The 1970 World Expo in Osaka, Japan, offered a glimpse of the future. Huge domes and geometric towers housed early demonstrations of wireless mobile phones, levitating trains, and a screening of the first IMAX movie. It was the first World Expo in Asia, and more than 64 million people attended.

Those who visited the pavilion sponsored by NEC saw a unique demonstration called computer physiognomy. Over the next few decades, that term would evolve into the field of biometrics.

At the Osaka expo, guests were invited to sit in front of a large video camera to have their faces digitized and analyzed by a computer algorithm. Each of the 800 guests who complied had their faces matched to one of seven celebrities of the era.

Decades before the technology would be deployed in airports and police forensic units — and before the words “machine learning” would cross the lips of a venture capitalist — NEC was previewing facial recognition.

A timeline of NEC’s involvement in biometrics. Source: NEC

“It would have been naive to believe that the program actually produced scientific results, since physiognomic analysis had long been discredited as pseudoscience,” Kelly A. Gates wrote in her book Our Biometric Future. “But the experience of having one’s face analyzed by a computer program foretold a future in which intelligence machines would see the human face and make sense of it in a technologically advanced way.”

At the time, NEC was still called the Nippon Electric Company. Founded in 1899 as a telecommunications company and seeded with funds from U.S. communications firm Western Electric, Nippon Electric made a name for itself manufacturing telecommunications switchboards.

Before World War II, Japan’s economy depended on assembly lines and manufacturing—perfect for the precise telecommunications equipment that NEC built. The country’s manufacturing economy shifted toward consumer electronics such as televisions, computers, and telephones after the war, says Michael A. Cusumano, a distinguished professor at MIT Sloan School of Management who has written extensively on Japanese technology firms.

NEC was well positioned for the explosion of communication technology. It built radio broadcast technology and electronic telephone switchboards. By 1958, NEC had completed its first true, transistor-based computer.

Over the next three decades, NEC pushed its communications expertise into personal computers. By the early 1990s, NEC was the only company in the world to be among the top five producers of computers, semiconductors, and telecommunications equipment, according to Martin Fransman, a professor of economics at the University of Edinburgh who has researched Japan’s computer industry. It dominated 50% of Japan’s personal computer market. NEC was one of the most powerful companies in the world.

But NEC stumbled in the U.S. personal computer market. In the late 1990s, the firm entered into a drawn-out, ill-fated acquisition of Packard Bell, which resulted in nearly $2 billion in losses.

Over the course of the late 1990s and into the 2000s, NEC spun off its businesses by signing them into partnerships with companies like Samsung for computer and TV displays, or creating new companies like NEC Electronics, a standalone semiconductor company. NEC was still enormous, but it was phasing out of being a household electronics name in the United States.

In 1989, the company started research and development of commercial facial recognition by extending pattern-matching software it developed to identify characters like numbers and letters.

In the early 2000s, NEC began to shift its focus toward a division of the company that had, for decades, remained in the wings: biometrics, or the practice of verifying someone’s identity using biological features.

NEC’s first foray into biometrics was fingerprint analysis. As early as 1969, the company had begun working with the Japanese National Police Agency to build a system that would automatically identify fingerprints. In 1982, the National Police Agency installed the Automated Fingerprint Identification System in Japan; in 1983, it installed a version of the program in San Francisco.

Throughout the 1980s, NEC signed contracts everywhere from Washington state to Australia, cementing it as an early leader in biometric technology. In 1989, the company started research and development of commercial facial recognition by extending pattern-matching software it developed to identify characters like numbers and letters. According to a 2018 company presentation, NEC rolled out NeoFace, its first mass-market facial recognition product, in 2002.

Since its start with fingerprints, NEC has been an industry leader in the accuracy of its biometric technologies. In 2004, the National Institute of Standards and Technology tested 34 automated fingerprint matching devices, and called out NEC as a top performer. As recently as September 2019, the National Institute of Standards and Technology (NIST) weighed NEC’s facial recognition algorithms against nearly 200 other programs and indicated that the company was among the most accurate.

“NEC, which had produced broadly the most accurate algorithms in 2010 and 2013, submitted algorithms that are substantially more accurate than their June 2018 versions, and on many measures are now the most accurate,” the 2019 NIST report said.

Though accuracy has been a major selling point for NEC’s facial recognition systems, it’s unclear just how accurate they really are, especially as the field of facial recognition as a whole has proven unreliable outside of the lab. A 2018 analysis of commercial facial recognition systems found that the algorithms were more than 30% less accurate when attempting to identify women of color compared to white men, making systems little more accurate than a coin toss. Privacy advocates say that if the algorithm were to mistake one person whose image was taken at a crime scene for another, that innocent person could be unfairly implicated or investigated for committing a crime, putting them under undue police scrutiny.

“We have a technology that was created and designed by one demographic, that is only mostly effective on that one demographic, and they’re trying to sell it and impose it on the entirety of the country,” New York congresswoman Alexandria Ocasio-Cortez said in a 2019 congressional hearing on facial recognition and law enforcement.

A 2019 slide showing NEC’s biometric contracts in the United States. Source: NEC

NIST’s tests have come under some scrutiny as well. “You can think of NIST as being the easiest possible case to pass,” says Deborah Raji, an A.I. researcher who works with the AI Now Institute and the Algorithmic Justice League on auditing facial recognition systems. “The images are well lit and in a constrained environment with a consistent background. If the model does not do well on this test, that’s significant, but doing well on NIST does not at all mean the model can handle real-world conditions.”

There are few ways to independently audit NEC’s technology outside of NIST testing. In trials of the NEC technology in London, one of the only independent analyses of NEC’s algorithm found that 81% of 42 people flagged by the facial recognition algorithm were not actually on a watchlist.

To Raji, who worked on the audits that inspired congressional hearings on racial disparity in facial recognition, the results of these real-world trials are crucial.

“The only way to get a truly meaningful reading of a model’s accuracy in deployment is to pilot the technology and measure those metrics in the real world. And even after doing so, it takes so much more than accuracy to understand a model’s performance and likelihood for success in deployment,” she says.