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The ugly face of a crime-fighting move: Facial Recognition

  • IASbaba
  • August 25, 2021
  • 0
UPSC Articles
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GOVERNANCE/ SECURITY

  • GS-3: Science & Technology; Security
  • GS-2: Government policies and interventions for development in various sectors and issues arising out of their design and implementation

The ugly face of a crime-fighting move: Facial Recognition

In news Government has been exploring the potential of facial recognition technology.

About NAFRS

  • To empower the Indian police with information technology, India approved implementation of the National Automated Facial Recognition System (NAFRS)
  • It will function as a national-level search platform that will use facial recognition technology: to facilitate investigation of crime or for identifying a person of interest (e.g., a criminal) regardless of face mask, makeup, plastic surgery, beard or hair extension.
  • The system compares the faceprint generated with a large existing database of faceprints (typically available to law enforcement agencies) through a database on driver’s licence or police mugshots).

Do You Know?

  • FBI in US uses facial recognition technology for potential investigative leads; Police forces in England use facial recognition to tackle serious violence. 
  • China use facial recognition for racial profiling and mass surveillance — to track Uighur Muslims.

Criticism of NAFRS

  • Violates Right to Privacy: As NAFRS will collect, process, and store sensitive private information: facial biometrics for long periods; if not permanently — it will impact the right to privacy.
  • Not 100% accurate: Facial recognition does not return a definitive result — it ‘identifies’ or ‘verifies’ only in probabilities (e.g., a 70% likelihood. Though the accuracy of facial recognition has improved over the years due to modern machine-learning algorithms, the risk of error and bias still exists. 
  • Bias & Prejudice: Research suggests facial recognition software is based on pre-trained models. Therefore, if certain types of faces (such as female, children, ethnic minorities) are under-represented in training datasets, then this bias will negatively impact its performance.
  • Fear of Profiling: With the element of error and bias, facial recognition can result in profiling of some overrepresented groups (such as Dalits and minorities) in the criminal justice system.
  • Constitutionality Concerns: It is alleged that NAFRS fails the three tests of Puttaswamy Judgement: legitimacy (backed by law), proportionate to its need and least restrictive.
  • Lacks Statutory Clarity: There is potential for abuse and misuse of NAFRS especially when there is absence of clear guidelines for its deployment and lack of Comprehensive Data Protection Bill. 
  • Chilling Effect on Civil Liberties: Unregulated use of facial recognition technology will dis-incentivise independent journalism or the right to assemble peaceably or any other form of civic society activism.
  • Federal Challenges: Policing and law and order being State subjects, some Indian States have started the use of new technologies without fully appreciating the dangers involved.

Conclusion

Government must enact a strong and meaningful data protection law, in addition to statutory authorisation of NAFRS and guidelines for deployment to prevent its misuse and abuse. 

Connecting the dots:

  • Aadhar Public Data Ecosystem
  • The Personal Data Protection Bill, 2019

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