agregador de noticias
Si decimos Internet, a todos se nos vienen a la cabeza palabras como libre, público o universal. Tiene sentido, porque esas son algunas de sus principales características. Sin embargo realmente no existe un “sólo Internet” ya que el medio está formado por muchos diferentes, por redes de usuarios, contenidos e información con características distintas a las que tiene lo que comúnmente se entiende por Internet. Por ejemplo tenemos la Darknet, una de las subredes que opera aparte de las públicas en la cual acaba de nacer Grams, una especie de Google limitado gracias al que navegar por parte de ella se ha vuelto algo más fácil.
Afinando un poco más, muchos usan el término Darknet para describir la subred que funciona al margen de las públicas compuesta por un conjunto de sitios y tecnologías utilizadas por la mayoría con el objetivo de mercadear y compartir información y contenidos digitales de manera anónima. Dicha red sólo es navegable a través de Tor, y hacerlo no es nada simple porque todos los sitios usan URLs complejas y por su propia naturaleza crear motores de búsqueda genéricos no es viable.
Y aquí es donde la cosa se pone interesante, porque alguien pensó que aunque desarrollar un motor de búsqueda genérico funcional para la Darknet no es posible, sí lo era hacer uno destinado a buscar en sitios concretos de la subred. Justamente eso es Grams, un buscador que indexa los contenidos de los principales mercados que existen en la Darknet actualmente y permite buscar entre ellos.
En concreto Grams indexa los contenidos de los “mercados negros” Agora, BlackBank, Cloud Nine, Evolution, Pandora, Silk Road 2 y The Pirate Market, su aspecto se parece mucho al de Google, y también su funcionamiento: el usuario sólo tiene que acceder al sitio a través de la URL http://grams7enufi7jmdl.onion mediante el navegador web de Tor, indicar las palabras clave que desee, pulsar el botón buscar y listo, devolverá una lista de resultados ordenados de más relevantes a menos junto a otras opciones clásicas del mundo de las búsquedas como los filtros.
¿Conclusión? Pues está clara, al igual que ocurre en la vida real la vía de la prohibición y la mano duro no van a terminar con la Darknet y todo el tráfico de drogas, documentos falsos y demás cosas ilegales que se dan en sus “mercados negros”. Y no lo van a hacer porque aunque las autoridades estadounidenses le asestaron un duro golpe recientemente a los “darknet black market” con el cierre de Silk Road, el más grande que existía, como hemos visto siguen surgiendo nuevos y nuevas herramientas que facilitan usarlos.
For one month, I became the “micro-entrepreneur” touted by companies like TaskRabbit, Postmates, and Airbnb. Instead of the labor revolution I had been promised, all I found was hard work, low pay, and a system that puts workers at a disadvantage.
Excerpted from a must-read article by Sarah Kessler:
“The prospects of finding a living wage in America do not seem any brighter than they did back in 2008 when Busque founded TaskRabbit. Unemployment has drifted down from its high of 10% in October 2009 to 6.6% in the January 2014 report, but income inequality is, according to research based on tax-return data from the IRS, the worst it has been since 1923.
And the anecdotal evidence is appalling. Walmart, the single largest private employer in the country, was spotted at one location last holiday season hosting a Thanksgiving food drive for its own workers. McDonald’s, the second largest fast-food chain in the country, teamed up last summer with Visa to sketch out a budget for its low-paid full-time workers. The budget presumed they would each be working a second job. More than a decade after Barbara Ehrenreich wrote Nickel and Dimed to chronicle firsthand the struggles of low-wage workers, conditions only seem to have worsened.
Meanwhile, politicians have begun fighting over what they might do to help, namely, raise the federal minimum wage from $7.25 an hour to as much as $10.10 an hour. President Obama and the Democratic lawmakers advocating the raise hope that it spurs private employers to follow suit. Gap, for one, announced that it would raise its lowest hourly wages to $10 an hour by next year.
In the tech world, fueled by the success and high valuations of Airbnb (room or home rentals), Uber (car service), Lyft (car service), DogVacay (pet sitting), Postmates (urban courier service), and the many other services that rely on a new cadre of employee to fulfill what they’re selling, hope remains high that these marketplaces can create the solution. “People who are renting their homes out in Airbnb or driving for Lyft, they may make more money than working a minimum-wage job,” says Jeremiah Owyang, a former social-media analyst who last December launched Crowd Companies, a firm devoted to helping name brands such as Ford and Home Depot connect with startups in the gig economy. These folks are doing so well, in fact, Owyang says, “For some brands, this is a threat to employment.”
Some examples cited in the story:
“people like Sharon in San Diego, who has a goal of making $300 a week on TaskRabbit to help pay her bills, but hasn’t hit it yet. Or Kristen in New York City, who bids on tasks when she’s working full-time as a receptionist. Or Stacie, who works full-time as a software engineer in Boston, but always keeps the TaskRabbit website open so she can complete tasks on her lunch hour, after work, on weekends, or without leaving her desk. Stacie made about $6,000 on TaskRabbit last year, earning her “elite TaskRabbit” status. She likes helping people out, but she would never work on TaskRabbit just for the money. “If I wasn’t working full time, I could do more tasks,” she tells me, “but even if I doubled that, that’s still poverty–$12,000 a year. And there are no benefits. You don’t know what you’re going to wake up to. You could wake up one day, and be like, oh my god, I made $300 today, and then have three days where you’re making $12.”
