Data-intensive Innovation and the State: Evidence from AI Firms in China

被引:59
作者
Beraja, Martin [1 ,2 ]
Yang, David Y. [2 ,3 ,4 ]
Yuchtman, Noam [5 ,6 ,7 ]
机构
[1] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[2] NBER, Cambridge, MA 02138 USA
[3] Harvard Univ, Cambridge, MA 02138 USA
[4] CIFAR, Toronto, ON, Canada
[5] LSE, London, England
[6] CEPR, London, England
[7] CESifo, Munich, Germany
关键词
Data; Innovation; Artificial intelligence; China; Innovation policy; Privacy; Surveillance; O30; P00; E00; L5; L63; O25; O40; SELECTION; DEMAND; REFORM;
D O I
10.1093/restud/rdac056
中图分类号
F [经济];
学科分类号
02 ;
摘要
Developing artificial intelligence (AI) technology requires data. In many domains, government data far exceed in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China's facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies' capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis suggests a contribution of government data to the rise of China's facial recognition AI firms, and that states' data collection and provision policies could shape AI innovation.
引用
收藏
页码:1701 / 1723
页数:23
相关论文
共 40 条
[1]   The wrong kind of AI? Artificial intelligence and the future of labour demand [J].
Acemoglu, Daron ;
Restrepo, Pascual .
CAMBRIDGE JOURNAL OF REGIONS ECONOMY AND SOCIETY, 2020, 13 (01) :25-35
[2]  
Aghion P., 2017, Artificial Intelligence and Economic Growth, DOI [10.3386/w23928, DOI 10.3386/W23928, 10.7208/chicago/9780226613475.003, DOI 10.7208/CHICAGO/9780226613475.003]
[3]  
AGRAWAL A., 2019, The Economics of Artificial Intelligence: An Agenda
[4]  
Agrawal A., 2018, Prediction machines: the simple economics of artificial intelligence
[5]  
Alic JohnA., 1992, Beyond Spinoff: Military and Commercial Technologies in a Changing World
[6]   Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects [J].
Anderson, Michael L. .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2008, 103 (484) :1481-1495
[7]  
Aridor G., 2020, The economic consequences of data privacy regulation: Empirical evidence from gdpr
[8]  
Azoulay P., 2019, Innovation policy and the economy, V19, P69, DOI DOI 10.1086/699933
[9]   Special Deals with Chinese Characteristics [J].
Bai, Chong-en ;
Hsieh, Chang-Tai ;
Song, Zheng .
NBER MACROECONOMICS ANNUAL, 2020, 34 (01) :341-379
[10]   Are Ideas Getting Harder to Find? [J].
Bloom, Nicholas ;
Jones, Charles, I ;
Van Reenen, John ;
Webb, Michael .
AMERICAN ECONOMIC REVIEW, 2020, 110 (04) :1104-1144