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facial recognition unlawfully used

Facial recognition has been used unlawfully and violated human rights, UK Court of Appeal rules in landmark case from r/technology

A British police force violated human rights by unlawfully using facial recognition technology, the Court of Appeal has ruled in a landmark case.

https://www.independent.co.uk/news/uk/home-news/facial-recognition-unlawful-violation-human-rights-court-of-appeal-a9664441.html

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more on facial recognition in this IMS blog
https://blog.stcloudstate.edu/ims?s=facial+recognition

Facial Recognition issues

Chinese Facial Recognition Will Take over the World in 2019

Michael K. Spencer Jan 14, 2018
https://medium.com/futuresin/chinese-facial-recognition-will-take-over-the-world-in-2019-520754a7f966
The best facial recognition startups are in China, by a long-shot. As their software is less biased, global adoption is occurring via their software. This is evidenced in 2019 by the New York Police department in NYC for example, according to the South China Morning Post.
The mass surveillance state of data harvesting in real-time is coming. Facebook already rates and profiles us.

The Tech Wars come down to an AI-War

Whether the NYC police angle is true or not (it’s being hotly disputed), Facebook and Google are thinking along lines that follow the whims of the Chinese Government.

SenseTime and Megvii won’t just be worth $5 Billion, they will be worth many times that in the future. This is because a facial recognition data-harvesting of everything is the future of consumerism and capitalism, and in some places, the central tenet of social order (think Asia).

China has already ‘won’ the trade-war, because its winning the race to innovation. America doesn’t regulate Amazon, Microsoft, Google or Facebook properly, that stunts innovation and ethics in technology where the West is now forced to copy China just to keep up.

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more about facial recognition in schools
https://blog.stcloudstate.edu/ims/2019/02/02/facial-recognition-technology-in-schools/

Facial Recognition Technology in schools

With Safety in Mind, Schools Turn to Facial Recognition Technology. But at What Cost?

By Emily Tate     Jan 31, 2019

https://www.edsurge.com/news/2019-01-31-with-safety-in-mind-schools-turn-to-facial-recognition-technology-but-at-what-cost

SAFR (Secure, Accurate Facial Recognition)

violent deaths in schools have stayed relatively constant over the last 30 years, according to data from the National Center for Education Statistics. But then there’s the emotive reality, which is that every time another event like Sandy Hook or Parkland occurs, many educators and students feel they are in peril when they go to school.

RealNetworks, a Seattle-based software company that was popular in the 1990s for its audio and video streaming services but has since expanded to offer other tools, including SAFR (Secure, Accurate Facial Recognition), its AI-supported facial recognition software.

After installing new security cameras, purchasing a few Apple devices and upgrading the school’s Wi-Fi, St. Therese was looking at a $24,000 technology tab.

The software is programmed to allow authorized users into the building with a smile.

“Facial recognition isn’t a panacea. It is just a tool,” says Collins, who focuses on education privacy issues.

Another part of the problem with tools like SAFR, is it provides a false sense of security.

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more on surveillance in this IMS blog
https://blog.stcloudstate.edu/ims?s=surveillance

more on privacy in this IMS blog
https://blog.stcloudstate.edu/ims?s=privacy

College Students Privacy

Today’s College Students Care About Privacy — Despite Some of Their Online Actions

https://www.edsurge.com/news/2021-11-02-today-s-college-students-care-about-privacy-despite-some-of-their-online-actions

a new report from the nonprofit Future of Privacy Forum, which analyzed recent research about young adults from the U.S., China, Germany and Japan.

a study from Indiana University detailed the fears college students have about and the ways they adapt to the fact that they may be photographed at any moment by friends, classmates or even strangers.

Another worry described in the Future of Privacy Forum report is about a type of digital harassment known as “doxxing,”

Many students are loath to share biometric information with colleges and are wary about tools like facial recognition software.

What is AI

What is AI? Here’s everything you need to know about artificial intelligence

An executive guide to artificial intelligence, from machine learning and general AI to neural networks.

https://www-zdnet-com.cdn.ampproject.org/c/s/www.zdnet.com/google-amp/article/what-is-ai-heres-everything-you-need-to-know-about-artificial-intelligence/

What is artificial intelligence (AI)?

