化对每个工人产出的增加也超过了工资的增加,并降低了劳动在国民收入中的份额。更强大的对抗自动化的力量是创造新的劳动密集型任务,这使劳动力在新的活动中恢复,并倾向于增加劳动力份额,以抵消自动化的影响。我们的框架还强调了减缓经济和劳动力市场向自动化调整的限制和不完善之处,并削弱了这种转变所带来的生产力收益:新技术的技能要求之间的不匹配,以及自动化以过高的速度引入的可能性,可能以牺牲其他提高生产力的技术为代价。本文对现有人工智能工作中使用的各种方法进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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