‘The ethical questions that haunt facial-recognition research’

Although facial recognition software proves to be useful in certain scenarios, what happens if this technology falls into the wrong hands. Researchers must recognize that unethical facial recognition practice is fundamentally dangerous.

• Face-recognition technology is becoming commonplace, used in most smartphones for unlocking. Several popular mobile applications, such as Instagram and Snapchat, use the technology to tag individuals and apply filters to photographs.
• It is a fast-emerging market. The global facial recognition market is expected to grow annually at 22 per cent for the next two years to become a $9.6 billion trade.
• While there is a range of facial recognition techniques, prevalent models rely on using an image to create a mathematical representation of a person’s face.
• In recent years, three-dimensional facial recognition devices have captured a significant market as retailers deploy them to gauge customers’ facial gestures and expressions to gain insights into their shopping behaviors.
• By assessing customers’ facial expressions and even bodily responses, retailers are able to gain better insights into consumer behaviour, even to the point where they can predict how and when a buyer might purchase their products in the future. This helps increase sales.

What is facial recognition, and how does it work?

• Facial recognition is a biometric technology that uses distinguishable facial features to identify a person.
• Facial recognition is a subcategory of biometrics. It’s made possible by advanced computing components, such as processors and memory, and Artificial Intelligence tools, such as machine learning.
• Facial recognition is when a device uses a camera to identify a face for security or other purposes.
• Today, it’s used in a variety of ways from allowing people to unlock their phones, go through security at the airport, purchase products at stores, etc.
• Today, the world is inundated with data of all kinds, but the plethora of photo and video data available provides the dataset required to make facial recognition technology work.
• Facial recognition systems analyze the visual data and millions of images and videos created by high-quality Closed-Circuit Television (CCTV) cameras, smartphones, social media, and other online activity.
• Machine learning and artificial intelligence capabilities in the software map distinguishable facial features mathematically, look for patterns in the visual data, and compare new images and videos to other data stored in facial recognition databases to determine identity.
  

Facial Recognition Technology in India

• Despite a limited understanding of what it entails, the potential of facial recognition is beginning to be widely explored in India, especially in enhancing national security.
• The country took the first significant step in this direction in 2019 when the National Crime Records Bureau (NCRB) under the Home Ministry released a tender calling on bidders to help create an Automated Facial Recognition System (AFRS).
• Since then, the AFRS is currently being leveraged to make police forces in India more efficient.
• One of the biggest challenges is to manually match CCTV videos against images in various databases across governmental departments, newspapers, and other sources in the public domain.
• AFRS simplifies this process by extracting facial biometrics from videos and matching it with the images housed in these databases.
• Thus, it equips them with real-time capacity to easily monitor and nab criminals, and even identify missing children as well as deceased bodies.
• Further iterations are currently being explored through machine learning to enhance it.
• In addition to AFRS, NCRB is also reportedly looking to integrate fingerprint data under its National Automated Fingerprint Identification System (NAFIS) program with Crime and Criminal Tracking Network & Systems (CCTNS).
• Combined with facial data, it will greatly assist law enforcement agencies in their investigations.

The pros and cons of facial recognition technology

Pros of facial recognition

• Enhanced security: One of the major advantages of facial recognition technology is safety and security. When people know they are being watched, they are less likely to commit crimes so the possibility of facial recognition technology being used could deter crime.
  • Law enforcement agencies use the technology to uncover criminals or to find missing children or seniors.
  • Airports are increasingly adding facial recognition technology to security checkpoints.
• Automation: Instead of hiring security officials to identify people, facial recognition technology can make the process automated. Manual recognition can be a tedious process and introduces the chances of errors. However, facial recognition works 24/7, recognizes faces automatically, and provides more reliable results.
• Quick and seamless: Since there is no contact required for facial recognition like there is with fingerprinting or other security measures, facial recognition offers a quick, automatic, and seamless verification experience.

Cons of facial recognition

• Threat to privacy: The biggest drawback for facial recognition technology in most people's opinions is the threat to an individual's privacy.
• Misidentification: The technology isn’t as effective at identifying people of color and women as it is white males. One reason for this is the data set the algorithms are trained on is not as robust for people of color and women. Until this is rectified, there are concerns about the ramifications for misidentifying people with the technology. 
• Imposes on personal freedom: Being recorded and scanned by facial recognition technology can make people feel like they’re always being watched and judged for their behavior.
• Violates personal rights: Countries with limited personal freedoms, commonly use facial recognition to spy on citizens and arrest those deemed troublemakers.
• Creates data vulnerabilities: There is also concern about the storage of facial recognition data, as these databases have the potential to be breached. 

What’s the Law on Facial Recognition?