When Stacie heard about Lyft, she decided to try that, too. She passed the screening process, attached the requisite pink mustache to her car, and had a great time driving people around for a day. Then she read an article about the insurance risks of driving for a peer-to-peer ride platform like Lyft. She became afraid that if someone were to sue her for getting hurt in her car, her insurance would not cover it. “I have savings, I have kids, and I have a house. I can’t risk it,” she says. “If I were 25 and I had nothing, yeah, to make a buck, what are the chances.” (Lyft has recently made efforts to address such concerns by expanding the insurance it provides drivers, but there are still ambiguities about what happens if claims exceed Lyft’s $1 million protection.)
Leena Chitnis, a former Fulbright scholar, finished an MBA program at Syracuse University last year and, while she looks for work, set up eight gigs on Fiverr to keep her going. So far, she’s completed a total of 27 orders and made $176. “I have $90,000 in school loans,” she says, “so when people say, can you edit my business plan for five bucks, I’m like, people charge $10,000 to write your business plan, and here I am editing it for four bucks [Fiverr takes 20% of every $5 fee]. I’ve seen panhandlers get more money outside of the 7-11.”
When I order my next Postmates delivery, I talk with the courier who biked through an icy storm to bring me a bag of cashews from Whole Foods. He’s 22, which means he can still use his parents’ insurance. On this four-hour shift, one of his first since signing up for Postmates, he expects to make about $40. “I don’t rely on this for my main source of income,” he says. “I haven’t talked with anyone who does.”
Every once in a while on a crowded New York City sidewalk, a puff of sadness will float off a stranger and hit me like a cloud of too-strong cologne. Whether it’s coming from a deliveryman with ice caked to the back of his bike or from a man with an overly starched white collar, it only lasts as long as it takes us to pass each other.
Not so in the gig economy. When you meet your neighbors, you meet their hardships. Sometimes they’re upfront about it. “Going through a divorce,” reads one TaskRabbit task. “Need somebody to preview emails from a contentious ex, redact any contentious material and summarize the essential practical elements (like ‘pack the kids’ rain boots next week,’).” Other hardships, like Teresa’s loneliness, sneak up on you. But it’s Marge who makes me want my desk job back.”
Continuing on her own experience, Sarah writes:
“My experiences in the gig economy raise troubling issues about what it means to be an employee today and what rights a worker, even on a assignment-by-assignment basis, are entitled to. The laws regarding what constitutes an employee have not yet caught up to the idea that jobs are now being doled out by iPhone push notification.
In a recent lawsuit filed against Uber–in the wake of an incident in which a driver hit and killed a child pedestrian on New Year’s Eve in San Francisco–the prosecuting attorney is arguing that Uber drivers are employees because their vehicles are logged by the Uber App and are therefore “on the clock” even when they don’t have a customer in their car. Postmates asks their workers to sign up for shifts. Zirtual asks them to be available during working hours. And most gig economy platforms have a system for weeding out employees who don’t get good reviews from customers. TaskRabbit “removes” them after the “second strike.”
I ask Postmates CEO Bastian Lehmann whether he thinks there’s a case to be made that his couriers are actually employees. “I don’t think it’s up to the companies or the startups to decide whether there’s an argument to be made or not,” he tells me. “There is a law that defines how you employ people, and that law allows independent contractors to be working for companies under specific conditions. If people want to change the scope of the discussion, then I think we have to discuss what is allowed by the law and not what a startup does.” Lehmann then trots out the now very familiar argument about how these independent contractors can choose to take the jobs or not, and he points out that FedEx also uses independent contractors (it contracts with small businesses to pick up, deliver, and transport packages).
By Lehmann’s math, Postmates couriers are making pretty good money. About 20% of couriers on Postmates’ platform are working the job as their primary source of income, he tells me. And for those who might complain they aren’t even making minimum wage as a Postmates courier (a charge leveled on Internet message boards and picked up by The Register), Lehmann thinks they’re doing it wrong. “Saying we don’t provide minimum wage, that’s like saying, I’m driving for Uber and there is not enough jobs at 6:00 in the morning,” he says. “It’s like saying, I don’t make any money on Airbnb because I only rent my apartment out on Wednesday night.”
My last call is to Leah Busque, CEO and founder of TaskRabbit, to seek comment on many of the problems that I and my fellow TaskRabbits have encountered while working on her platform: the difficulty of scheduling work, the lack of insurance, the desire for recurring work. Busque tells me that a platform revamp is scheduled to go live in the United States this year and that it will address some of these issues. She says that she’s “looked into a benefits program” for TaskRabbits and it’s “in the works.”
But Busque is emphatic that her company’s responsibility to TaskRabbits is only to provide the best platform possible–nothing more. “We’re about empowering these independent contractors to build out their own businesses,” she says. “We don’t want them to be TaskRabbit employees. It’s good for them to have the autonomy and the drive to do what they want, when they want, for the price that they want.”
