MSGID: 1:317/3 64b0cf83   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    How an 'AI-tocracy' emerges    
      
     Date:   
         July 13, 2023   
     Source:   
         Massachusetts Institute of Technology   
     Summary:   
         Research finds 'AI-tocracy,' China's increased investments in   
         AI-driven facial-recognition technology, both help the regime   
         repress dissent and may drive the technology forward.   
      
      
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   Many scholars, analysts, and other observers have suggested that   
   resistance to innovation is an Achilles' heel of authoritarian   
   regimes. Such governments can fail to keep up with technological changes   
   that help their opponents; they may also, by stifling rights, inhibit   
   innovative economic activity and weaken the long-term condition of   
   the country.   
      
   But a new study co-led by an MIT professor suggests something quite   
   different.   
      
   In China, the research finds, the government has increasingly deployed   
   AI- driven facial-recognition technology to suppress dissent; has been   
   successful at limiting protest; and in the process, has spurred the   
   development of better AI-based facial-recognition tools and other forms   
   of software.   
      
   "What we found is that in regions of China where there is more unrest,   
   that leads to greater government procurement of facial-recognition   
   AI, subsequently, by local government units such as municipal police   
   departments," says MIT economist Martin Beraja, who is co-author of a   
   new paper detailing the findings.   
      
   What follows, as the paper notes, is that "AI innovation entrenches   
   the regime, and the regime's investment in AI for political control   
   stimulates further frontier innovation."  The scholars call this state   
   of affairs an "AI-tocracy," describing the connected cycle in which   
   increased deployment of the AI-driven technology quells dissent while   
   also boosting the country's innovation capacity.   
      
   The open-access paper, also called "AI-tocracy," appears in the   
   August issue of the Quarterly Journal of Economics. An abstract of the   
   uncorrected proof was first posted online in March. The co-authors are   
   Beraja, who is the Pentti Kouri Career Development Associate Professor of   
   Economics at MIT; Andrew Kao, a doctoral candidate in economics at Harvard   
   University; David Yang, a professor of economics at Harvard; and Noam   
   Yuchtman, a professor of management at the London School of Economics.   
      
   To conduct the study, the scholars drew on multiple kinds of evidence   
   spanning much of the last decade. To catalogue instances of political   
   unrest in China, they used data from the Global Database of Events,   
   Language, and Tone (GDELT) Project, which records news feeds globally. The   
   team turned up 9,267 incidents of unrest between 2014 and 2020.   
      
   The researchers then examined records of almost 3 million   
   procurementcontracts issued by the Chinese government between 2013 and   
   2019, from a database maintained by China's Ministry of Finance. They   
   found that local governments' procurement of facial-recognition AI   
   services and complementary public security tools -- high-resolution video   
   cameras -- jumped significantly in the quarter following an episode of   
   public unrest in that area.   
      
   Given that Chinese government officials were clearly responding to public   
   dissent activities by ramping up on facial-recognition technology,   
   the researchers then examined a follow-up question: Did this approach   
   work to suppress dissent?  The scholars believe that it did, although   
   as they note in the paper, they "cannot directly estimate the effect"   
   of the technology on political unrest.   
      
   But as one way of getting at that question, they studied the relationship   
   between weather and political unrest in different areas of China. Certain   
   weather conditions are conducive to political unrest. But in prefectures   
   in China that had already invested heavily in facial-recognition   
   technology, such weather conditions are less conducive to unrest compared   
   to prefectures that had not made the same investments.   
      
   In so doing, the researchers also accounted for issues such as whether   
   or not greater relative wealth levels in some areas might have produced   
   larger investments in AI-driven technologies regardless of protest   
   patterns. However, the scholars still reached the same conclusion:   
   Facial-recognition technology was being deployed in response to past   
   protests, and then reducing further protest levels.   
      
   "It suggests that the technology is effective in chilling unrest,"   
   Beraja says.   
      
   Finally, the research team studied the effects of increased AI demand   
   on China's technology sector and found the government's greater use of   
   facial- recognition tools appears to be driving the country's tech sector   
   forward. For instance, firms that are granted procurement contracts for   
   facial-recognition technologies subsequently produce about 49 percent   
   more software products in the two years after gaining the government   
   contract than they had beforehand.   
      
   "We examine if this leads to greater innovation by facial-recognition   
   AI firms, and indeed it does," Beraja says.   
      
   Such data -- from China's Ministry of Industry and Information Technology   
   - - also indicates that AI-driven tools are not necessarily "crowding out"   
   other kinds of high-tech innovation.   
      
   Adding it all up, the case of China indicates how autocratic governments   
   can potentially reach a near-equilibrium state in which their political   
   power is enhanced, rather than upended, when they harness technological   
   advances.   
      
   "In this age of AI, when the technologies not only generate growth   
   but are also technologies of repression, they can be very useful" to   
   authoritarian regimes, Beraja says.   
      
   The finding also bears on larger questions about forms of government   
   and economic growth. A significant body of scholarly research shows   
   that rights- granting democratic institutions do generate greater   
   economic growth over time, in part by creating better conditions for   
   technological innovation. Beraja notes that the current study does not   
   contradict those earlier findings, but in examining the effects of AI in   
   use, it does identify one avenue through which authoritarian governments   
   can generate more growth than they otherwise would have.   
      
   "This may lead to cases where more autocratic institutions develop side   
   by side with growth," Beraja adds.   
      
   Other experts in the societal applications of AI say the paper makes a   
   valuable contribution to the field.   
      
   "This is an excellent and important paper that improves our understanding   
   of the interaction between technology, economic success, and political   
   power," says Avi Goldfarb, the Rotman Chair in Artificial Intelligence and   
   Healthcare and a professor of marketing at the Rotman School of Management   
   at the University of Toronto. "The paper documents a positive feedback   
   loop between the use of AI facial-recognition technology to monitor   
   suppress local unrest in China and the development and training of AI   
   models. This paper is pioneering research in AI and political economy. As   
   AI diffuses, I expect this research area to grow in importance."   
   For their part, the scholars are continuing to work on related aspects of   
   this issue. One forthcoming paper of theirs examines the extent to which   
   China is exporting advanced facial-recognition technologies around the   
   world - - highlighting a mechanism through which government repression   
   could grow globally.   
      
   Support for the research was provided in part by the U.S. National Science   
   Foundation Graduate Research Fellowship Program; the Harvard Data Science   
   Initiative; and the British Academy's Global Professorships program.   
      
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   Journal Reference:   
      1. Martin Beraja, Andrew Kao, David Y Yang, Noam   
      Yuchtman. AI-tocracy. The   
         Quarterly Journal of Economics, 2023; 138 (3): 1349 DOI:   
         10.1093/qje/ qjad012   
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   Link to news story:   
   https://www.sciencedaily.com/releases/2023/07/230713142008.htm   
      
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