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When Does Predictive Technology Become Unethical?

#artificialintelligence

Machine learning can ascertain a lot about you -- including some of your most sensitive information. For instance, it can predict your sexual orientation, whether you're pregnant, whether you'll quit your job, and whether you're likely to die soon. Researchers can predict race based on Facebook likes, and officials in China use facial recognition to identify and track the Uighurs, a minority ethnic group. Now, do the machines actually "know" these things about you, or are they only making informed guesses? And, if they're making an inference about you, just the same as any human you know might do, is there really anything wrong with them being so astute?


When Does Predictive Technology Become Unethical?

#artificialintelligence

Machine learning can correctly guess a lot about you -- including some of your most sensitive information. For instance, it can reliably predict your sexual orientation, whether you're pregnant, whether you'll quit your job, and whether you're likely to die soon. Researchers can predict race based on Facebook likes, and officials in China use facial recognition to identify and track the Uighurs, a minority ethnic group. Now, do the machines actually "know" these things about you, or are they only making informed guesses? And, if they're making an inference about you, just the same as any human you know might do, is there really anything wrong with them being so astute?


Activists Turn Facial Recognition Tools Against the Police

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Mr. Howell was offended by Mr. Wheeler's characterization of his project but relieved he could keep working on it. "There's a lot of excessive force here in Portland," he said in a phone interview. "Knowing who the officers are seems like a baseline." Mr. Howell, 42, is a lifelong protester and self-taught coder; in graduate school, he started working with neural net technology, an artificial intelligence that learns to make decisions from data it is fed, such as images. He said that the police had tear-gassed him during a midday protest in June, and that he had begun researching how to build a facial recognition product that could defeat officers' attempts to shield their identity.


Photoshop's AI neural filters can tweak age and expression with a few clicks

#artificialintelligence

Artificial intelligence is changing the world of image editing and manipulation, and Adobe doesn't want to be left behind. Today, the company is releasing an update to Photoshop version 22.0 that comes with a host of AI-powered features, some new, some already shared with the public. These include a sky replacement tool, improved AI edge selection, and -- the star of the show -- a suite of image-editing tools that Adobe calls "neural filters." These filters include a number of simple overlays and effects but also tools that allow for deeper edits, particularly to portraits. With neural filters, Photoshop can adjust a subject's age and facial expression, amplifying or reducing feelings like "joy," "surprise," or "anger" with simple sliders.


Photoshop's AI neural filters can tweak age and expression with a few clicks

#artificialintelligence

Artificial intelligence is changing the world of image editing and manipulation, and Adobe doesn't want to be left behind. Today, the company is releasing an update to Photoshop version 22.0 that comes with a host of AI-powered features, some new, some already shared with the public. These include a sky replacement tool, improved AI edge selection, and -- the star of the show -- a suite of image-editing tools that Adobe calls "neural filters." These filters include a number of simple overlays and effects but also tools that allow for deeper edits, particularly to portraits. With neural filters, Photoshop can adjust a subject's age and facial expression, amplifying or reducing feelings like "joy," "surprise," or "anger" with simple sliders.


Earphone tracks facial expressions, even with a face mask

#artificialintelligence

Cornell researchers have invented an earphone that can continuously track full facial expressions by observing the contour of the cheeks – and can then translate expressions into emojis or silent speech commands. With the ear-mounted device, called C-Face, users could express emotions to online collaborators without holding cameras in front of their faces – an especially useful communication tool as much of the world engages in remote work or learning. "This device is simpler, less obtrusive and more capable than any existing ear-mounted wearable technologies for tracking facial expressions," said Cheng Zhang, assistant professor of information science and senior author of "C-Face: Continuously Reconstructing Facial Expressions by Deep Learning Contours of the Face With Ear-Mounted Miniature Cameras." The paper will be presented at the Association for Computing Machinery Symposium on User Interface Software and Technology, to be held virtually Oct. 20-23. "In previous wearable technology aiming to recognize facial expressions, most solutions needed to attach sensors on the face," said Zhang, director of Cornell's SciFi Lab, "and even with so much instrumentation, they could only recognize a limited set of discrete facial expressions."


Cornell researchers created an earphone that can track facial expressions

Engadget

Researchers from Cornell University have created an earphone system that can track a wearer's facial expressions even when they're wearing a mask. C-Face can monitor cheek contours and convert the wearer's expression into an emoji. That could allow people to, for instance, convey their emotions during group calls without having to turn on their webcam. "This device is simpler, less obtrusive and more capable than any existing ear-mounted wearable technologies for tracking facial expressions," Cheng Zhang, director of Cornell's SciFi Lab and senior author of a paper on C-Face, said in a statement. "In previous wearable technology aiming to recognize facial expressions, most solutions needed to attach sensors on the face and even with so much instrumentation, they could only recognize a limited set of discrete facial expressions."


Can facial recognition tech boost Asia's biometric acceptance?

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It was not too long ago that biometric identification methods became accepted means to authenticate a customer's identity in the financial services sector. First fingerprints became commonplace, followed by voice recognition tech. Now, facial recognition tech is becoming increasingly accepted by financial institutions, notoriously some of the hardest (and slowest) organizations to approve of new procedures, due to their tight enforcement protocols. If banks in Southeast Asia are accepting facial biometric IDs, then it's a good bet that industries that don't have such stringent standards will start looking at the technology as a means of authenticating identity, too. Facial rec software applies artificial intelligence (AI) and machine learning technologies to match a face captured on-camera against a database of millions of faces, and is usually used to identify or authorize access for an individual.


A Brief History of Facial Recognition – 1880-2001

#artificialintelligence

During your time on earth you've seen hundreds of thousands of faces. Out of all of those faces, you've most likely recognized many of them. The phrase "I'd know that face anywhere" is very relevant here. Have you ever thought about how you recognize a face? The process is much more complicated than you'd think.


Face recognition and the future air travel experience

#artificialintelligence

Airports uniquely demand both a very high passenger throughput and a very high degree of security underpinned by the positive identity confirmation of those passengers. At multiple points throughout the air travel experience, traveler identity must be confirmed to meet commercial policy, physical security, or national security requirements. This uncommon set of demands has forced innovation in the form of automated identity confirmation, primarily using biometrics. For two decades, some combination of face, fingerprint, and iris recognition has been deployed in an effort to speed up identity confirmation, with the goal of creating a secure and frictionless passenger experience. Thanks to rapid advances in Artificial Intelligence and specific technologies like Deep Learning and Convolutional Neural Networks, face recognition, in particular, has dramatically improved in the last few years.