Given the challenges I witnessed in making a living wage via TaskRabbit, I ask Busque how many people are able to work full-time via her labor market. She puts the percentage of TaskRabbits who use the site as their sole income at about 10%, and she says they “cash out” about $5,000 or $6,000 each month. Another 75%, according to TaskRabbit, “rely on the service to pay their bills.”
Busque would like to see both numbers increase. “I think we have a real opportunity to match our vision,” she says, “which is to revolutionize the way people work. And to do that, we have to see more and more people using the platform full-time.”
By the last day of my employment in the sharing economy, I’ve booked precisely zero Fiverr gigs. Nobody has invited me to cook pizzas at their hipster special occasions (and after about a month, my menu has mysteriously disappeared from the site). Apparently the people of Manhattan are better with Scotch tape than I anticipated, because I have not had a single Skillshare student. WunWun still hasn’t responded to my application. I have had two DogVacay requests that I could not accommodate. Two of the services on my list, Prim and Cherry, have shut down. One of them, Exec, was acquired. It had started as an broader errand-running business, and one of the founders wrote a farewell blog post in which he noted that “it was difficult to get [people seeking supplemental income] to stick around when we couldn’t guarantee work.”
I have come to realize that one of the cruel ironies of the gig economy is that even though it’s geared almost exclusively to serve urban markets, the kind of densely packed cities where space is at a premium, one needs a car to have a shot at the cream of the work that’s available. Even worse, the universe of gig economy startups is mostly relying on young people and others who are underemployed–exactly the people whom are least likely to be able to afford a car in a city. Or have an extra bedroom. Or a parking space. Or designer clothes. Or handyman skills.
When I’m looking for dependable work, I find myself at the bottom of the digital employment totem pole: Mechanical Turk, Amazon’s freelance marketplace. More than 500,000 people–many of whom live in the U.S.–have signed up on the site to complete mundane, repetitive tasks posted by such companies as Twitter, LinkedIn, and AOL. Site veterans can earn qualifications that allow them to accept better, higher-paying tasks (my college degree has no pull here). My best asset is that my IP address is registered in the United States. It’s a prerequisite that allows me to take some of the better jobs, like spending 24 minutes taking a survey that pays $0.70.
I spend the biggest chunk of my time, about two hours, labeling photo slideshows at a nickel each. Each of them has five photos, and each photo has 11 pages of labels to use on it. That means that it takes at least 55 clicks to earn $0.05. There are slideshows of cats on couches. Cats on beds. Dogs on beds. Cats in sinks. Dogs with cakes. Cats with cakes. Cats with pizza. Cats with windows. Dogs in car mirrors. Dogs with bananas.
On my way to completing 61 slideshows, I begin to resent Larry Zitnick, the Microsoft researcher who posted this maddening task. When I call him later, he’s actually quite nice. Zitnick explains that my slideshow labels are helping to train a computer to recognize images. “In the early 2000s, our datasets generally had hundreds or maybe a few thousand images in them,” he says. “And now we had have datasets with millions of images in them. It’s because of Mechanical Turk.”
Labeling slideshows suddenly feels very important. But it still doesn’t pay. I make $1.94 an hour. Research suggests most people, like me, aren’t making substantial income off their Mechanical Turk work. Only 8% of workers surveyed by researchers at the University of California, Irvine, said that Mechanical Turk income always helped them meet their basic needs.
My best day at TaskRabbit suddenly seems like a winner. I made $10 an hour at the dance job (not counting the performance that will take place the next day), $15 an hour at the Harvard Club, and about $20 an hour wrapping presents: $95 in total. My eight-and-a-half hour day was a best-case scenario. There was no downtime. The only break I had was a 10-minute lunch that I grabbed next to TaskRabbit user Mark’s apartment before gift wrapping his presents. But when you factor in the time I spend commuting between tasks, I only made $11 an hour.
That week, I make $166 on TaskRabbit, which is $46 above the median active TaskRabbit in my neighborhood. I also made $100 in cash from the tutoring job that started on TaskRabbit but was paid off the platform.
Near Central Park the next day, in the second blizzard of the year, my fellow dancers breathe into their mittens for an hour while waiting for the choreographed marriage proposal. “I would never say this professionally,” says the choreographer, “But I don’t fucking care. Do whatever you need to do to stay warm and get through this.” The girl from Sweden doesn’t have any boots. She fantasizes out loud about going home to stick her feet in the bathtub as we all jump around trying to stay warm. I mention the $20 I’m making, which at this point seems rather low. The dancers stare at me. It turns out that I and two other TaskRabbits are the only members of the group who are actually getting paid.”
Standardisation in the Area of Innovation and Technological Development, Notably in the Field of Text and Data Mining
You Asked: Tell us all your secrets.
SGT STAR: Good question. I'm not sure how to answer that. Please try rewording your question. I understand simple questions best.
You Asked: In that case, tell us everything.
SGT STAR: That is a good question, however, I am not positive that I understand what you're asking. Try rephrasing your question. I understand simple questions best.
Sgt. Star is the U.S. Army’s dedicated marketing and recruitment chatbot, and he isn’t going to turn whistleblower any time soon. There’s no use threatening him for answers either—he’s programmed to report that kind of hostility to the Army Criminal Investigation Division.
