Caroline Haskins, writing for The Outline: Hundreds of multi-ton liabilities -- soaring faster than the speed of sound, miles above the surface of the earth -- are operating on Windows-95. They're satellites, responsible for everything from GPS positioning, to taking weather measurements, to carrying cell signals, to providing television and internet. For the countries that own these satellites, they're invaluable resources. Even though they're old, it's more expensive to take satellites down than it is to just leave them up. So they stay up. Unfortunately, these outdated systems makes old satellites prime targets for cyber attacks. [...]

A malicious actor could fake their IP address, which gives information about a user's computer and its location. This person could then get access to the satellite's computer system, and manipulate where the satellite goes or what it does. Alternatively, an actor could jam the satellite's radio transmissions with earth, essentially disabling it. The cost of such an attack could be huge. If a satellite doesn't work, life-saving GPS or online information could be withheld to people on earth when they need it most. What's worse, if part of a satellite -- or an entire satellite -- is knocked out of its orbit from an attack, the debris could create a domino effect and cause extreme damage to other satellites.

An anonymous reader quotes the New York Times: Riots and lynchings around the world have been linked to misinformation and hate speech on Facebook, which pushes whatever content keeps users on the site longest -- a potentially damaging practice in countries with weak institutions and histories of social instability. Time and again, communal hatreds overrun the newsfeed unchecked as local media are displaced by Facebook and governments find themselves with little leverage over the company. Some users, energized by hate speech and misinformation, plot real-world attacks.

A reconstruction of Sri Lanka's descent into violence, based on interviews with officials, victims and ordinary users caught up in online anger, found that Facebook's newsfeed played a central role in nearly every step from rumor to killing. Facebook officials, they say, ignored repeated warnings of the potential for violence, resisting pressure to hire moderators or establish emergency points of contact... Sri Lankans say they see little evidence of change. And in other countries, as Facebook expands, analysts and activists worry they, too, may see violence.
A Facebook spokeswoman countered that "we remove such content as soon as we're made aware of it," and said they're now trying to expand those teams and investing in "technology and local language expertise to help us swiftly remove hate content." But one anti-hate group told the Times that Facebook's reporting tools are too slow and ineffective.

"Though they and government officials had repeatedly asked Facebook to establish direct lines, the company had insisted this tool would be sufficient, they said. But nearly every report got the same response: the content did not violate Facebook's standards."

An anonymous reader shares an excerpt from a report written by Scott E. Page, who explains why hiring the "best" people produces the least creative results: The burgeoning of teams -- most academic research is now done in teams, as is most investing and even most songwriting (at least for the good songs) -- tracks the growing complexity of our world. We used to build roads from A to B. Now we construct transportation infrastructure with environmental, social, economic, and political impacts. The complexity of modern problems often precludes any one person from fully understanding them. The multidimensional or layered character of complex problems also undermines the principle of meritocracy: The idea that the "best person" should be hired. There is no best person. When putting together an oncological research team, a biotech company such as Gilead or Genentech would not construct a multiple-choice test and hire the top scorers, or hire people whose resumes score highest according to some performance criteria. Instead, they would seek diversity. They would build a team of people who bring diverse knowledge bases, tools and analytic skills. That team would more likely than not include mathematicians (though not logicians such as Griffeath). And the mathematicians would likely study dynamical systems and differential equations.

Believers in a meritocracy might grant that teams ought to be diverse but then argue that meritocratic principles should apply within each category. Thus the team should consist of the "best" mathematicians, the "best" oncologists, and the "best" biostatisticians from within the pool. That position suffers from a similar flaw. Even with a knowledge domain, no test or criteria applied to individuals will produce the best team. Each of these domains possesses such depth and breadth, that no test can exist. When building a forest, you do not select the best trees as they tend to make similar classifications. You want diversity. Programmers achieve that diversity by training each tree on different data, a technique known as bagging. They also boost the forest 'cognitively' by training trees on the hardest cases -- those that the current forest gets wrong. This ensures even more diversity and accurate forests.

