Behavior is a mirror in which everyone displays his own image
{ Images generated from captions by AI models | Technology Review | full story }
{ Images generated from captions by AI models | Technology Review | full story }
The Justice Department plans to bring an antitrust case against Google as soon as this month […] A coalition of 50 states and territories support antitrust action against Google […]
Alphabet was an obvious antitrust target. Through YouTube, Google search, Google Maps and a suite of online advertising products, consumers interact with the company nearly every time they search for information, watch a video, hail a ride, order delivery in an app or see an ad online. Alphabet then improves its products based on the information it gleans from every user interaction, making its technology even more dominant.
Google controls about 90 percent of web searches globally, and rivals have complained that the company extended its dominance by making its search and browsing tools defaults on phones with its Android operating system. Google also captures about one-third of every dollar spent on online advertising, and its ad tools are used to supply and auction ads that appear across the internet. […]
Makan Delrahim, the head of the Justice Department’s antitrust division, had pushed the department to investigate Google but was recused from the case because he represented the company in a 2007 acquisition that helped it to dominate the online advertising market.
In an unusual move, Mr. Barr placed the investigation under Jeffrey A. Rosen, the deputy attorney general, whose office would not typically oversee an antitrust case. Mr. Barr and Mr. Delrahim also disagreed on how to approach the investigation, and Mr. Barr had told aides that the antitrust division had been asleep at the switch for decades, particularly in scrutinizing the technology industry.
Mr. Rosen does have a tech background: He was the lead counsel for Netscape Communications when it filed an antitrust complaint against Microsoft in 2002.
In October, Mr. Rosen hired Ryan Shores, a veteran antitrust lawyer, to lead the review and vowed to “vigorously seek to remedy any violations of law, if any are found.”
Mr. Barr also had a counselor from his own office, Lauren Willard, join the team as his liaison. She met with staff members and requested information about the investigation. She also issued directives and made proposals about next steps.
platinum print { Robert Mapplethorpe, Coral Sea, 1983 }
Some luxury brands have started adding surveillance to their arsenal, turning to blockchains to undermine the emergence of secondary markets in a way that pays lip service to sustainability and labor ethics concerns. LVMH launched Aura in 2019, a blockchain-enabled platform for authenticating products from the Louis Vuitton, Christian Dior, Marc Jacobs, and Fenty brands, among others. Meanwhile, fashion label Stella McCartney began a transparency and data-monitoring partnership with Google for tracking garment provenance, discouraging fakes and promising to ensure the ethical integrity of supply chains. Elsewhere, a host of fashion blockchain startups, including Loomia, Vechain, and Faizod, have emerged, offering tracking technologies to assuage customer concerns over poor labor conditions and manufacturing-related pollution by providing transparency on precisely where products are made and by which subcontractors. […]
Companies such as Arianee, Dentsu and Evrythng also aim to track clothes on consumers’ bodies and in their closets. At the forefront of this trend is Eon, which with backing from Microsoft and buy-in from mainstream fashion brands such as H&M and Target, has begun rolling out the embedding of small, unobtrusive RFID tags — currently used for everything from tracking inventory to runners on a marathon course — in garments designed to transmit data without human intervention. […]
According to the future depicted by Eon and its partners, garments would become datafied brand assets administering access to surveillance-enabled services, benefits, and experiences. The people who put on these clothes would become “users” rather than wearers. In some respects, this would simply extend some of the functionality of niche wearables to garments in general. Think: swimsuits able to detect UV light and prevent overexposure to the sun, yoga pants that prompt the wearer to hold the right pose, socks that monitor for disease risks, and fitness trackers embedded into sports shirts. […]
According to one potential scenario outlined by Eon partners, a running shoe could send a stream of usage data to the manufacturer so that it could notify the consumer when the shoe “nears the end of its life.” In another, sensors would determine when a garment needs repairing and trigger an online auction among competing menders. Finally, according to another, sensors syncing with smart mirrors would offer style advice and personalized advertising.
according to its own IPO filings, Uber can only be profitable if it invents fully autonomous vehicles and replaces every public transit ride in the world with them.
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Elon Musk - a man whose “green electric car company” is only profitable thanks to the carbon credits it sells to manufacturers of the dirtiest SUVs in America, without which those planet-killing SUVs would not exist - makes the same mistake. Musk wants to abolish public transit and replace it with EVs […]
Now, both Uber and Musk are both wrong as a matter of simple geometry. Multiply the space occupied by all those AVs by the journeys people in cities need to make by the additional distances of those journeys if we need road for all those cars, and you run out of space.
related { In this work of speculative fiction author Cory Doctorow takes us into a near future where the roads are solely populated by self-driving cars. }
related { Why Uber Still Can’t Make a Profit }
aluminum, acrylic paint, and LCD screen, sound { Tony Oursler [ s~iO. ], 2017 }
{ Malmö-based startup Bitcraze has come up with a way to pre-program their tiny 27 gram drones to work autonomously, enabling them to fly in science fiction-like coordinated swarms of up to 49 units at a time. | The Local | full story }
related { Autonomous killer drones }
A powerful antibiotic that kills some of the most dangerous drug-resistant bacteria in the world has been discovered using artificial intelligence.