It depends who you ask.

What are the uses for AI?

What are the different types of AI?

Narrow AI is what we see all around us in computers today — intelligent systems that have been taught or have learned how to carry out specific tasks without being explicitly programmed how to do so.

General AI

General AI is very different and is the type of adaptable intellect found in humans, a flexible form of intelligence capable of learning how to carry out vastly different tasks, anything from haircutting to building spreadsheets or reasoning about a wide variety of topics based on its accumulated experience.

What can Narrow AI do?

There are a vast number of emerging applications for narrow AI:

  • Interpreting video feeds from drones carrying out visual inspections of infrastructure such as oil pipelines.
  • Organizing personal and business calendars.
  • Responding to simple customer-service queries.
  • Coordinating with other intelligent systems to carry out tasks like booking a hotel at a suitable time and location.
  • Helping radiologists to spot potential tumors in X-rays.
  • Flagging inappropriate content online, detecting wear and tear in elevators from data gathered by IoT devices.
  • Generating a 3D model of the world from satellite imagery… the list goes on and on.

What can General AI do?

A survey conducted among four groups of experts in 2012/13 by AI researchers Vincent C Müller and philosopher Nick Bostrom reported a 50% chance that Artificial General Intelligence (AGI) would be developed between 2040 and 2050, rising to 90% by 2075.

What is machine learning?

What are neural networks?

What are other types of AI?

Another area of AI research is evolutionary computation.

What is fueling the resurgence in AI?

What are the elements of machine learning?

As mentioned, machine learning is a subset of AI and is generally split into two main categories: supervised and unsupervised learning.

Supervised learning

Unsupervised learning

ai-ml-gartner-hype-cycle.jpg

Which are the leading firms in AI?

Which AI services are available?

All of the major cloud platforms — Amazon Web Services, Microsoft Azure and Google Cloud Platform — provide access to GPU arrays for training and running machine-learning models, with Google also gearing up to let users use its Tensor Processing Units — custom chips whose design is optimized for training and running machine-learning models.

Which countries are leading the way in AI?

It’d be a big mistake to think the US tech giants have the field of AI sewn up. Chinese firms Alibaba, Baidu, and Lenovo, invest heavily in AI in fields ranging from e-commerce to autonomous driving. As a country, China is pursuing a three-step plan to turn AI into a core industry for the country, one that will be worth 150 billion yuan ($22bn) by the end of 2020 to become the world’s leading AI power by 2030.

How can I get started with AI?

While you could buy a moderately powerful Nvidia GPU for your PC — somewhere around the Nvidia GeForce RTX 2060 or faster — and start training a machine-learning model, probably the easiest way to experiment with AI-related services is via the cloud.

How will AI change the world?

Robots and driverless cars

Fake news

Facial recognition and surveillance

Healthcare

Reinforcing discrimination and bias 

AI and global warming (climate change)

Will AI kill us all?

 

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more on AI in this iMS blog
https://blog.stcloudstate.edu/ims?s=artificial+intelligence+education

Algorithmic Test Proctoring

Our Bodies Encoded: Algorithmic Test Proctoring in Higher Education

SHEA SWAUGER ED-TECH

https://hybridpedagogy.org/our-bodies-encoded-algorithmic-test-proctoring-in-higher-education/

While in-person test proctoring has been used to combat test-based cheating, this can be difficult to translate to online courses. Ed-tech companies have sought to address this concern by offering to watch students take online tests, in real time, through their webcams.

Some of the more prominent companies offering these services include ProctorioRespondusProctorUHonorLockKryterion Global Testing Solutions, and Examity.

Algorithmic test proctoring’s settings have discriminatory consequences across multiple identities and serious privacy implications. 

While racist technology calibrated for white skin isn’t new (everything from photography to soap dispensers do this), we see it deployed through face detection and facial recognition used by algorithmic proctoring systems.

While some test proctoring companies develop their own facial recognition software, most purchase software developed by other companies, but these technologies generally function similarly and have shown a consistent inability to identify people with darker skin or even tell the difference between Chinese people. Facial recognition literally encodes the invisibility of Black people and the racist stereotype that all Asian people look the same.

