Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings

新兴技术 新兴市场 数据科学 比例(比率) 计算机科学 秩(图论) 人工智能 经济 地理 数学 地图学 宏观经济学 组合数学
作者
Avi Goldfarb,Bledi Taska,Florenta Teodoridis
出处
期刊:Research Policy [Elsevier BV]
卷期号:52 (1): 104653-104653 被引量:183
标识
DOI:10.1016/j.respol.2022.104653
摘要

Many emerging technologies have aspects of General Purpose Technologies (GPTs). However, true GPTs are rare and hold potential for large-scale economic impact. Thus, it is important for policymakers and managers to assess which emerging technologies are likely GPTs. We describe an approach that uses data from online job ads to rank emerging technologies on their GPT likelihood. The approach suggests which technologies are likely to have a broader economic impact, and which are likely to remain useful but narrower enabling technologies. Our approach has at least 5 years predictive power distinct from prevailing patent-based methods of identifying GPTs. We apply our approach to 21 different emerging technologies, and find that a cluster of technologies comprised of machine learning and related data science technologies is relatively likely to be a GPT.
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
刚刚
CodeCraft应助科研通管家采纳,获得10
刚刚
阔达的海完成签到,获得积分10
刚刚
刚刚
爆米花应助科研通管家采纳,获得10
刚刚
汉堡包应助科研通管家采纳,获得10
刚刚
cdercder应助科研通管家采纳,获得30
1秒前
上官若男应助科研通管家采纳,获得10
1秒前
jyzxzr完成签到,获得积分10
1秒前
英俊的铭应助科研通管家采纳,获得10
1秒前
Akim应助科研通管家采纳,获得10
1秒前
bkagyin应助科研通管家采纳,获得10
1秒前
CipherSage应助科研通管家采纳,获得10
1秒前
小二郎应助科研通管家采纳,获得10
1秒前
英姑应助科研通管家采纳,获得10
1秒前
斯文败类应助科研通管家采纳,获得10
1秒前
852应助科研通管家采纳,获得10
1秒前
酷波er应助科研通管家采纳,获得10
1秒前
汉堡包应助科研通管家采纳,获得10
1秒前
Orange应助科研通管家采纳,获得10
1秒前
充电宝应助科研通管家采纳,获得10
1秒前
脑洞疼应助科研通管家采纳,获得10
2秒前
JamesPei应助科研通管家采纳,获得10
2秒前
华仔应助科研通管家采纳,获得10
2秒前
Orange应助科研通管家采纳,获得10
2秒前
ZD发布了新的文献求助10
2秒前
XYN1完成签到,获得积分10
2秒前
xxxx完成签到,获得积分10
2秒前
2秒前
2秒前
CipherSage应助cancan采纳,获得10
3秒前
打打应助尺八采纳,获得10
3秒前
QYN完成签到,获得积分10
3秒前
李珂完成签到,获得积分10
3秒前
3秒前
稳重的小之完成签到,获得积分10
4秒前
威武爆米花完成签到,获得积分10
4秒前
赘婿应助Larluli采纳,获得10
4秒前
Ortho Wang完成签到,获得积分10
5秒前
晚风完成签到,获得积分20
5秒前
高分求助中
Adhesion Science: Principles & Practice 1234
Signals, Systems, and Signal Processing 610
Burger's Medicinal Chemistry and Drug Discovery 400
A Step-by-Step Guide to Qualitative Data Coding 2nd Edition 400
Impact of Storage Orientation and Duration on Prefilled Syringe Performance: Break-Loose and Glide Forces, and Injection Time Across Multiple Time Points 360
Programming for Chemical Engineers Using C, C++, and MATLAB 300
Upland Kenya wild flowers and ferns: a flora of the flowers, ferns, grasses, and sedges of highland Kenya 300
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 6665317
求助须知:如何正确求助?哪些是违规求助? 8414884
关于积分的说明 17988362
捐赠科研通 5871027
什么是DOI,文献DOI怎么找? 2975707
邀请新用户注册赠送积分活动 1951599
关于科研通互助平台的介绍 1878380