Last year, EFF began to look at how the government deploys chatbots to interact with and collect information from the public. Sgt. Star was a natural place to start, since he’s almost famous. Serving as the Army’s virtual public spokesperson, each year he guides hundreds of thousands of potential recruits through goarmy.com and fields their questions on Facebook.
(On the Media’s TLDR recorded an informative and entertaining podcast about Sgt. Star, our research and the issues AI chatbots raise—listen here.)
Since Sgt. Star wasn’t going to tell us everything he knows without us breaking it down into a thousand simple questions, we decided to just use the Freedom of Information Act to get it all at once. At first the Army ignored our inquiries, but with a little digging and pressure from the media1, we have been able to piece together a sort of personnel file for Sgt. Star.
We now know everything that Sgt. Star can say publicly as well as some of his usage statistics. We also learned a few things we weren’t supposed to: Before there was Sgt. Star, the FBI and CIA were using the same underlying technology to interact with child predators and terrorism suspects on the Internet. And, in a bizarre twist, the Army claims certain records don't exist because an element of Sgt. Star is “living.”
Everything We Know About Sgt. Star
Chatbots are computer programs that can carry on conversations with human users, often through an instant-message style interface. To put it another way: Sgt. Star is what happens when you take a traditional “FAQ” page and inject it with several million dollars worth of artificial intelligence upgrades.
Sgt. Star’s story dates back to the months after the 9/11 attacks, when the Army was experiencing a 40-percent year-over-year increase in traffic to the chatrooms on its website, goarmy.com. By the time the U.S. invaded Iraq, analysts predicted that the annual cost to staff the live chatrooms would be as high as $4 million.
A cost-cutting solution presented itself in late 2003 in the form of an artificial intelligence program called ActiveAgent, developed by a Spokane, Washington-based tech firm called Next IT. After years of trial runs and focus groups, the Army debuted Sgt. Star2 in 2006.
Technology and law scholars, such as Ryan Calo of the University of Washington School of Law and Ian Kerr of the University of Ottawa Faculty of Law, have warned of the threats to privacy posed by bots that combine social manipulation with mass data gathering. As Calo wrote of Sgt. Star in his paper, “Peering HALs: Making Sense of Artificial Intelligence and Privacy”:
As in the context of data mining, a computer equipped with artificial intelligence is capable of engaging thousands of individuals simultaneously, twenty-four hours a day. But here the agent is able to leverage the power of computers to persuade via carefully orchestrated social tactics known to elicit responses in humans. In an age of national security and targeted advertising, citizen and consumer information is at an all time premium. Techniques of AI and HCI [Human-Computer Interaction] create the opportunity for institutions to leverage the human tendency to anthropomorphise and other advantages computers hold over humans (ubiquity, diligence, trust, memory, etc.) to facilitate an otherwise impracticable depth and breadth of data collection.
Through a FOIA request, we were able to quantify Sgt. Star’s reach. According to a spreadsheet provided by the Army, Sgt. Star does the work of 55 human recruiters. Over the last five years, he has answered 10.5 million questions (94 percent of them correctly) in 2.8 million chat sessions. That means, on average, that Sgt. Star is engaging more than 1,550 people each day.
Sgt. Star is currently operated by the Army Marketing and Research Group, a division created in 2012 that operates out of the Pentagon. According to contracting documents, as of 2011, the Army had spent $5 million on the program, plus another couple of million in maintenance contracts3 in the years since.
The Army also revealed to TLDR that Sgt. Star is not so smart that he can increase his own knowledge base. Instead, the Army and Next IT hold monthly meetings to assess and adjust how Sgt. Star responds to questions.
While Sgt. Star may seem innocuous enough, he provides a window into how other agencies may use the technology for far more invasive purposes.
Sgt. Star’s Family
You Asked: Are there other government chatbots?
Sgt Star: I'm here to help you navigate though goarmy.com and answer your questions about the Army. I'm not here to discuss politics.
Sgt. Star has a large family of “intelligence virtual assistants” at Next IT. His brother Spike assists incoming students at Gonzaga University. Ann helps health consumers at AETNA. Travelers interact (and flirt) with Jenn at Alaska Airlines, Alex at United Airlines, and Julie at Amtrak. Next IT’s newest addition is Alme, a healthcare AI designed to help physicians interface with patients. But so far, Sgt. Star is the only federal government chatbot acknowledged on Next IT’s website.
Secretly, however, Sgt. Star does have family at law enforcement and intelligence agencies. According to an inadequately redacted document publicly available on the federal government’s contracting site, FBO.gov, Sgt. Star is built on technology developed for the FBI and CIA more than a decade ago to converse with suspects online. From the document:
LTC Robert Plummer, Director, USAREC PAE, while visiting the Pacific Northwest National Laboratories (PNNL) in late 2003, discovered an application developed by NextIt Corporation of Spokane, WA, that PNNL identified for the FBI AND CIA. The application used chat with an underlying AI component that replicated topical conversations. These agencies were using the application to engage PEDOPHILES AND TERRORISTS online, and it allowed a single agent to monitor 20-30 conversations concurrently.
The bolded text was redacted, but still legible in the document. At this point we don’t know whether the CIA and FBI are still using these bots.4 That will likely take a much longer FOIA process and, considering the redaction, the agencies may not be willing to give up the information without a fight.