According to a new study by Uber and Stanford economists, male Uber drivers get paid 7 percent more than their female counterparts in the U.S. "That's surprising, because Uber's driver assignments and pay are gender-blind, meaning a driver's gender isn't considered when matching riders or assigning fares," reports Recode. "Rather, pay has to do with trip length, distance and whether it's happening during surge-price hours or not." From the report: There are more male drivers -- women make up 27 percent of Uber drivers in the U.S. -- and male drivers tend to work longer hours. However, on an hourly rate, women still make less, according to the data, which measured trips by 1.8 million drivers from 2015 to 2017. According to the study, discrimination on the customer side isn't the reason for the pay gap, either. So why are female Uber drivers paid less than men? The study points to three reasons that make the gap disappear:

When and where: The times and places female Uber drivers work seem to be less profitable. That could be fewer overnight shifts, shifts with shorter wait times or surge-price shifts than men.
Driver experience: Drivers who've been with Uber longer get paid more, on account of knowing which routes and times tend to pay more. In general, men work for Uber longer than women so they are more experienced. The attrition rate after six months is 77 percent for women and 65 percent for men.
Speed: Male Uber drivers conduct more trips per hour than women, meaning they're actually driving faster, according to the data. More trips mean more money. About 50 percent of the earnings gap is explained away by differences in driving speed.

Samantha Cole, reporting for Motherboard: In December, Motherboard discovered a Redditor named 'deepfakes' quietly enjoying his hobby: Face-swapping celebrity faces onto porn performers' bodies. He made several convincing porn videos of celebrities -- including Gal Gadot, Maisie Williams, and Taylor Swift -- using a machine learning algorithm, his home computer, publicly available videos, and some spare time. Since we first wrote about deepfakes, the practice of producing AI-assisted fake porn has exploded. More people are creating fake celebrity porn using machine learning, and the results have become increasingly convincing. A redditor even created an app specifically designed to allow users without a computer science background to create AI-assisted fake porn. All the tools one needs to make these videos are free, readily available, and accompanied with instructions that walk novices through the process.

An anonymous reader quotes GeekWire: The first Amazon Go grocery and convenience store will open to the public Monday in Seattle -- letting any person with an Amazon account, the Amazon Go app and a willingness to give up more of their personal privacy than usual simply grab anything they want and walk out, without going through a checkout line... After shoppers check in by scanning their unique QR code, overhead cameras work with weight sensors in the shelves to precisely track which items they pick up and take with them. When they leave, they just leave. Amazon Go's systems automatically debit their accounts for the items they take, sending the receipt to the app. In my first test of Amazon Go this past week, my elapsed time in the store was exactly 23 seconds -- from scanning the QR code at the entrance to exiting with my chosen item...

The company says the tracking is precise enough to distinguish between multiple people standing side-by-side at a shelf, detecting which one picked up a yogurt or cupcake, for example, and which one was merely browsing. The system also knows when people pick up items and put them back, ensuring that Amazon doesn't dock anyone's account for milk or chips when they simply wanted to read the label. The idea is to "push the boundaries of computer vision and machine learning" to create an "effortless experience for customers," said Dilip Kumar, Amazon Go vice president of technology, after taking GeekWire through the store this past week... Apart from the kitchen staff preparing fresh food at the back, we saw only two workers in the 1,800-square-foot Amazon Go store during our visit: one at the beer and wine section to check IDs, and another just inside the entrance to greet customers.
TechCrunch calls it "Amazon's surveillance-powered no-checkout convenience store," adding "the system is made up of dozens and dozens of camera units mounted to the ceiling, covering and recovering every square inch of the store from multiple angles."

The Seattle Times reports that the store "was also criticized by grocery-store workers' unions, which feared an effort to automate the work done by cashiers, the second-most-common job in the U.S."