ChinAI #131: The Abuses of Facial Recognition
A Special Report by The Beijing News
|Jeffrey Ding||Feb 15||3|
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Feature Translation: A Special Report on the Abuses of Facial Recognition Technology
Context: Last month, The Beijing News published a special report on the abuses of facial recognition in China. This was an impressive 8-part series (see screenshot below):
The Beijing News is a news outlet known for investigative reporting (though there has been a “taming of critical journalism” in China since 2012). I’ve translated the first two articles in the series, each of which draws from original research by a think tank under The Beijing News. One reports on an evaluation of 70 apps that support facial recognition; the other covers a public opinion questionnaire about facial recognition.
1) Key Takeaways from the app evaluation (link to original in Mandarin)
Background: Controversy about facial recognition has surged after China’s “first case involving facial recognition” (a professor sued a wildlife park for requiring facial recognition) went to appeal, and after the case of prospective house buyers wearing helmets to avoid facial recognition-enabled price discrimination went viral.
The think tank under The Beijing News evaluated 67 apps that support facial recognition, and they found: a) only 7% of apps have clear facial recognition usage agreements AND obtain user permission beforehand; b) 84% do not tell users how to delete their personal information related to facial data.
Facial recognition is becoming the “standard configuration” for smart property management BUT there has been some pushback: In the case of the former, access control by facial recognition covers 168,900 residents in communities in Lanzhou (capital of Gansu Province); in the case of the latter, in December 2020 the “Tianjin Municipal Social Credit Regulations” implemented the first public prohibitions on the collection of facial recognition information. Neighborhood committees asked residents to decide for themselves whether to continue using facial recognition for access control.
Report goes after government affairs for loopholes in facial recognition applications: one example is an app for real estate transfers, which was launched by Nanning (capital of Guangxi). There was a security breach in the facial recognition function of the app which led to fraudulent property transfers.
2) Key Takeaways from the public opinion questionnaire (link to original in Mandarin)
Beijing News Think Tank surveyed 1,515 people about their attitudes towards facial recognition (not a nationally representative sample, as >80% of people had a bachelor’s degree or above)
The most common scenarios for facial recognition applications were: transportation security checks (70% of respondents) and identity verification/registration, such as to check-in at hotels or buy tickets (65%)
75% of respondents are worried about facial recognition; 60% say that they are “on alert” about facial recognition; 2% say that they are indifferent or that it doesn’t matter
55.5% of respondents say that “if there’s another method, I definitely will not choose facial recognition.”
87% of respondents opposed the use of facial recognition in public places for business.
FULL TRANSLATION: A Special Report on the Abuses of Facial Recognition Technology
ChinAI Links (Four to Forward)
Madeleine Clare Elish’s article underscores the significance of human-computer interaction design in explaining accidents involving autonomous systems. Elish presents two cases studies — one of Three Mile Island and another on the crash of Air France Flight 447 — that highlight the “moral crumple zone,” a space where human operators of machine systems take the blame for accidents that are the fault of more complex interactions between humans and automated systems.
Abstract: “In this proof-of-concept project, CSET and Amplyfi Ltd. used machine learning models and Chinese-language web data to identify Chinese companies active in artificial intelligence. Most of these companies were not labeled or described as AI-related in two high-quality commercial datasets. The authors' findings show that using structured data alone—even from the best providers—will yield an incomplete picture of the Chinese AI landscape.”
For Lawfare, Lindsay Hundley, a postdoctoral fellow at Stanford University’s Center for International Security and Cooperation, points out that “The Kremlin’s main method of influencing opinion rests on a seemingly benign tool: the topics that its state-led media report…None of these stories [in Russia Today about the U.S. inauguration] is false, and much of the reporting refrains from overt editorializing. But these stories are designed to leave readers and viewers with particular beliefs about the attractiveness of the U.S. political system.”
A joint report from a working group at Stanford and a program at American University Washington College of Law that “suggests a comprehensive framework for understanding and assessing the risks posed by Chinese technology platforms in the United States … the specific threats and risks posed by different Chinese technologies vary, and effective policies must start with a targeted understanding of the nature of risks and an assessment of the impact US measures will have on national security and competitiveness. The goal of the paper is not to specifically quantify the risk of any particular technology, but rather to analyze the various threats, put them into context, and offer a framework for assessing proposed responses in ways that the signatories hope can aid those doing the risk analysis in individual cases.”
Thank you for reading and engaging.
These are Jeff Ding's (sometimes) weekly translations of Chinese-language musings on AI and related topics. Jeff is a PhD candidate in International Relations at the University of Oxford and a researcher at the Center for the Governance of AI at Oxford’s Future of Humanity Institute.
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Any suggestions or feedback? Let me know at firstname.lastname@example.org or on Twitter at @jjding99
EDITED 2.27.21 with a smoother translation for 公共消费场所 — h/t to a ChinAI reader for the suggestion.