As Os Keyes has demonstrated, facial recognition has a terrible history with gender. This means that a software asking students to verify their identity is compromising for students who identify as trans, non-binary, or express their gender in ways counter to cis/heteronormativity.

These features and settings create a system of asymmetric surveillance and lack of accountability, things which have always created a risk for abuse and sexual harassment. Technologies like these have a long history of being abused, largely by heterosexual men at the expense of women’s bodies, privacy, and dignity.

Their promotional messaging functions similarly to dog whistle politics which is commonly used in anti-immigration rhetoric. It’s also not a coincidence that these technologies are being used to exclude people not wanted by an institution; biometrics and facial recognition have been connected to anti-immigration policies, supported by both Republican and Democratic administrations, going back to the 1990’s.

Borrowing from Henry A. Giroux, Kevin Seeber describes the pedagogy of punishment and some of its consequences in regards to higher education’s approach to plagiarism in his book chapter “The Failed Pedagogy of Punishment: Moving Discussions of Plagiarism beyond Detection and Discipline.”

my note: I am repeating this for years
Sean Michael Morris and Jesse Stommel’s ongoing critique of Turnitin, a plagiarism detection software, outlines exactly how this logic operates in ed-tech and higher education: 1) don’t trust students, 2) surveil them, 3) ignore the complexity of writing and citation, and 4) monetize the data.

Technological Solutionism

Cheating is not a technological problem, but a social and pedagogical problem.
Our habit of believing that technology will solve pedagogical problems is endemic to narratives produced by the ed-tech community and, as Audrey Watters writes, is tied to the Silicon Valley culture that often funds it. Scholars have been dismantling the narrative of technological solutionism and neutrality for some time now. In her book “Algorithms of Oppression,” Safiya Umoja Noble demonstrates how the algorithms that are responsible for Google Search amplify and “reinforce oppressive social relationships and enact new modes of racial profiling.”

Anna Lauren Hoffmann, who coined the term “data violence” to describe the impact harmful technological systems have on people and how these systems retain the appearance of objectivity despite the disproportionate harm they inflict on marginalized communities.

This system of measuring bodies and behaviors, associating certain bodies and behaviors with desirability and others with inferiority, engages in what Lennard J. Davis calls the Eugenic Gaze.

Higher education is deeply complicit in the eugenics movement. Nazism borrowed many of its ideas about racial purity from the American school of eugenics, and universities were instrumental in supporting eugenics research by publishing copious literature on it, establishing endowed professorships, institutes, and scholarly societies that spearheaded eugenic research and propaganda.

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more on privacy in this IMS blog
https://blog.stcloudstate.edu/ims?s=privacy

Facial recognition technology breaches GDPR says Vestager

Margrethe Vestager, EU’s tech chief Margrethe Vestager said on Thursday that facial recognition technologies breach the need to give consent, which is stipulated in Europe’s data protection rules (GDPR).

“China might have data and the US might have money, but Europe has purpose,” the Commission’s VP for a Europe Fit for the Digital Age said.

The use of facial recognition technology remains highly controversial due to fears of China-type surveillance regimes and human rights violations, with Ursula von der Leyen, EC President pledging to distance Europe from these practices and to announcing new AI ethical and human-centred rules in the first 100 days of her mandate.

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more on facial recognition in this IMS blog
https://blog.stcloudstate.edu/ims?s=facial+recognition

AI and privacy

The Secretive Company That Might End Privacy as We Know It: It’s taken 3 billion images from the internet to build a an AI driven database that allows US law enforcement agencies identify any stranger. from r/Futurology

Until now, technology that readily identifies everyone based on his or her face has been taboo because of its radical erosion of privacy. Tech companies capable of releasing such a tool have refrained from doing so; in 2011, Google’s chairman at the time said it was the one technology the company had held back because it could be used “in a very bad way.” Some large cities, including San Francisco, have barred police from using facial

But without public scrutiny, more than 600 law enforcement agencies have started using Clearview in the past year, according to the company, which declined to provide a list. recognition technology.

Facial recognition technology has always been controversial. It makes people nervous about Big Brother. It has a tendency to deliver false matches for certain groups, like people of color. And some facial recognition products used by the police — including Clearview’s — haven’t been vetted by independent experts.