Some food for thought: Sgt. Star engaged in almost 3 million conversations over the last five years, and those were people who actually wanted to talk to him. How many people could two CIA and FBI covert bots converse with over 10 years? What happens to conversations that aren’t relevant to an investigation, and how do the agencies weed out the false positives, such as when a chatbot misinterprets a benign conversation as dangerous?
We also know that Next IT developed an artificial intelligence program called ActiveSentry5, specifically designed to identify and neutralize threats to data security within a computer network. According to promotional materials, ActiveSentry’s origin story is very similar to Sgt. Star’s:
Our solution, ActiveSentry, is evolved from a proven technology we developed that has been deployed by government agencies to monitor Internet Relay Chat (IRC) rooms for such suspicious behavior as potential threats to national security, child exploitation, and drug trafficking.
ActiveSentry is not a chatbot, but a kind of patrol guard, watching keystrokes, conversations and monitoring network activity, looking for employee misbehavior and then springing into action. Here’s how Next IT’s founder and CEO described its investigative and evidence-gathering capabilities in a presentation at a homeland security technology showcase:
If bad behavior occurs, ActiveSentry can respond with real-time proactive steps to block the action. It might shut down the computer, shut down the application, alarm a security officer, or give the user a warning. If the security breach is sufficient, ActiveSentry creates a detailed record of everything the user does, stores all the action with date/time stamps, and secures the data for foolproof evidentiary material.
So far, we are unaware of any criminal cases where information gathered by a Next IT bot has been used as evidence. If you do know of such a case, please get in touch with us.
Is Sgt. Star Alive?
You Asked: Are you alive?
SGT STAR: I am a dynamic, intelligent self-service virtual guide, created by the Army, that will help you quickly navigate the GoArmy Web site and retrieve Army-related subject matter, while simultaneously answering questions and directing communication based on interaction with the user.
Generations upon generations of folklorists, philosophers, futurists and science fiction authors have asked the question: at what point does a machine become a living being?
Sorry, we can’t settle that debate. That said, the Army’s FOIA office did use some rather strange language in describing one piece of Sgt. Star’s programming.
In our request, we sought his output script (every possible response in his database) as it stands now, but also for each year since he went live. That way, we could compare how his answers have evolved and grown through military policy changes, such as the end of Don’t Ask Don’t Tell and the ban on women in combat. The Army gave us the 835 current responses, but could not give us the rest. Apparently, the historical scripts don’t exist because the script is a “living body.” The Army’s exact words in describing the spreadsheet of 835 responses:
This collection is the current running content that appears on the site and represents a “living body” of content that reflects the additions and updates to answers that have evolved since the introduction of the Sgt. Star feature.
Do they mean, “living” like the Constitution is said to be a living document? Or are they using it in the sense of Johnny 5 from Short Circuit? We plan to file a FOIA appeal to learn more. Likely what they mean is that they don’t maintain older versions of Sgt. Star’s script because they constantly update a single file. If that’s the case, then that indicates poor record-keeping by the Army. If the FBI treats their bots in the same way, that would raise serious questions about the ability of defendants to challenge the reliability of a bot if they are charged with a crime after the bot’s programming has changed.
The Army also refused to provide us with Sgt. Star’s input patterns, i.e. all the phrases and keywords that he is programmed to recognize, claiming that this information is Next IT’s proprietary material and therefore exempt from FOIA. We will address this in our FOIA appeal; we are not seeking Sgt. Star's underlying off-the-shelf ActiveAgent code, but we would like to see the customization details that give Sgt. Star his distinct Army flavor. It's also worth knowing what Sgt. Star is programmed to flag, even if he’s not programmed to actually respond to it.
Everything Sgt. Star Knows
You can view all of Sgt. Star’s current responses here. It's 288 pages.
Sgt. Star has a seemingly exhaustive supply of answers to questions about military service, from opportunities for dentists and veterinarians to whether soldier are allowed to use umbrellas (only women and under certain conditions). He also has answers that simply exist to deepen his personality, such as his music and film preferences, and information about his Rottweiler, "Chomp." He will also deliver rather in-depth, scientific answers to throwaway questions, including "why is the sky blue?" and "why is grass green?"
For all his character quirks, a user would never mistake Sgt. Star for human—that's just not how he was designed. That can’t necessarily be said for other government bots. Military, law enforcement and intelligence agencies have employed virtual people capable of interacting with and surveilling the public on a massive scale, and every answer raises many, many more questions.
You Asked: Until next time.
SGT STAR: Goodbye.
- 1. Special thanks to Alex Goldman of On The Media for following up with the Army, and journalist Jason Leopold for firing off a supporting FOIA request.
- 2. Technically, he is SGT STAR, with STAR as an acronym for “Strong, Trained And Ready,” which Sgt. Star says all soldier must be before being assigned to a unit or deployed. However, in the development stages, the program used the name “Sgt. Rock.”
- 3. While the Army does work directly with Next IT, it has also contracted out maintenance to two defense contractors—Nakuuruq Solutions and Truestone Communications—both subsidiaries of a corporation owned by the Iñupiat people of Northwest Alaska.
- 4. Next IT is no longer the only company offering pedophile-hunting chatbots. In 2004, a British programmer introduced a product he called “NetNannies.” Last year, Spanish researchers announced another AI, called Negobot.
