Facebook to Shut Down Face-recognition System, Delete Data

Photo: REUTERS
Photo: REUTERS
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Facebook to Shut Down Face-recognition System, Delete Data

Photo: REUTERS
Photo: REUTERS

Facebook said it will shut down its face-recognition system and delete the faceprints of more than 1 billion people amid growing concerns about the technology and its misuse by governments, police and others.

“This change will represent one of the largest shifts in facial recognition usage in the technology’s history,” Jerome Pesenti, vice president of artificial intelligence for Facebook’s new parent company, Meta, wrote in a blog post on Tuesday.

He said the company was trying to weigh the positive use cases for the technology “against growing societal concerns, especially as regulators have yet to provide clear rules.” The company in the coming weeks will delete “more than a billion people’s individual facial recognition templates," he said.

Facebook’s about-face follows a busy few weeks. On Thursday it announced its new name Meta for Facebook the company, but not the social network. The change, it said, will help it focus on building technology for what it envisions as the next iteration of the internet -- the “metaverse.”

The company is also facing perhaps its biggest public relations crisis to date after leaked documents from whistleblower Frances Haugen showed that it has known about the harms its products cause and often did little or nothing to mitigate them.

More than a third of Facebook’s daily active users have opted in to have their faces recognized by the social network’s system. That’s about 640 million people. Facebook introduced facial recognition more than a decade ago but gradually made it easier to opt out of the feature as it faced scrutiny from courts and regulators.

Facebook in 2019 stopped automatically recognizing people in photos and suggesting people “tag" them, and instead of making that the default, asked users to choose if they wanted to use its facial recognition feature.

Facebook's decision to shut down its system “is a good example of trying to make product decisions that are good for the user and the company,” said Kristen Martin, a professor of technology ethics at the University of Notre Dame. She added that the move also demonstrates the power of public and regulatory pressure, since the face recognition system has been the subject of harsh criticism for over a decade.

Meta Platforms Inc., Facebook's parent company, appears to be looking at new forms of identifying people. Pesenti said Tuesday's announcement involves a “company-wide move away from this kind of broad identification, and toward narrower forms of personal authentication."

“Facial recognition can be particularly valuable when the technology operates privately on a person’s own devices," he wrote. “This method of on-device facial recognition, requiring no communication of face data with an external server, is most commonly deployed today in the systems used to unlock smartphones."
Apple uses this kind of technology to power its Face ID system for unlocking iPhones.

Researchers and privacy activists have spent years raising questions about the tech industry's use of face-scanning software, citing studies that found it worked unevenly across boundaries of race, gender or age. One concern has been that the technology can incorrectly identify people with darker skin.

Another problem with face recognition is that in order to use it, companies have had to create unique faceprints of huge numbers of people – often without their consent and in ways that can be used to fuel systems that track people, said Nathan Wessler of the American Civil Liberties Union, which has fought Facebook and other companies over their use of the technology.

“This is a tremendously significant recognition that this technology is inherently dangerous,” he said.

Facebook found itself on the other end of the debate last year when it demanded that facial recognition startup ClearviewAI, which works with police, stop harvesting Facebook and Instagram user images to identify the people in them.

Concerns also have grown because of increasing awareness of the Chinese government’s extensive video surveillance system, especially as it’s been employed in a region home to one of China’s largely Muslim ethnic minority populations.

Facebook’s huge repository of images shared by users helped make it a powerhouse for improvements in computer vision, a branch of artificial intelligence. Now many of those research teams have been refocused on Meta’s ambitions for augmented reality technology, in which the company envisions future users strapping on goggles to experience a blend of virtual and physical worlds. Those technologies, in turn, could pose new concerns about how people’s biometric data is collected and tracked.

Facebook didn’t provide clear answers when asked how people could verify that their image data was deleted and what the company would be doing with its underlying face-recognition technology.