Clearview deployed current and former Republican officials to approach police forces, offering free trials and annual licenses for as little as $2,000. Mr. Schwartz tapped his political connections to help make government officials aware of the tool, according to Mr. Ton-That.

“We have no data to suggest this tool is accurate,” said Clare Garvie, a researcher at Georgetown University’s Center on Privacy and Technology, who has studied the government’s use of facial recognition. “The larger the database, the larger the risk of misidentification because of the doppelgänger effect. They’re talking about a massive database of random people they’ve found on the internet.”

Law enforcement is using a facial recognition app with huge privacy issues Clearview AI’s software can find matches in billions of internet images. from r/technology

Part of the problem stems from a lack of oversight. There has been no real public input into adoption of Clearview’s software, and the company’s ability to safeguard data hasn’t been tested in practice. Clearview itself remained highly secretive until late 2019.

The software also appears to explicitly violate policies at Facebook and elsewhere against collecting users’ images en masse.

while there’s underlying code that could theoretically be used for augmented reality glasses that could identify people on the street, Ton-That said there were no plans for such a design.

Banning Facial Recognition Isn’t Enough from r/technology

In May of last year, San Francisco banned facial recognition; the neighboring city of Oakland soon followed, as did Somerville and Brookline in Massachusetts (a statewide ban may follow). In December, San Diego suspended a facial recognition program in advance of a new statewide law, which declared it illegal, coming into effect. Forty major music festivals pledged not to use the technology, and activists are calling for a nationwide ban. Many Democratic presidential candidates support at least a partial ban on the technology.

facial recognition bans are the wrong way to fight against modern surveillance. Focusing on one particular identification method misconstrues the nature of the surveillance society we’re in the process of building. Ubiquitous mass surveillance is increasingly the norm. In countries like China, a surveillance infrastructure is being built by the government for social control. In countries like the United States, it’s being built by corporations in order to influence our buying behavior, and is incidentally used by the government.

People can be identified at a distance by their heart beat or by their gait, using a laser-based system. Cameras are so good that they can read fingerprints and iris patterns from meters away. And even without any of these technologies, we can always be identified because our smartphones broadcast unique numbers called MAC addresses.

China, for example, uses multiple identification technologies to support its surveillance state.

There is a huge — and almost entirely unregulated — data broker industry in the United States that trades on our information.

This is why many companies buy license plate data from states. It’s also why companies like Google are buying health records, and part of the reason Google bought the company Fitbit, along with all of its data.

The data broker industry is almost entirely unregulated; there’s only one law — passed in Vermont in 2018 — that requires data brokers to register and explain in broad terms what kind of data they collect.

The Secretive Company That Might End Privacy as We Know It from r/technews

Until now, technology that readily identifies everyone based on his or her face has been taboo because of its radical erosion of privacy. Tech companies capable of releasing such a tool have refrained from doing so; in 2011, Google’s chairman at the time said it was the one technology the company had held back because it could be used “in a very bad way.” Some large cities, including San Francisco, have barred police from using facial recognition technology.

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on social credit system in this IMS blog
https://blog.stcloudstate.edu/ims?s=social+credit

smart anonymization

This startup claims its deepfakes will protect your privacy

But some experts say that D-ID’s “smart video anonymization” technique breaks the law.

https://www.technologyreview.com/s/614983/this-startup-claims-its-deepfakes-will-protect-your-privacy/

The upside for businesses is that this new, “anonymized” video no longer gives away the exact identity of a customer—which, Perry says, means companies using D-ID can “eliminate the need for consent” and analyze the footage for business and marketing purposes. A store might, for example, feed video of a happy-looking white woman to an algorithm that can surface the most effective ad for her in real time.

Three leading European privacy experts who spoke to MIT Technology Review voiced their concerns about D-ID’s technology and its intentions. All say that, in their opinion, D-ID actually violates GDPR.

Surveillance is becoming more and more widespread. A recent Pew study found that most Americans think they’re constantly being tracked but can’t do much about it, and the facial recognition market is expected to grow from around $4.5 billion in 2018 to $9 billion by 2024. Still, the reality of surveillance isn’t keeping activists from fighting back.

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more on deep fake in this IMS blog
https://blog.stcloudstate.edu/ims?s=deep+fake

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