Long years have passed.
I think of goodbye.
Locked tight in the night
I think of passion;
Drawn to for blue, the night
During the page
My shattered pieces of life
watching the joy
shattered pieces of love
My shattered pieces of love
Crowdworking is often hailed by its boosters as ushering in a new age of work. With the zeal of high-tech preachers, they cast it as a space in which individualism, choice and self-determination flourish. “CrowdFlower, and others in the crowdsourcing industry, are bringing opportunities to people who never would have had them before, and we operate in a truly egalitarian fashion, where anyone who wants to can do microtasks, no matter their gender, nationality, or socio-economic status, and can do so in a way that is entirely of their choosing and unique to them,” asserts Lukas Biewald, the CEO of CrowdFlower, in an e-mail exchange. (CrowdFlower claims to have “among the largest, if not the largest, crowd” available, with roughly 100,000 workers completing tasks on any given day.)
But if you happen to be a low-end worker doing the Internet’s grunt work, a different vision arises. According to critics, Amazon’s Mechanical Turk may have created the most unregulated labor marketplace that has ever existed. Inside the machine, there is an overabundance of labor, extreme competition among workers, monotonous and repetitive work, exceedingly low pay and a great deal of scamming. In this virtual world, the disparities of power in employment relationships are magnified many times over, and the New Deal may as well have never happened.
As Miriam Cherry, one of the few legal scholars focusing on labor and employment law in the virtual world, has explained: “These technologies are not enabling people to meet their potential; they’re instead exploiting people.” Or, as CrowdFlower’s Biewald told an audience of young tech types in 2010, in a moment of unchecked bluntness: “Before the Internet, it would be really difficult to find someone, sit them down for ten minutes and get them to work for you, and then fire them after those ten minutes. But with technology, you can actually find them, pay them the tiny amount of money, and then get rid of them when you don’t need them anymore.”
Today the National Highway Safety Administration officially published two recall announcements, one from Tesla Motors and one from GM. Both are related to problems that could cause fires. In the case of GM, trucks left idling can overheat and catch fire—eight fires have been reported. In Tesla’s case, an overheating charger plug seems have to have been the cause of a fire in a garage (it’s not clear if the problem had to do with miswiring of the wall charger, damage to the plug, or something else).
Both problems can be addressed with software updates–in Tesla’s case, the software detects charging problems and decreases charging rates to avoid overheating (GM hasn’t provided details). Owners of 370,000 Chevrolet Silverado and GMC Sierra pickups will need to find time to take their pickups to the dealer to get the software fixed. But because of its ability to send software updates to its vehicles wirelessly, the 29,222 Tesla Model S electric cars that were affected have already been fixed.
Your favorite basketball player is about to get one step closer to being a cyborg.
The NBA’s Development League (D-League) will soon begin experimenting with wearable technology on the court, the league announced today. A small disc weighing in at a whopping one ounce—attached either to players’ chests or between their shoulder blades and worn underneath their uniforms—measures vital biological statistics.
Developed in conjunction with STAT Sports, Catapult, and Zephyr, this groundbreaking wearable tech makes available—in real time—individual players’ current state and statistics. The information is relayed to coaching and medical staffs alike in an effort to improve players’ efficiency and effectiveness on the court.
Researchers at Australia’s Flinders University showed twenty participants smiley faces, along with real faces and strings of symbols that shouldn’t look like faces, all while recording the signals in the region of the brain that’s primarily activated when we see faces. This signal, called the N170 event-related potential, is the highest when people see actual faces, but was also high when people saw the standard emoticon :). “This indicates that when upright, emoticons are processed in occipitotemporal sites similarly to faces due to their familiar configuration,” the researchers write.