BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CMSA - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CMSA
X-ORIGINAL-URL:https://cmsa.fas.harvard.edu
X-WR-CALDESC:Events for CMSA
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20180311T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20181104T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190426T143000
DTEND;TZID=America/New_York:20200426T153000
DTSTAMP:20260502T184244
CREATED:20240212T100818Z
LAST-MODIFIED:20240221T092817Z
UID:10001958-1556289000-1587915000@cmsa.fas.harvard.edu
SUMMARY:4/26/2019 General Relativity Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-26-2019-general-relativity-seminar/
CATEGORIES:General Relativity Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200129T163000
DTEND;TZID=America/New_York:20200129T173000
DTSTAMP:20260502T184244
CREATED:20240212T090021Z
LAST-MODIFIED:20240507T203431Z
UID:10001898-1580315400-1580319000@cmsa.fas.harvard.edu
SUMMARY:Data-intensive Innovation and the State: Evidence from AI Firms in China
DESCRIPTION:Speaker: David Yang (Harvard)\n\nTitle: Data–intensive Innovation and the State: Evidence from AI Firms in China\n\nAbstract: Data–intensive technologies such as AI may reshape the modern world. We propose that two features of data interact to shape innovation in data–intensive economies: first\, states are key collectors and repositories of data; second\, data is a non-rival input in innovation. We document the importance of state-collected data for innovation using comprehensive data on Chinese facial recognition AI firms and government contracts. Firms produce more commercial software and patents\, particularly data–intensive ones\, after receiving government public security contracts. Moreover\, effects are largest when contracts provide more data. We then build a directed technical change model to study the state’s role in three applications: autocracies demanding AI for surveillance purposes\, data-driven industrial policy\, and data regulation due to privacy concerns. When the degree of non-rivalry is as strong as our empirical evidence suggests\, the state’s collection and processing of data can shape the direction of innovation and growth of data–intensive economies.
URL:https://cmsa.fas.harvard.edu/event/1-29-2020-colloquium/
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Colloquium-01.29.20-1.png
END:VEVENT
END:VCALENDAR