On the first point, company spokesperson Jason Grosse said in email only that user templates will be “marked for deletion” if their face-recognition settings are on, and that the deletion process should be completed and verified in “coming weeks.” On the second, point, Grosse said that Facebook will be “turning off” components of the system associated with the face-recognition settings.

Meta’s newly wary approach to facial recognition follows decisions by other US tech giants such as Amazon, Microsoft and IBM last year to end or pause their sales of facial recognition software to police, citing concerns about false identifications and amid a broader US reckoning over policing and racial injustice.

At least seven US states and nearly two dozen cities have limited government use of the technology amid fears over civil rights violations, racial bias and invasion of privacy.

President Joe Biden’s science and technology office in October launched a fact-finding mission to look at facial recognition and other biometric tools used to identify people or assess their emotional or mental states and character. European regulators and lawmakers have also taken steps toward blocking law enforcement from scanning facial features in public spaces.

Facebook’s face-scanning practices also contributed to the $5 billion fine and privacy restrictions the Federal Trade Commission imposed on the company in 2019. Facebook’s settlement with the FTC included a promise to require “clear and conspicuous” notice before people’s photos and videos were subjected to facial recognition technology.

And the company earlier this year agreed to pay $650 million to settle a 2015 lawsuit alleging it violated an Illinois privacy law when it used photo-tagging without users’ permission.

“It is a big deal, it’s a big shift but it’s also far, far too late,” said John Davisson, senior counsel at the Electronic Privacy Information Center. EPIC filed its first complaint with the FTC against Facebook’s facial recognition service in 2011, the year after it was rolled out.



Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
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Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson

Shares in Meta skyrocketed by 10 percent at opening on Wall Street on Thursday, a day after the social media giant posted better than expected earnings as the company invests heavily in artificial intelligence.

Microsoft, whose earnings disappointed analysts, saw its share price tumble by 10 percent, with investors showing concern for the return on investment for the software giant's spending on AI.


Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
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Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File

South Korean tech giant Samsung Electronics posted record quarterly profits Thursday, riding massive market demand for the memory chips that power artificial intelligence.

A global frenzy to build AI data centers and develop the fast-evolving technology has sent orders for advanced high bandwidth memory microchips soaring.

That is also pushing up prices for less flashy chips used in consumer electronics -- threatening higher prices for phones, laptops and other devices worldwide.

In the quarter to December 2025, Samsung said it saw "its highest-ever quarterly consolidated revenue at KRW 93.8 trillion (US$65.5 billion)", a quarter-on-quarter increase of nine percent.

"Operating profit was also an all-time high, at KRW 20.1 trillion," the company said.

The dazzling earnings came a day after a key competitor, South Korean chip giant SK hynix, said operating profit had doubled last year to a record high, also buoyed by the AI boom.

The South Korean government has pledged to become one of the top three AI powers, behind the United States and China, with Samsung and SK hynix among the leading producers of high-performance memory.

Samsung said Thursday it expects "AI and server demand to continue increasing, leading to more opportunities for structural growth".

Annual revenue stood at 333.6 trillion won, while operating profit came in at 43.6 trillion won. Sales for the division that oversees its semiconductor business rose 33 percent quarter-on-quarter.

The company pointed to a $33.2 billion investment in chip production facilities -- pledging to continue spending in "transitioning to advanced manufacturing processes and upgrading existing production lines to meet rising demand".

- 'Clearly back' -

Major electronics manufacturers and industry analysts have warned that chipmakers focusing on AI sales will cause higher retail prices for consumer products across the board.

This week US chip firm Micron said it was building a $24 billion plant in Singapore in response to AI-driven demand that has caused a global shortage of memory components.

SK hynix announced Wednesday that its operating profit had doubled last year to a record 47.2 trillion won.

The company's shares have surged some 220 percent over the past six months, while Samsung Electronics has risen about 130 percent, part of a huge global tech rally fueled by optimism over AI.

Both companies are on the cusp of producing next-generation high-bandwidth "HBM4" chips for AI data centers, with Samsung reportedly due to start making them in February.