- 5. ActiveSentry is now marketed by Next IT's affiliate, NextSentry Corporation.
Share this: || Join EFF
El último guía personal vuela a pocos metros del suelo, utiliza GPS y sensores de posicionamiento, responde a llamadas telefónicas, te espera si te retrasas en tu ruta y por supuesto te habla. Llamado de forma muy acertada como SkyCall, es uno de los últimos experimentos en los que se encuentra trabajando el equipo del prolífico y sorprendente SENSEable City Lab del MIT, dirigido por el italiano Carlo Ratti. A través de Skycall los estudiantes pueden, como muestra el vídeo, encontrar la ruta hacia su destino sin desorientarse por el Campus del MIT, que es en palabras de uno de los desarrolladores del prototipo, Christopher Green, uno de los más “desorientadores y difíciles laberintos del mundo”.
El dispositivo es un drone de cuatro hélices equipado con piloto automático, cámara, Wi-Fi, un sistema de navegación GPS y sensores que le permiten volar de forma autónoma y segura en interiores. El funcionamiento no puede ser más sencillo: el usuario llama a uno de los dispositivos a través de la aplicación SkyCall y sus coordenadas son transmitidas de forma inmediata el drone inactivo más cercano. Tras una espera el dispositivo hace su aparición y permanece flotando en el radio de acción del usuario de la aplicación a la espera de recibir instrucciones sobre el destino en forma de código alfanumérico. Una vez introducido el destino, el vehículo aéreo no tripulado comienza su vuelo posicionándose siempre a pocos metros por delante del usuario sirviendo de guía.
Probablemente y a simple vista no parece más que una forma francamente efectista de hacer lo mismo que ya hacemos cuando estamos desubicados y abrimos nuestra aplicación de Google Maps. Aparte de que esta nueva forma de guía – todavía en experimentación – nos permitiría retirar los ojos de la pantalla de nuestro dispositivo y disfrutar el entorno mientras somos guiados, tendrá además otros usos de mayor calado y es el ejemplo del Campus del MIT solo la puerta de entrada a otras muchas aplicaciones como el análisis de zonas afectadas por desastres naturales, el control de la proliferación de las algas, detectar problemas en infraestructuras o acabar por fín con los eternos debates politizados sobre el número de asistentes a las manifestaciones de uno u otro signo.Hacia una ecología digital facilitada por drones
El futuro del proyecto iniciado por el MIT con SkyCall llegará en forma de integración entre los dispositivos y los sistemas ecológicos naturales a través de una plataforma medioambiental de sensores basada en drones que sirva de soporte a la implementación y desarrollo de servicios de emergencias para identificar por ejemplo suelos fértiles, y llevar a cabo mediante insectos digitales (sí, has leído bien) perfectamente integrados con el entorno natural y sus “congéneres” acciones de polinización para repoblar y mantener la naturaleza.
Este será uno de los experimentos con los que el SENSEable City Lab del MIT está explorando la integración de la tecnología con la biodiversidad y que mostrará a buen seguro en la próxima Expo 2015 de Milán. En palabras de Yaniv Jacob Turgeman, responsable máximo de investigacion del Laboratorio, “supone una poética posibilidad de especulación sobre las formas en las que los sistemas creados por el hombre pueden volver a conectarlo con la naturaleza”.
Imágenes: SkyCall – MIT SENSEable City Lab
Welcome to your weekly roundup of badgeriffic news and updates!
This week’s calls were jam-packed with exciting project launches and badge system reports, generating lots of enthusiasm and discussion. The badging team at Penn State joined the Research & Badge System Design Call to share the thinking behind the Lifelong Learning Landscape developed by Dr Kyle Peck and Chris Gamrat to badge teacher professional development - read more here. On the Community Call, the Badge Alliance leadership shared updates on the working groups and the Cities of Learning kick-off - read more here.
What else happened this week?
- Design Researcher Emily joined the Community Call and shared her take-aways from her recent trip to Finland. She also shared some resources on her blog.
- Carla Casilli, Grainne Hamilton and others were in Edinburgh for Moodlemoot 2014, and community members participated, learned, shared, and blogged their experiences!
- Pittsburgh announced it will join Chicago and other Cities of Learning this summer in launching a pilot badging program for youth, and issued an open call for organizations to get involved!
- Nate Otto shared the updated system design worksheet from the Indiana University Badge Design Principles Documentation Project.
- Medium.com published a piece by Alex Wukman asking the question, Could Digital Badges Mark the End of the ‘Easy A’?
- Mary Cullinane wrote a thought-provoking op-ed for EdSurge - Ban “Digital” Learning!
- This fall, Coastal Carolina University will be rolling out “a unique curricular initiative,” awarding badges for mastery of critical skills in their first-year writing courses.
- The DML Research Hub has now launched the Connected Learning Alliance - read more here. Check out the new site + sign up for updates at http://clalliance.org
That’s a wrap, folks!
Have a great weekend - Happy Easter to those who celebrate, Happy Chocolate Day to those who plan to indulge :)
Open Badges blog: "A credential, like any common currency, is valued only because of the collective agreement to assign..."
