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Facial recognition law in China.
Su, Zhaohui; Cheshmehzangi, Ali; McDonnell, Dean; Bentley, Barry L; da Veiga, Claudimar Pereira; Xiang, Yu-Tao.
  • Su Z; School of Public Health, Southeast University, Nanjing, China suzhaohuiszh@yeah.net ytxiang@um.edu.mo.
  • Cheshmehzangi A; Department of Architecture and Built Environment, University of Nottingham - Ningbo China, Ningbo, Zhejiang, China.
  • McDonnell D; Network for Education and Research on Peace and Sustainability, Hiroshima University, Hiroshima, Japan.
  • Bentley BL; Department of Humanities, Institute of Technology Carlow, Carlow, Ireland.
  • da Veiga CP; Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, UK.
  • Xiang YT; School of Management-PPGOLD, UFPR, Curitiba, PR, Brazil.
J Med Ethics ; 48(12): 1058-1059, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1779408
ABSTRACT
Although the prevalence of facial recognition-based COVID-19 surveillance tools and techniques, China does not have a facial recognition law to protect its residents' facial data. Oftentimes, neither the public nor the government knows where people's facial images are stored, how they have been used, who might use or misuse them, and to what extent. This reality is alarming, particularly factoring in the wide range of unintended consequences already caused by good-intentioned measures and mandates amid the pandemic. Biometric data are matters of personal rights and national security. In light of worrisome technologies such as deep-fake pornography, the protection of biometric data is also central to the protection of the dignity of the citizens and the government, if not the industry as well. This paper discusses the urgent need for the Chinese government to establish rigorous and timely facial recognition laws to protect the public's privacy, security, and dignity amid COVID-19 and beyond.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Facial Recognition / COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: J Med Ethics Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Facial Recognition / COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: J Med Ethics Year: 2022 Document Type: Article