American chip giant Nvidia -- now the world's most valuable company -- is expected to be one of Samsung's customers for HBM4 chips.

But Nvidia has reportedly allocated around 70 percent of its HBM4 demand to SK hynix for 2026, up from the market's previous estimate of 50 percent.

"Samsung is clearly back and we are expecting them to show a significant turnaround with HBM4 for Nvidia's new products -- helping them move past last year's quality issues," Hwang Min-seong, research director at market analysis firm Counterpoint, told AFP.

But SK still "maintains a market lead in both quality and supply" of a number of key components, including Dynamic Random Access Memory chips used in AI servers, he said.

SK also this week said it will set up an "AI solutions firm" in the United States, committing $10 billion and weighing investments in US companies.


Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
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Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)

Google unveiled an artificial intelligence tool Wednesday that its scientists said would help unravel the mysteries of the human genome -- and could one day lead to new treatments for diseases.

The deep learning model AlphaGenome was hailed by outside researchers as a "breakthrough" that would let scientists study and even simulate the roots of difficult-to-treat genetic diseases.

While the first complete map of the human genome in 2003 "gave us the book of life, reading it remained a challenge", Pushmeet Kohli, vice president of research at Google DeepMind, told journalists.

"We have the text," he said, which is a sequence of three billion nucleotide pairs represented by the letters A, T, C and G that make up DNA.

However, "understanding the grammar of this genome -- what is encoded in our DNA and how it governs life -- is the next critical frontier for research," said Kohli, co-author of a new study in the journal Nature.

Only around two percent of our DNA contains instructions for making proteins, which are the molecules that build and run the body.

The other 98 percent was long dismissed as "junk DNA" as scientists struggled to understand what it was for.

However, this "non-coding DNA" is now believed to act like a conductor, directing how genetic information works in each of our cells.

These sequences also contain many variants that have been associated with diseases. It is these sequences that AlphaGenome is aiming to understand.

- A million letters -

The project is just one part of Google's AI-powered scientific work, which also includes AlphaFold, the winner of 2024's chemistry Nobel.

AlphaGenome's model was trained on data from public projects that measured non-coding DNA across hundreds of different cell and tissue types in humans and mice.

The tool is able to analyze long DNA sequences then predict how each nucleotide pair will influence different biological processes within the cell.

This includes whether genes start and stop and how much RNA -- molecules which transmit genetic instructions inside cells -- is produced.

Other models already exist that have a similar aim. However, they have to compromise, either by analyzing far shorter DNA sequences or decreasing how detailed their predictions are, known as resolution.

DeepMind scientist and lead study author Ziga Avsec said that long sequences -- up to a million DNA letters long -- were "required to understand the full regulatory environment of a single gene".

And the high resolution of the model allows scientists to study the impact of genetic variants by comparing the differences between mutated and non-mutated sequences.

"AlphaGenome can accelerate our understanding of the genome by helping to map where the functional elements are and what their roles are on a molecular level," study co-author Natasha Latysheva said.

The model has already been tested by 3,000 scientists across 160 countries and is open for anyone to use for non-commercial reasons, Google said.

"We hope researchers will extend it with more data," Kohli added.

- 'Breakthrough' -

Ben Lehner, a researcher at Cambridge University who was not involved in developing AlphaGenome but did test it, said the model "does indeed perform very well".

"Identifying the precise differences in our genomes that make us more or less likely to develop thousands of diseases is a key step towards developing better therapeutics," he explained.

However, AlphaGenome "is far from perfect and there is still a lot of work to do", he added.

"AI models are only as good as the data used to train them" and the existing data is not very suitable, he said.

Robert Goldstone, head of genomics at the UK's Francis Crick Institute, cautioned that AlphaGenome was "not a magic bullet for all biological questions".

This was partly because "gene expression is influenced by complex environmental factors that the model cannot see", he said.

However, the tool still represented a "breakthrough" that would allow scientists to "study and simulate the genetic roots of complex disease", Goldstone added.