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"The algorithm, called Compas (Correctional Offender Management Profiling for Alternative Sanctions), is used throughout the US to weigh up whether defendants awaiting trial or sentencing are at too much risk of reoffending to be released on bail. Since being developed in 1998, the tool is reported to have been used to assess more than one million defendants. But a new paper has cast doubt on whether the software's predictions are sufficiently accurate to justify its use in potentially life-changing decisions."

"the facial recognition system was tested by disney research using infrared hi-def cameras that capture people's faces while watching movies like 'big hero 6', 'the jungle book' and 'star wars: the force awakens'. the results showcased 16 million facial landmarks from 3,179 viewers demonstrating a 'very strong predictive performance'. to do so, the AI software takes the faces of people and understands how many of them are laughing, how wide are their eyes, and the different expressions they make."

"It is in the nature of AI that makers do not, and often cannot, predict what their creations do. We know how to make machines learn. But programmers do not understand completely the knowledge that intelligent computing acquires. If we did, we wouldn't need computers to learn to learn."

"The arcane nature of "protein folding", a mind-boggling form of molecular origami, is rarely discussed outside scientific circles, but it is a problem of profound importance. The machinery of biology is built from proteins and it a protein's shape defines its function. Understand how proteins fold up and researchers could usher in a new era of scientific and medical progress."

"As colleges come under unprecedented pressure to downsize, from the pandemic as well as the steep enrollment decline that was already projected for 2025, some professors predict that the shift online might reinforce "corporate university" tendencies to track professors' productivity and use the results as an excuse to lay them off."

"An AI system developed by Chinese tech company Baidu that uses an infrared sensor and AI to predict people's temperatures is now in use in Beijing's Qinghe Railway Station, according to an email sent to Baidu employees that was shared with VentureBeat."

"The system uses AI to predict situations before they occur - thus informing on how resources could be better allocated - and to provide insights for better decision-making."

"In the future, the team predict the software could also learn the appropriate emotion to express at a given time. "It could be mostly empathic," said Huang, adding that a challenge would be to avoid the chatbot reinforcing negative feelings such as rage."

"Robots will begin replacing teachers in the classroom within the next 10 years as part of a revolution in one-to-one learning, a leading educationist has predicted. Sir Anthony Seldon, vice-chancellor of the University of Buckingham, said intelligent machines that adapt to suit the learning styles of individual children would soon render traditional academic teaching all but redundant."

"Computers once performed facial recognition rather imprecisely, by identifying people's facial features and measuring the distances among them - a crude method that did not reliably result in matches. But recently, the technology has improved significantly, because of advances in artificial intelligence. A.I. software can analyze countless photos of people's faces and learn to make impressive predictions about which images are of the same person; the more faces it inspects, the better it gets. Clearview is deploying this approach using billions of photos from the public internet. By testing legal and ethical limits around the collection and use of those images, it has become the front-runner in the field. "

"Consider abstract art. We've noted that machine learning, in aiming to make an accurate prediction, constructs a high-dimensional feature space that contorts and reconfigures the data representing features of the natural world. Likewise, artists "mash and rip" features of visual reality to create a system of forms, texture, and color that richly represent features of visual experience in an alien way. The subject of representation is abstracted but represented none-the-less. "

"In 2015, a research group fed an AI system called Deep Patient health and medical data from some 700,000 people, and tested whether it could predict diseases. It could, but Deep Patient provides no explanation for the basis of a diagnosis, and the researchers have no idea how it comes to its conclusions. A doctor either can either trust or ignore the computer, but that trust will remain blind."

"A widely used algorithm that predicts which patients will benefit from extra medical care dramatically underestimates the health needs of the sickest black patients, amplifying long-standing racial disparities in medicine, researchers have found."

"The battle over algorithms in healthcare has come into full view since last fall. The debate only intensified in the wake of the coronavirus pandemic, which has disproportionately devastated Black and Latino communities. In October, Science published a study that found one hospital unintentionally directed more white patients than Black patients to a high-risk care management program because it used an algorithm to predict the patients' future healthcare costs as a key indicator of personal health. Optum, the company that sells the software product, told Mashable that the hospital used the tool incorrectly. "

"The models work by dividing maps into what Google calls "supersegments" "

"Over the years critics have pointed out their many shortcomings as well. Perhaps the biggest flaw of all is that the laws are vague. If machines become so human that we find it difficult to tell them and us apart, how will a machine tell the difference? Where does humanity end and artificial intelligence begin? And even if an AI can distinguish itself from a human being, we also cannot know what loopholes and reprogramming a robot is capable of. Surely an AI more clever than us could plan a way to access its core and bypass any of its existing limitations."

"Mentor is made by eDriving, which describes the app on its website as a "smartphone-based solution that collects and analyzes driver behaviors most predictive of crash risk and helps remediate risky behavior by providing engaging, interactive micro-training modules delivered directly to the driver in the smartphone app." But CNBC talked to drivers who said the app mostly invades their privacy or miscalculates dangerous driving behavior. One driver said even though he didn't answer a ringing phone, the app docked points for using a phone while driving. Another worker was flagged for distracted driving at every delivery stop she made. The incorrect tracking has real consequences. ranging from restricted payouts and bonuses to job loss. "

"Raji says her investigation into the data has made her gravely concerned about deep-learning-based facial recognition. "It's so much more dangerous," she says. "The data requirement forces you to collect incredibly sensitive information about, at minimum, tens of thousands of people. It forces you to violate their privacy. That in itself is a basis of harm. And then we're hoarding all this information that you can't control to build something that likely will function in ways you can't even predict. That's really the nature of where we're at.""

"As the lava lamps bubble and swirl, a video camera on the ceiling monitors their unpredictable changes and connects the footage to a computer, which converts the randomness into a virtually unhackable code.  Why use lava lamps for encryption instead of computer-generated code? Since computer codes are created by machines with relatively predictable patterns, it is entirely possible for hackers to guess their algorithms, posing a security risk. Lava lamps, on the other hand, add to the equation the sheer randomness of the physical world, making it nearly impossible for hackers to break through."

"Admission algorithms can make or break your academic plans. A Washington Post investigation found 44 schools use prediction software to give applicants a score out of 100 for its admissions process. The score considers different aspects of a student's application from test scores, home address, transcripts, and even what websites they've visited. That's all calculated to rate how strong of a match a student is for a school."