Group items matching

in title, tags, annotations or url

""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.""

"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"."

"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"."

"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."

"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."

"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."

"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."

"Unlike other face recognition technology, their algorithm allows quick searches in big data sets. "Three million searches in a database of nearly 1bn photographs: that's hundreds of trillions of comparisons, and all on four normal servers. With this algorithm, you can search through a billion photographs in less than a second from a normal computer," said Kabakov, during an interview at the company's modest central Moscow office. The app will give you the most likely match to the face that is uploaded, as well as 10 people it thinks look similar."

"Should we embrace these new trust algorithms? Baveja and Shapiro acknowledge the responsibility that comes with trying to take ethical decisions and translate them into code. How much of our personal information do we want trawled through in this way? And how comfortable are we with letting an algorithm judge who is trustworthy?"

"Concerns have been growing about AI's so-called "white guy problem" and now scientists have devised a way to test whether an algorithm is introducing gender or racial biases into decision-making."

"There's an increasingly popular solution to this problem: why not let an intelligent algorithm make hiring decisions for you? Surely, the thinking goes, a computer is more able to be impartial than a person, and can simply look at the relevant data vectors to select the most qualified people from a heap of applications, removing human bias and making the process more efficient to boot."

"The algorithm behind what3words took six months to write. Sheldrick worked on it with two friends he had grown up with. Mohan Ganesalingham, a maths fellow at Trinity College, Cambridge, and Jack Waley-Cohen, a full-time quiz obsessive and question-setter for Only Connect. After the initial mapping was complete, they incorporated an error-correction algorithm, which places similar-sounding combinations a very long way apart."

"MIT researcher's at CSAIL have developed a lane-changing algorithm for self-driving cars. the algorithm allows for aggressive lane changes much like the kind only real drivers would be capable of.   it works by computing 'buffer zones' around autonomous vehicles and reassessing them on the fly. MIT uses a mathematically efficient approach which calculates new buffer zones if the default buffer zones lead to performance that's far worse than a human's driver."

"And that was a genuine first - the only time I can recall when an algorithmic decision had been challenged in public protests that were powerful enough to prompt a government climbdown. In a world increasingly - and invisibly - regulated by computer code, this uprising might look like a promising precedent."

"But users began to spot flaws in the feature over the weekend. The first to highlight the issue was PhD student Colin Madland, who discovered the issue while highlighting a different racial bias in the video-conference software Zoom. When Madland, who is white, posted an image of himself and a black colleague who had been erased from a Zoom call after its algorithm failed to recognise his face, Twitter automatically cropped the image to only show Madland."

"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"But the documents show that the company relies heavily on the intervention of a small editorial team to determine what makes its "trending module" headlines - the list of news topics that shows up on the side of the browser window on Facebook's desktop version. The company backed away from a pure-algorithm approach in 2014 after criticism that it had not included enough coverage of unrest in Ferguson, Missouri, in users' feeds."

"Bitcoin mining - the process in which a bitcoin is awarded to a computer that solves a complex series of algorithms - is a deeply energy-intensive process. "Mining" bitcoin involves solving complex math problems in order to create new bitcoins. Miners are rewarded in bitcoin. Earlier in bitcoin's relatively short history - the currency was created in 2009 - one could mine bitcoin on an average computer. But the way bitcoin mining has been set up by its creator (or creators - no one really knows for sure who created it) is that there is a finite number of bitcoins that can be mined: 21m. The more bitcoin that is mined, the harder the algorithms that must be solved to get a bitcoin become."

The ensuing controversy has sparked renewed debates about the ways in which algorithms can perpetuate biases, yielding unintended and often offensive results.

"Amazon's algorithms encourage customers pay more than they need to for popular products and appear to give more prominence to items that benefit the retail giant, according to an investigation by ProPublica. The investigation looked at 250 frequently purchased products over several weeks to see which ones were chosen to appear in the highly-prized "buy box" that pops up first as a suggested purchase. "