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""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."

"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."

"TikTok's algorithm is famously effective, yet hard to study. As part of the Guardian's special series on the platform's explosive rise, we tested how the algorithm treats different users. We wondered what would happen if three people - with varying ages, backgrounds, and familiarity with the platform - created new accounts and recorded what they saw."

"How that effects systems of governance has yet to be fully explored, but there are cautions. "Algorithms are only as good as the data on which they are based, and the problem with current AI is that it was trained on data that was incomplete or unrepresentative and the risk of bias or unfairness is quite substantial," says West. The fairness and equity of algorithms are only as good as the data-programming that underlie them. "For the last few decades we've allowed the tech companies to decide, so we need better guardrails and to make sure the algorithms respect human values," West says. "We need more oversight.""

"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."

"The first paper turns the tables on the trend for job applicants to be screened by algorithms. The researchers assigned some applicants "algorithmic writing assistance" with their CVs or covering letters to see if it influenced employers' decisions. But obviously those of us who do lots of recruiting would never be affected by such small changes… would we? I'm afraid so. Jobseekers who had the tech help were 8% more likely to get hired. Sigh."

"The folks at Signal are taking one of the four post-quantum cryptography algorithms that have been chosen by the US National Institute of Standards and Technology to withstand attacks by quantum computers, but instead of using it to replace their existing public-key encryption system, they are layering the new algorithm on top of what they already have. "We are augmenting our existing cryptosystems," they say, "such that an attacker must break both systems in order to compute the keys protecting people's communications." And they will be rolling out this augmented system to all users in the next few months."

"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."