The simple macroeconomics of AI

生产力 全要素生产率 背景(考古学) 经济 任务(项目管理) 不平等 计量经济学 骨料(复合) 宏观经济学 劳动经济学 古生物学 复合材料 管理 材料科学 数学分析 生物 数学
作者
Daron Acemoğlu
出处
期刊:Economic Policy [Oxford University Press]
卷期号:40 (121): 13-58 被引量:134
标识
DOI:10.1093/epolic/eiae042
摘要

SUMMARY This paper evaluates claims about the large macroeconomic implications of new advances in Artificial intelligence (AI). It starts from a task-based model of AI’s effects, working through automation and task complementarities. So long as AI’s microeconomic effects are driven by cost savings/productivity improvements at the task level, its macroeconomic consequences will be given by a version of Hulten’s theorem: Gross Domestic Product (GDP) and aggregate productivity gains can be estimated by what fraction of tasks are impacted and average task-level cost savings. Using existing estimates on exposure to AI and productivity improvements at the task level, these macroeconomic effects appear non-trivial but modest – no more than a 0.66% increase in total factor productivity (TFP) over 10 years. The paper then argues that even these estimates could be exaggerated, because early evidence is from easy-to-learn tasks, whereas some of the future effects will come from hard-to-learn tasks, where there are many context-dependent factors affecting decision-making and no objective outcome measures from which to learn successful performance. Consequently, predicted TFP gains over the next 10 years are even more modest and are predicted to be less than 0.53%. I also explore AI’s wage and inequality effects. I show theoretically that even when AI improves the productivity of low-skill workers in certain tasks (without creating new tasks for them), this may increase rather than reduce inequality. Empirically, I find that AI advances are unlikely to increase inequality as much as previous automation technologies because their impact is more equally distributed across demographic groups, but there is also no evidence that AI will reduce labour income inequality. Instead, AI is predicted to widen the gap between capital and labour income. Finally, some of the new tasks created by AI may have negative social value (such as the design of algorithms for online manipulation), and I discuss how to incorporate the macroeconomic effects of new tasks that may have negative social value.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
123完成签到,获得积分10
1秒前
2秒前
bkagyin应助苏silence采纳,获得10
5秒前
柚子完成签到 ,获得积分10
5秒前
6秒前
hokin33发布了新的文献求助10
7秒前
乐观的皮卡丘完成签到,获得积分10
8秒前
大模型应助Sunday采纳,获得30
9秒前
颜开发布了新的文献求助10
10秒前
酷波er应助drawf采纳,获得10
10秒前
领导范儿应助LY采纳,获得10
13秒前
15秒前
16秒前
16秒前
Eureka完成签到,获得积分10
16秒前
hokin33完成签到,获得积分10
16秒前
爱学习的YY完成签到 ,获得积分10
17秒前
17秒前
Eureka发布了新的文献求助10
19秒前
AllRightReserved应助樊夔采纳,获得30
19秒前
罗柠七完成签到,获得积分20
20秒前
晰默发布了新的文献求助10
20秒前
温柔寒梅完成签到 ,获得积分10
20秒前
orixero应助Bigwang采纳,获得10
21秒前
23秒前
所所应助Lipuer采纳,获得10
23秒前
樟木头发布了新的文献求助10
23秒前
打打应助Vodka采纳,获得10
25秒前
深情安青应助Chow采纳,获得10
27秒前
yptian2002完成签到,获得积分10
28秒前
pups发布了新的文献求助10
28秒前
嘉熙完成签到,获得积分10
30秒前
小鹿5460应助科研通管家采纳,获得10
31秒前
天天快乐应助科研通管家采纳,获得10
31秒前
爆米花应助科研通管家采纳,获得10
31秒前
华仔应助科研通管家采纳,获得10
31秒前
31秒前
情怀应助科研通管家采纳,获得10
32秒前
彭于晏应助科研通管家采纳,获得10
32秒前
Orange应助科研通管家采纳,获得10
32秒前
高分求助中
The Graphene Handbook (2019 Edition) 800
Signals, Systems, and Signal Processing 610
IEST-RP-CC018: Cleanroom Cleaning and Sanitization: Operating and Monitoring Procedures 600
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
久松真一著作集〈第5巻〉禅と芸術 500
Fundamentals of Modern Mathematics: A Practical Review (Dover Books on Mathematics) 500
Cold War Transcended: Australia's China Policy, 1949-1990 470
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6598743
求助须知:如何正确求助?哪些是违规求助? 8368192
关于积分的说明 17911560
捐赠科研通 5752822
什么是DOI,文献DOI怎么找? 2953823
邀请新用户注册赠送积分活动 1929064
关于科研通互助平台的介绍 1823914