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"DeepMind is trying to combine deep learning and algorithms, creating the one algorithm to rule them all: a deep learning model that can learn how to emulate any algorithm, generating an algorithm-equivalent model that can work with real-world data."

"A preliminary study finds that facial recognition algorithms struggle to identify people wearing masks. The study tested 89 commercial facial recognition algorithms, and the best had error rates between 5% and 50% in matching unmasked photos with photos of the same person wearing a digitally-applied mask. Masks both lowered the algorithms' accuracy rates and raised the number of failures to process. The more of the nose is covered by the mask the lower the algorithm's accuracy; however, error rates were generally lower with round masks; and the algorithms generally performed worse with black masks than with surgical blue ones. False positive remained stable or declined a small amount."

""In some ways we've lost agency. When programs pass into code and code passes into algorithms and then algorithms start to create new algorithms, it gets farther and farther from human agency. Software is released into a code universe which no one can fully understand.""

""Weapons of math destruction" is how the writer Cathy O'Neil describes the nasty and pernicious kinds of algorithms that are not subject to the same challenges that human decision-makers are. Parole algorithms (not Jure's) can bias decisions on the basis of income or (indirectly) ethnicity. Recruitment algorithms can reject candidates on the basis of mistaken identity. In some circumstances, such as policing, they might create feedback loops, sending police into areas with more crime, which causes more crime to be detected."

"Twitter's image cropping algorithm prefers younger, slimmer faces with lighter skin, an investigation into algorithmic bias at the company has found. The finding, while embarrassing for the company, which had previously apologised to users after reports of bias, marks the successful conclusion of Twitter's first ever "algorithmic bug bounty"."

"Other far more sinister real-world effects of algorithms are well documented. In the US, pedestrians have been mowed down by robotaxis; prisoners denied bail on the advice, in part, of software; in Australia, welfare recipients incorrectly and illegally hounded by an algorithmic debt collector that came to be known as robodebt. In the UK, students took to the streets in 2020 after being denied places at universities by the calculations of digital minions - their chants of "fuck the algorithm" proving a "defining moment" for Kowalkiewicz and an inspiration for his book."

"In October 2016, algorithms reacted to negative news headlines about Brexit negotiations by sending the pound down 6% against the dollar in under two minutes, before recovering almost immediately. Knowing which particular headline, or which particular algorithm, caused the crash is next to impossible. When one haywire algorithm started placing and cancelling orders that ate up 4% of all traffic in US stocks in October 2012, one commentator was moved to comment wryly that "the motive of the algorithm is still unclear"."

"When Google's algorithms result in men on the Internet seeing better-paying job advertisements than women, it's worth looking under the hood at the assumptions that the algorithms, and the people behind it, have made. "

"Unlike other companies, Zebra's algorithms provide an actual diagnosis, completely automatically using only imaging data. This is a very new field - older technology was always driven by the radiologist, and never automatic. The algorithms are part of the Zebra Analytics Platform - a cloud based analytics engine that receives medical imaging studies, analyzes them and returns results to participating hospitals and physicians."

"Indeed, a recent working paper in the area of machine learning suggests that the simpler the algorithm, the more likely its outcome will further disadvantage already disadvantaged groups. In other words, our social relationships are complex, and our algorithms should be, too. But in the quest to streamline processes, they aren't always, and that can be a huge problem."

"But the answer to how he was chosen is actually an algorithm, a computer program that crunched through reams of data, looking at how much each passenger had paid for their ticket, what time they checked in, how often they flew on United, and whether they were part of a rewards program. The algorithm likely determined that Dr. Dao was one of the least valuable customers on the flight at the time."

"On inbuilt bias in algorithms, Sharkey said: "There are so many biases happening now, from job interviews to welfare to determining who should get bail and who should go to jail. It is quite clear that we really have to stop using decision algorithms, and I am someone who has always been very light on regulation and always believed that it stifles innovation."

"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. "

"Algorithms and the data that drive them are designed and created by people, which means those systems can carry biases based on who builds them and how they're ultimately deployed. Safiya Umoja Noble, author of Algorithms of Oppression: How Search Engines Reinforce Racism, offers a curated reading list exploring how technology can replicate and reinforce racist and sexist beliefs, how that bias can affect everything from health outcomes to financial credit to criminal justice, and why data discrimination is a major 21st century challenge."

"More algorithmic decision making and decision augmenting systems will be used in the coming years. Unlike the approach taken for A-levels, future systems may include opaque AI-led decision making. Despite such risks there remain no clear picture of how public sector bodies - government, local councils, police forces and more - are using algorithmic systems for decision making."

"Creating an algorithm that discriminates or shows bias isn't as hard as it might seem, however. As a first-year graduate student, my advisor asked me to create a machine-learning algorithm to analyze a survey sent to United States physics instructors about teaching computer programming in their courses."

"Last week we reported how Facebook and Instagram's algorithms are luring young men into the Manosphere. This week, we explore what happens when TikTok's algorithm is unleashed on a blank account in the absence of any interactions such as liking or commenting. In April, Guardian Australia set up a new TikTok account on a completely blank smartphone linked to a new, unused email address. A John Doe profile was set up as a generic 24-year-old male. We scrolled through the feed every couple of weeks."

"Those changes happened relatively slowly, but it seems to me that employment disruption is accelerating. A large reason for this is that what used to be a room-sized super computer now fits in my pocket. Over the last two decades, I have observed a fundamental change in how we can apply advanced algorithms to sensing and controlling systems-the kinds of technology that enable more sophisticated robotic manufacturing. I can remember discussing various algorithms and believing they were well beyond what we could ever implement. Now these same algorithms are considered elementary. They are just some of the changes that have fueled the revolution in manufacturing."

"The algorithm at play is performing what's commonly referred to as predictive policing. Using years - and sometimes decades - worth of crime reports, the algorithm analyses the data to identify areas with high probabilities for certain types of crime, placing little red boxes on maps of the city that are streamed into patrol cars."

"On the contrary, building large centralized databases and predictive algorithms that make decisions on behalf of humans, and which completely ignore privacy concerns, now seem to be the most efficient way of governing. Algorithms now handle college admissions processes, applicants' selection processes for jobs, where to go to college, what to study in that college, which city is best for you to start your career and raise a family, what part of that city you should live in, and even who you should marry."