ABFER 13th ANNUAL CONFERENCE
The call for papers is now open for the ABFER 13th Annual Conference. The conference will be held on 18-21 May 2026 in Singapore
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12th ASIAN MONETARY POLICY FORUM
The 12th AMPF commenced on 22 May 2025 with a joint dinner with ABFER, followed by the forum on 23 May 2025 at Conrad Singapore Orchard
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CALL FOR POSTERS 2025
The Call for Posters is now closed. Selected papers will be informed by end of February. The poster sessions will be held on 20 and 21 May 2025 at the ABFER 12th Annual Conference.
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CAPITAL MARKET DEVELOPMENT: CHINA AND ASIA
Webinar series on every third Thursday of the month
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INDUSTRY OUTREACH PANEL
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  • ABFER 13th ANNUAL CONFERENCE
  • 12th ASIAN MONETARY POLICY FORUM
  • CALL FOR POSTERS 2025
  • CAPITAL MARKET DEVELOPMENT: CHINA AND ASIA
  • INDUSTRY OUTREACH PANEL

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4265 SUBMITTED Papers submitted to
Annual Conference
11415 AUTHORS Representing number
of authors
684 PRESENTED Papers presented at
Annual Conferences
218 JOURNALS Papers published in
significant journals
5200 PARTICIPANTS Participants at
Annual Conferences

Webinar Series

 

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

Developing AI technology requires data. In many domains, government data far exceeds 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. The authors argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. They gather comprehensive information on firms and public security procurement contracts in China's facial recognition AI industry. The authors quantify the data accessible through contracts by measuring public security agencies' capacity to collect surveillance video. Using a triple-differences strategy, the authors find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Their analysis indicates a contribution of government data to the rise of China's facial recognition AI firms, and suggests that states’ data collection and provision policies could shape AI innovation.

03
Nov
2021
Wednesday

Session Chair: Zheng (Michael) SONG
Professor at the Department of Economics, Chinese University of Hong Kong



Updated 8 Nov 2021

Speakers

Session Format

Each session lasts for 1 hour 10 minutes (25 minutes for the author, 25 minutes for the discussion and 20 minutes for participants' Q&A). Sessions will be recorded and posted on ABFER's web, except in cases where speakers or discussants request us not to.

Registration

Registration has closed. Please visit the main page for details on next webinar.