- Michael Staton - Harvard Business Review (via worldofe)
En el mercado existen multitud de restaurantes pero ¿cuál es el mejor para pasar un rato con los amigos? ¿Y para ver actuaciones en vivo mientras cenamos? ¿O para organizar una reunión importante o sorprender a nuestra pareja? Para dar respuesta a todas estas preguntas ha nacido recientemente Restuento. Esta plataforma se basa en una red social que analiza los gustos gastronómicos de cada usuario, así como de sus amigos y gente cuya compatibilidad gastronómica sea alta, para adaptar las búsquedas a sus preferencias. Además esta red social ofrece la oportunidad de interactuar, invitar a amigos a que se unan a la plataforma, escribir críticas de los restaurantes visitados, hablar con el restaurante directamente para saber lo que ofrece, etc.
Para acertar con los gustos de los usuarios y los locales que más se adaptan a sus necesidades Restuento realiza un test que sirve para saber qué tipo de comida le gusta al cliente, tipo de restaurante, ambiente, plan, precios, etc. Gracias a esto y a los comentarios que se van dejando de los diferentes establecimientos el usuario encuentra lo que mejor se adapta a sus requisitos.En busca de calidad y confianza
La idea de crear Restuento parte de Jon Sánchez y Eneko González, dos empresarios vascos con una reforzada trayectoria en el mundo de la empresa, quienes se propusieron resolver los problemas de tiempo y cualificación de las opiniones que se encuentran en internet a la hora de reservar mesa en un restaurante. “Estos problemas son debido a la cantidad de comentarios demasiado positivos sobre restaurantes en concreto o demasiado negativos para poner por debajo al restaurante de la competencia, lo que hace que se genere cierta desconfianza entre los clientes”, dice Jon Sánchez.
Por lo tanto, se unían dos factores importantes. Primero, el cada vez mayor número de personas que acude a Internet a buscar un restaurante, y la segunda, la desconfianza y el tiempo utilizado para acertar en la elección. “Era el momento justo para crear una plataforma que aportase calidad a esas opiniones y sobre todo confianza”, añade Sánchez.
Restuento está dirigido a un público de hombres y mujeres de entre 23 y 48 años de edad, ya que estos los usuarios que están más acostumbrados a navegar por Internet para buscar páginas web relacionadas con su hobbies, intereses y necesidades. Además, conocen y manejan las redes sociales en busca de descuentos y oportunidades.Modelo de negocio y sistema de financiación
La compañía acaba de nacer gracias a una primera inversión de friends, fools and family de 60.000 euros y con aportaciones iniciales de los socios. La empresa está “en pleno lanzamiento”, según sus dos creadores, que están buscando una segunda ronda de financiación que permitirá el afianzamiento del proyecto en el mercado nacional y una posterior salida al mercado internacional, empezando por Reino Unido y Francia.
La red social integra un añadido de reservas con el fin de monetizar el proyecto desde el primer día. “Nuestro modelo de negocio se monetiza a través de las comisiones que tenemos de reservas a través de Internet de nuestros partners”, comenta Eneko González.
Read more of this story at Slashdot.
We really like the FairShares Model “where the knowledge creation model of Wikipedia is combined with the governance model of the John Lewis Partnership and the values and principles of the Co-operative Group”, and so we’re cross-posting this article (licensed by the FairShares Association under a Creative Commons Attribution, Sharealike License) here:
In this article, FairShares Association co-founder Rory Ridley-Duff outlines the continuing case for social and economic reform to support a FairShares Model of enterprise. FairShares brand principles change the way that investment activity is understood to ensure that capital is allocated for entrepreneurial, labour and user activities as well as financial contributions. The result is wealth and power that is shared more fairly.
At the start of 2014, I came across new studies that acted as a powerful reminder of the need for a FairShares Model. In this article I will describe the most striking of these, then argue that the co?operative and social enterprise movements need to concern themselves with everyone in the ‘bottom’ 80% of the population, not just those in extreme poverty. They also need to protect the wealth embedded in our natural environment.
I recently came across a YouTube animation that portrays private wealth distribution in the US using data from a study at Harvard University. This tells a completely different story to Shift Change, a documentary about social economy in the US and Spain. While the Harvard study reports that top US CEOs get380 times the average worker’s pay, Shift Change reports that worker co-operatives either adopt equal pay systems or accept small wage differentials sanctioned by the worker-owners. For example, the ratio between top and lowest paid workers in the Mondragon Co-ops – where there are 100,000 workers – averages just 5:1 .
The Harvard study claims that 90% of citizens are impoverished by private sector business practices. The ‘bottom’ 80% owns just 7% of total wealth, while the top 20% has 93%. Only 10% gain, and the top 1% gain disproportionately. There is no doubt. Hayek’s theory that economic freedom leads to a ‘trickle down’ effect is untrue. It produces a ‘trickle up’ effect instead  . But Shift Change shows that where co?operative business models become dominant, wealth is spread more evenly and equitably. Member-owned businesses more often than not, are as (commercially) successful as their private sector counterparts  . That’s where the FairShares Model comes in – it stimulates change to support growth in the social economy.
The Key Issue
Most social enterprises focus on the poorest communities. Whilst important, it is more urgent that we reform systems that exploit and impoverish up to 90% of working people (as well as the environment in which they live). We need social enterprises for the bottom 90% (everyone impoverished) not just the bottom 10% (the most impoverished). We also need a way to prevent the top 10% of earners acquiring hegemonic control over investment decisions. If this task is beyond us, the goals of social enterprise will also be beyond us.
