I wrote at the time that while these Big Tech firms were responding to pressure after the Clearview AI debacle, work on facial recognition technology would continue unabated (bit.ly/4c82BQv ).
To remind you, Clearview AI, without express permission, had access to all platforms, such as Facebook, Instagram and others, which may have contained images of our faces.
At that time, Microsoft extended its time limit on selling facial recognition technology to police indefinitely, emphasizing the need for government regulation before starting this sale. Amazon initially imposed a one-year ban on police use of its facial recognition technology, Rekognition, and has since extended the ban.
IBM took a more specific position by exiting the general-purpose facial recognition market, shifting its focus to specialized applications such as vision recognition for specific industrial purposes. These companies are very much sticking to their promises, but they are continuing to develop and use facial recognition technology in other sectors.
Meanwhile, other companies have filled the void. International markets, especially in countries with less regulation, continue to see the enthusiastic development and deployment of facial recognition technology.
A wag once told me that thanks to facial recognition and advanced location technology, at least three governments and maybe 5-6 Big Tech and maybe a few startups always know exactly where you are. Given the importance and convenience this technology offers to the common man, this is a good thing.
However, when it comes to racial segregation, the story is very different—and this is a common issue in multiracial societies, such as the US, that defines the Big Tech situation.
The point is that studies have consistently shown that commercially available facial recognition systems are more likely to make mistakes with faces with non-Caucasian skin tones. This inconsistency can have negative consequences, such as mistreatment and reinforcing prejudice.
US government research shows that facial recognition systems have a 10-100 chance of not recognizing people with dark skin (bit.ly/3WObwCn). In the hands of the law, such error rates can be dangerous; this highlights the need to improve accuracy and reduce bias in these technologies, which is why Big Tech firms withdrew.
In the case of Microsoft in 2019, its software had negative reviews about ten times more for women of color than for men of color (bit.ly/3WNbJFM), while in previous years, Google technology it referred to Africans as gorillas (bit.ly/3Wrf7Vz). It was smart to get out.
Despite the problems seen in the US, India and China have continued to implement this technology extensively, often with claims of high accuracy. This may be due to the fact that there are few ethnic groups in these countries, but there are other reasons as well, especially government support for its use.
The accuracy rates required by facial recognition systems in India are often high, supported as they are often integrated with national identification systems such as Aadhaar.
China has invested heavily in facial recognition technology, with claims of high accuracy rates supported by a large collection of data and combined with various surveillance and identification systems.
The Chinese government reports accuracy rates as high as 99%, although these figures are not independently verified and may be influenced by Beijing’s investment in government regulation and surveillance programs. In China, the independent validation and ethical implications of these technologies remain issues of concern.
A number of factors can explain the many positives in India and China that differ from the American facial recognition experience. Government support of the projects, with larger funds combined with access to government resources, for example, would have made a difference.
Both India and China have much larger populations than any other country in the world, so their access to large image databases allows them to fully train facial recognition algorithms, improving their accuracy. Additionally, integrating facial recognition with other identification systems (such as national ID systems) can enhance the overall reliability of these systems.
Regulatory frameworks in India and China are also less stringent than in the US, allowing for easy and widespread deployment and iterative development of facial recognition technology. At least in India, this has given citizens conveniences, such as faster security checks during air and rail travel.
Commitments by Microsoft, Amazon and IBM to stop the sale of facial recognition technology to police have been widely welcomed in the US, reflecting a response to ethical and social concerns. Despite this, the development of facial recognition technology has continued, as I predicted.
While racial discrimination remains an important issue in the United States, India and China continue to improve their facial recognition systems, implying higher accuracy rates. In my opinion, this accuracy will increase. And in India, its use cases so far have been important to the general public.
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