"greater mass surveillance drives economic growth."
<https://www.harvardmagazine.com/2022/05/right-now-authoritarian-regimes-artificial-intelligence>
For the past decade, China has led the world in advanced-facial
recognition systems. Chinese companies dominate the rankings of the
National Institute of Standards and Technology’s Face Recognition Vendor
Test, considered the accepted standard for judging the accuracy of these
systems, and Chinese research papers on the subject are cited almost
twice as often as American ones. Many experts recognize the importance
of facial-recognition and other artificial-intelligence applications for
promoting future economic growth through productivity gains, which makes
understanding how China came to dominate this field a competitive
concern. And after years of research, Harvard assistant professor of
economics David Yang believes he’s discovered an explanation for the
Chinese companies’ advantage.
In a recent National Bureau of Economic Research working paper, Yang and
his colleagues found that authoritarian states like China may have an
inherent and decisive advantage over liberal democracies in
facial-recognition innovation. Their secret? The flow of massive amounts
of surveillance data to private AI companies that develop
facial-recognition software for local police departments. Like all AI
systems, facial-recognition systems depend on substantial quantities of
training data to learn how to recognize faces: the more data they
process, the more reliable they become. The researchers’ findings
suggest Chinese AI firms use surveillance data to develop sophisticated
facial-recognition algorithms that can later be repurposed for
commercial applications like more effective targeted advertisements and
tracking of customer behavior in stores, which creates a feedback loop
where greater mass surveillance drives economic growth.
It’s a startling conclusion that will likely have significant
repercussions for the commercialization of AI systems in the United
States and Europe. Yang’s findings suggest that policymakers in the West
need to start considering the economic tradeoffs that come with strong
protections for personal data rather than focusing solely on the value
of privacy. In fact, the research suggests that overly strong data
protections may turn out to be inadvertent anti-industrial policies that
starve fledgling AI companies of the data they need to innovate. Unless
these tensions are addressed soon, the United States may find itself far
behind in the race to build one of the most important technologies of
the twenty-first century.
At the core of China’s burgeoning facial-recognition industry is an
Orwellian mass surveillance system unparalled in scope and scale. More
than half of the world’s roughly one billion surveillance cameras are
within China’s borders, and nine of the world’s 10 most surveilled
cities on a cameras-per-capita basis are Chinese. If Chinese companies
are able to tap into this video surveillance network through government
contracts they should be able to develop superior algorithms and parlay
these systems into commercial applications.
“If you want to do any sort of customer identification or personalized
advertisements, then being able to identify who comes into a shop for
the first time and who is a repeat customer is super important
information,” says Yang. “From an algorithm perspective, these
commercial applications sound very similar to what a police department
might want to do on its own. So once a company uses government data to
improve its facial-recognition system’s accuracy rate, it’s natural that
it would also use it to help retailers make predictions about their
customers.”
It’s an intuitive theory, but until Yang and his colleagues collected
the data there was scant evidence to support the hypothesis. The
researchers started by analyzing publicly available listings of Chinese
facial-recognition companies and their major products, which the
government requires to be reported to its Ministry of Industry and
Information Technology. They identified approximately 1,000 companies
that had received a contract to supply local police departments with
facial-recognition software, which presumably came with access to local
surveillance video data.
The researchers’ next step was to determine whether the volume of video
data received by these firms correlated with their output of commercial
facial-recognition products. They sorted the contracts by the number of
surveillance cameras in the police district and labeled contracts with
above average numbers of cameras “data-rich” and those with below
average numbers of cameras “data-scarce.”
There may be “economic tradeoffs that come with strong protections for
personal data….”
If access to data-rich government contracts didn’t influence the
development of commercial facial-recognition software, the researchers
would have expected to see a drop in commercial products as firms
reallocated engineering talent to service the government contract. But
they found the opposite. Firms that secured a data-rich
facial-recognition contract with police departments almost immediately
produced more facial-recognition software for government /and/
commercial applications than those with a data-scarce contract. This
suggests that the government data boost AI innovation because they are
applicable to both government and commercial applications.
“Our speculation is that this happens because of algorithm spillover,”
says Yang. “The companies don’t need to decide between allocating
engineering resources to government or commercial applications because
the same algorithm can be applied in multiple places at the same time.”
The findings have important implications for how the United States and
other western countries think about the tradeoff between data privacy
and economic policies. While Yang is hesitant to draw any normative
conclusions from this work, he says that it does show how one-sided the
debate on AI and data ethics has become in the West. By focusing only on
the privacy implications of facial-recognition technology, policymakers
have ignored the economic effects of denying data to AI firms that need
it to develop their technology. As a result, facial- recognition firms
have flourished in authoritarian countries like China that lack robust
data-privacy protections—and languished in the United States and Europe.
Yang says the key to unlocking similar AI innovation in the West may
involve reframing access to government data as key public infrastructure
comparable to roads or bridges without sacrificing basic privacy
protections and civil liberties.
“A lot of privacy-protection policies could have anti-industrial
consequences because it hurts industries that rely on that data,” he
says. “I’m not suggesting whether these policies are or are not
justified, but there is an asymmetry in the discussion that only focuses
on the value of privacy. Once the economic value is taken into
consideration, we can start to think about whether the civil-liberty
costs outweigh the economic potential of these innovations.”
_______________________________________________
nexa mailing list
nexa@server-nexa.polito.it
https://server-nexa.polito.it/cgi-bin/mailman/listinfo/nexa