• The direct implementation of such technologies has not been recognized by law.
• As such, there is a need for having in place detailed legal frameworks passed by the Parliament of India which authorize the implementation and maintenance of such automated facial recognition technologies.
• Currently, in India, there is no specific law which authorizes deployment of these technologies.
• The Indian Information Technology Act, 2000 being India’s mother legislation on the electronic format is completely silent on facial recognition. Also even under the rules passed under the Information Technology Act, 2000, there has no reference to the facial recognition.
• As such, for a long term deployment of these technology, it will be imperative, that the Parliament should pass strong law to not just enable legal implementation of such technologies but also the law should establish the various instances where such technologies can be so implemented.

What about Right to privacy?

• One of the biggest challenges concerning facial recognition technology is the fact that it would tend to violate people fundamental right to privacy enshrined under Article 21 of the Constitution of India. 
• By virtue of the judgment of Justice Puttaswamy v/s Union of India, the Hon’ble Supreme Court of India has already declared the right to privacy as a fundamental right and such right can only be exercised in accordance with the procedure established under the law. 
• If there is no procedure established under law, any deployment or adoption of such technologies, tantamount to violation of people fundamental right to privacy.
• The Government needs to specifically keep in mind these factors and parameters into consideration as it move forward in the deployment of new technologies.

Where to draw the line? 

• On the face of it, the technology appears to be just another addition to the technologically perfect systems. But the world is waking up to its perils.
• While many question the necessity of this technology, others have raised alarm as it can be used by governments to pervade privacy and intensify mass surveillance.

Data without consent

• For facial-recognition algorithms to work well, they must be trained and tested on large data sets of images, ideally captured many times under different lighting conditions and at different angles.
• In the 1990s and 2000s, scientists generally got volunteers to pose for these photos — but most now collect facial images without asking permission.
  • For instance, in 2015, scientists at Stanford University in California published a set of 12,000 images from a webcam in a San Francisco café that had been live-streamed online.
  • The following year, researchers at Duke University in Durham, North Carolina, released more than 2 million video frames (85 minutes) of footage of students walking on the university campus.
  • In 2016, researchers at the University of Washington in Seattle posted a database, called MegaFace, of 3.3 million photos.
  • And scientists at Microsoft Research in Redmond, Washington, issued the world’s largest data set, MSCeleb5, consisting of 10 million images of nearly 100,000 individuals, including journalists, musicians and academics, scraped from the Internet.
• The US social-media firm Facebook, for instance, agreed this year to pay US$650 million to resolve an Illinois class-action lawsuit over a collection of photos that was not publicly available, which it used for facial recognition (it now allows users to opt out of facial-recognition tagging).
• The controversial New York City-based technology company Clearview AI — which says it scraped three billion online photos for a facial-recognition system — has also been sued for violating this law in pending cases.

Ethical checkpoints

• Questionable research projects have popped up in the United States, too.
• In May this year, a press release declared that researchers had developed facial-recognition software “capable of predicting whether someone is likely going to be a criminal”, with “80 percent accuracy and no racial bias”.
• The announcement triggered a wave of criticism, as had previous studies that hark back to the discredited work of nineteenth-century physiognomists.
• Though the press release was removed following the outcry, but left a dangling question: the press release had said that the work was to be published by Springer Nature in a book series (which the publisher later denied).
• On 22 June, more than 2,400 academics signed a letter from a group called the Coalition for Critical Technology (CCT), asking Springer Nature not to publish the work and calling on all publishers to refrain from publishing similar studies.
• The letter pointed out that such studies are based on unsound science. It also noted that algorithmic tools that tell police where or who to target tend to provide a scientific veneer for automated methods that only exacerbate existing biases in the criminal justice system.

Challenges in India

• Absence of individual privacy protection: In the Indian context, these concerns are amplified by the absence of strong individual privacy protections and checks on government infringement on civil liberties.
• Although privacy has been recognized as a “Fundamental Right” by Indian Supreme Court, law enforcement at both the state and central level have exhibited a growing tendency to flout court rulings in the absence of legal protection of personal privacy and data.
• Broad access to government: Pending legislation to guard individual privacy provides the central government with broad access to individual data and does not establish institutional checks on government use of emerging technologies with implications for individual privacy.
• Slow judicial system: Coupled with India’s slow judicial process and weak constraints on arrest of individuals, the use of FRT raises serious concerns about both individual privacy and protections from excessive law enforcement usage.
• False identification: Individuals falsely identified by facial recognition technologies face potential years of imprisonment before the legitimacy of their arrest is examined in court.

Conclusion

The application of facial recognition technologies in India would almost certainly aid the country’s stretched law enforcement units and may prove useful in future incidents of public rioting or unrest. Given the state of current technologies, government officials in India need to critically examine the reliability of this new platform and its potential to wrongfully infringe on the rights of innocent individuals.