Review of Economic Studies · 2022 · Martin Beraja、David Y. Yang、Noam Yuchtman
中文摘要
人工智能（AI）技术的开发需要数据。在许多领域，政府数据的规模和范围远超私营部门收集的数据，而人工智能企业在为国家提供服务时往往能够获取此类数据。我们认为，这种数据获取可以促进商业人工智能创新，部分原因在于数据和训练后的算法可在政府用途与商业用途之间共享。我们收集了中国人脸识别人工智能行业企业及公共安全采购合同的全面信息。通过衡量公共安全机构收集监控视频的能力，我们量化了企业可通过合同获取的数据。采用三重差分策略，我们发现，与数据稀缺型合同相比，数据丰富型合同会促使中标企业开发出显著且大幅更多的商业人工智能软件。我们的分析表明，政府数据推动了中国人脸识别人工智能企业的崛起，并且国家的数据收集与提供政策可能会塑造人工智能创新。
Abstract
Abstract 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.