On Monday, the Justice Department announced that it was charging four members of China’s People’s Liberation Army with the 2017 Equifax breach that resulted in the theft of personal data of about 145 million Americans.
Using the personal data of millions of Americans against their will is certainly alarming. But what’s the difference between the Chinese government stealing all that information and a data broker amassing it legally without user consent and selling it on the open market? Both are predatory practices to invade privacy for insights and strategic leverage. […]
Equifax is eager to play the hapless victim in all this. […] “The attack on Equifax was an attack on U.S. consumers as well as the United States,” [Equifax’s chief executive] said. […]
According to a 2019 class-action lawsuit, the company’s cybersecurity practices were a nightmare. The suit alleged that “sensitive personal information relating to hundreds of millions of Americans was not encrypted, but instead was stored in plain text” and “was accessible through a public-facing, widely used website.” Another example of the company’s weak safeguards, according to the suit, shows the company struggling to use a competent password system. “Equifax employed the username ‘admin’ and the password ‘admin’ to protect a portal used to manage credit disputes,” it read.
Though the attack was quite sophisticated — the hackers sneaked out information in small, hard to detect chunks and routed internet traffic through 34 servers in over a dozen countries to cover their tracks — Equifax’s apparent carelessness made it a perfect target.
According to a 2019 class-action lawsuit, the company’s cybersecurity practices were a nightmare. The suit alleged that “sensitive personal information relating to hundreds of millions of Americans was not encrypted, but instead was stored in plain text” and “was accessible through a public-facing, widely used website.” Another example of the company’s weak safeguards, according to the suit, shows the company struggling to use a competent password system. “Equifax employed the username ‘admin’ and the password ‘admin’ to protect a portal used to manage credit disputes,” it read.
The takeaway: While almost anything digital is at some risk of being hacked, the Equifax attack was largely preventable.
related { The End of Privacy as We Know It? }
related { The FBI downloaded CIA’s hacking tools using Starbuck’s WiFi }
{ Google Maps utilizes GPS and location data from mobile devices to determine if there is traffic congestion on a particular street. The app will then redirect users to less trafficked streets to avoid traffic. Using a hand cart filled with 99 active cell phones connected to Google Maps, artist Simon Weckert showed how he could create fake traffic jams in Google Maps simply by walking around the streets of Berlin. | Bleeping Computer | Continue reading }
Several delivery services, including Postmates, Seamless, Grubhub, and DoorDash, offer food from restaurants without their explicit permission. The delivery apps pull up restaurant menus listed online, from which customers make their selections, and couriers working for the apps place orders on their behalf. The process essentially inserts third-party apps as middlemen into a service many restaurants say they want control over, or wish to opt out of entirely.
Old emails, photos and files from years past sit undisturbed, awaiting a search […] The problem is that all those messages require energy to preserve them. […]
Right now, data centers consume about 2 percent of the world’s electricity, but that is expected to reach 8 percent by 2030. Moreover, only about 6 percent of all data ever created is in active use today, according to research from Hewlett Packard Enterprise. That means 94 percent is sitting in a vast “landfill” with a massive carbon footprint.
“It’s costing us the equivalent of maintaining the airline industry for data we don’t even use”
The latest research, published on Friday by two psychology professors, combs through about 40 studies that have examined the link between social media use and both depression and anxiety among adolescents. That link, according to the professors, is small and inconsistent. […]
In most cases, [most researchers] say, the phone is just a mirror that reveals the problems a child would have even without the phone. […]
“The current dominant discourse around phones and well-being is a lot of hype and a lot of fear,” Mr. Hancock said. “But if you compare the effects of your phone to eating properly or sleeping or smoking, it’s not even close.”
Mr. Hancock’s analysis of about 226 studies on the well-being of phone users concluded that “when you look at all these different kinds of well-being, the net effect size is essentially zero.”
Army researchers have developed an artificial intelligence and machine learning technique that produces a visible face image from a thermal image of a person’s face captured in low-light or nighttime conditions. This development could lead to enhanced real-time biometrics and post-mission forensic analysis for covert nighttime operations.
The prospect of data-driven ads, linked to expressed preferences by identifiable people, proved in this past decade to be irresistible. From 2010 through 2019, revenue for Facebook has gone from just under $2 billion to $66.5 billion per year, almost all from advertising. Google’s revenue rose from just under $25 billion in 2010 to just over $155 billion in 2019. Neither company’s growth seems in danger of abating.
The damage to a healthy public sphere has been devastating. All that ad money now going to Facebook and Google once found its way to, say, Conde Nast, News Corporation, the Sydney Morning Herald, NBC, the Washington Post, El País, or the Buffalo Evening News. In 2019, more ad revenue flowed to targeted digital ads in the U.S. than radio, television, cable, magazine, and newspaper ads combined for the first time. It won’t be the last time. Not coincidentally, journalists are losing their jobs at a rate not seen since the Great Recession.
Meanwhile, there is growing concern that this sort of precise ad targeting might not work as well as advertisers have assumed. Right now my Facebook page has ads for some products I would not possibly ever desire.
{ Slate | Continue reading | Thanks Tim }
Facebook said on Friday that it had removed hundreds of accounts with ties to the Epoch Media Group. […] Researchers said the profiles used photos generated by artificial intelligence. […]
The people behind the network of 610 Facebook accounts, 89 Facebook Pages, 156 Groups and 72 Instagram accounts posted about political news and issues in the United States, including President Trump’s impeachment, conservative ideology, political candidates, trade and religion. “This was a large, brazen network that had multiple layers of fake accounts and automation that systematically posted content with two ideological focuses: support of Donald Trump and opposition to the Chinese government,” Mr. Brookie said in an interview. […]
The people behind the network used artificial intelligence to generate profile pictures, Facebook said. They relied on a type of artificial intelligence called generative adversarial networks. These networks can, through a process called machine learning, teach themselves to create realistic images of faces, even though they do not belong to a real person. […] This A.I. technique did not actually make it harder for the company’s automated systems to detect the fakes, because the systems focus on patterns of behavior among accounts. […] Facebook said the accounts masked their activities by using a combination of fake and authentic American accounts to manage pages and groups on the platforms.
photo { Ian Strange, SOS, 2015-2017 }
Drunk shopping could be a $45bn /year industry, and only 6% of people regret their drunk purchases.
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In 2017 Google and Facebook lost $100 million between them to one scammer who sent them fake invoices.
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Using machine learning, researchers can now predict how likely an individual is to be involve in a car accident by looking at the image of their home address on Google Street View.
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Drug names are changing: X and Z names (Prozac, Seroxat) are giving way to names ending in O or A (Natesto, Qsymia) which are more appealing to speakers of Romance languages in Europe and South America.
[We] discovered at least 450 websites in a network of local and business news organizations, each distributing thousands of algorithmically generated articles and a smaller number of reported stories. Of the 450 sites we discovered, at least 189 were set up as local news networks across ten states within the last twelve months by an organization called Metric Media. […]
Titles like the East Michigan News, Hickory Sun, and Grand Canyon Times have appeared on the web ahead of the 2020 election. These networks of sites can be used in a variety of ways: as ‘stage setting’ for events, focusing attention on issues such as voter fraud and energy pricing, providing the appearance of neutrality for partisan issues, or to gather data from users that can then be used for political targeting. […]
Some of these mysterious, partisan local news sites publish physical newspapers and many have minimal social media presence. At first, they do not appear to be owned by the same network or organization, but a number of clues suggest that they are intimately linked. Our analysis demonstrates the links between the networks by identifying shared markers, such as unique analytics tokens, server IP addresses, and even shared design templates and bylines on articles. Further, the Privacy Policy and Terms of Service for many of these websites—but not all—suggest they are part of Locality Labs, LLC.
still { Martin Kersels, Pink Constellation, 2001 }
In 2016, London-based DeepMind Technologies, a subsidiary of Alphabet (which is also the parent company of Google), startled industry watchers when it reported that the application of artificial intelligence had reduced the cooling bill at a Google data center by a whopping 40 percent. What’s more, we learned that year, DeepMind was starting to work with the National Grid in the United Kingdom to save energy throughout the country using deep learning to optimize the flow of electricity.
Could AI really slash energy usage so profoundly? In the three years that have passed, I’ve searched for articles on the application of AI to other data centers but find no evidence of important gains. What’s more, DeepMind’s talks with the National Grid about energy have broken down. And the financial results for DeepMind certainly don’t suggest that customers are lining up for its services: For 2018, the company reported losses of US $571 million on revenues of $125 million, up from losses of $366 million in 2017. Last April, The Economist characterized DeepMind’s 2016 announcement as a publicity stunt, quoting one inside source as saying, “[DeepMind just wants] to have some PR so they can claim some value added within Alphabet.” […]
Many of McKinsey’s estimates were made by extrapolating from claims made by various startups. For instance, its prediction of a 10 percent improvement in energy efficiency in the U.K. and elsewhere was based on the purported success of DeepMind and also of Nest Labs, which became part of Google’s hardware division in 2018. In 2017, Nest, which makes a smart thermostat and other intelligent products for the home, lost $621 million on revenues of $726 million. That fact doesn’t mesh with the notion that Nest and similar companies are contributing, or are poised to contribute, hugely to the world economy.