It is not an accident that most people are getting poorer (in both absolute and relative terms). Studies of company law make it clear than private enterprises are not designed to share power or wealth . Founders fix structures at incorporation to privilege a set of interests (i.e. entrepreneur(s) and financial investors in companies, consumers or workers in single stakeholder co-operatives). Charitable organisations are also inflexible: board and workforce members are subordinate to charitable/social objects set by the founders.
Entrepreneurship research clarifies how enterprises start. One or more founding members – by design or accident – find opportunities to develop new markets for products and services . If viable, they organise resources to support a business and build socio-technical systems to maintain management control. Growing enterprises, however, also depend on the goodwill of the workforce, customers (service users) and institutional investors to access the human, social and financial capital needed for sustainability .
The key issue is that while we have developed systems for recognising the contribution of financial capital, we do not have adequate arrangements for recognising contributions of intellectual, human, social and natural capital. To understand why, we have to review the way social norms for constituting joint-stock companies and non-share companies have developed.
Private Sector (For-Profit) Norms – Companies Limited by Shares (CLS)
There is a connection between business ideology and the arrangements in law by which entrepreneurs acquire share capital (ordinary shares). They register as directors, then recruit employees to operationalize their ideas. New capital is issued when more financial capital is needed, but not when more intellectual, human, social or natural capital are needed. In an unadapted CLS, employees and customers are subordinated to the interests of shareholders. They are not invited to be full members or to contribute towards decisions outside their specialist area of expertise . If employees are offered share capital, voting rights are often limited or controlled by trustees who – in many cases – are under no legal obligation to vote in accordance with the wishes of their beneficiaries .
The intellectual property created by the workforce is acquired by the Company and controlled by executive managers and directors. In effect, majority shareholders treat intellectual, human, social and natural capital investments by others as if they were additional financial investments by themselves. They continue to acquire rights to all the property created by the interactions between employees, customers and the natural environment. This system of enterprise widens the wealth gap between those who own and govern the enterprise, and those who sell their labour to it, or buy goods from it. Even in the richest countries, wealth inequalities grow wider (unless the state intervenes)  and the natural environment is degraded .
Voluntary Sector (Non-Profit) Norms – Companies Limited by Guarantee (CLG)
A typical response to the social problems created by privately owned economies is to create (private) charities and ‘non-profit’ companies using a Company Limited by Guarantee (CLG). This form of incorporation usually involves specifying charitable or social objects that define the purpose(s) of the enterprise. Founders reframe themselves as trustee-directors responsible for allocating resources in pursuit of social goals.
Charitable CLGs do not issue share capital so trustee-directors give up personal rights to the surplus wealth created by the enterprise. Their role (in law) is one of stewardship, ensuring that funds raised are used to further charitable (or social) objectives defined in the Articles of Association. As in a CLS, they employ staff to pursue social goals. Employees are still not (usually) legal members. They continue to be subordinate to the trustee-directors and give up the (intellectual) property they create.
Social Economy Norms – The Co-operative Society / Mutual Company
Do we have to choose between these two models? Three bodies of knowledge suggest we do not. Firstly, there is a global movement backed by the UN to increase responsible use of corporate assets . Secondly, the UN’s International Year of Co-operatives highlighted the global growth of the social economy . Particularly important is the way that the internet has reduced the costs associated with co-operative working. The upsides of co-operation (intellectual exchange and collaborative decision-making) no longer come with the downsides of democracy (hefty co-ordination costs) . Lastly, more enterprises identify themselves as social, deploying business models that improve human well-being through innovative trading strategies .
Creating non-shareholding companies enables the wealthier sections of society to address some symptoms of poverty and exclusion that private enterprises create, but it cannot address the root causes because it changes neither the ownership structure nor governance processes that creates and sustains them. Traditional private / non-profit models continue to institutionalise a division between producers and consumers on the one hand, and entrepreneurs and (social) investors on the other. For this reason, Level 1 of the FairShares Model asks important questions about representation in ownership, governance and management.
FairShares Model – Level 1
As shown above, the FairShares Model is based on an approach to social economy defined by Social Enterprise Europe. It operates from the assumption that the exclusion of primary stakeholders from member-ownership (i.e. employees, producers, customers and service users) is a cause of contemporary poverty. At Level 2, the answer to each FairShares question suggests the set of corporate arrangements that is most favourable: entrepreneurs get Founder Shares; workforce members get Labour Shares; trading commitments are rewarded with User Shares; and financial capital creation is rewarded with Investor Shares.
FairShares Model – Level 2
This represents a new approach to valuing investments. When there are surpluses (profits), not only do the providers of financial capital get a return, but also the contributors of other types of capital. In a FairShares Company, half the capital gain is issued to Labour and User Shareholders as new Investor Shares,while the other half increases the value of existing Investor Shares. In a FairShares Co-operative, surpluses can be allocated to restricted funds controlled by Labour and User member-owners, who then use their chosen approach to direct democracy to allocate surpluses to social investment projects.
None of this means that the conventional mechanism for allocating shares to external financial investors has to stop. In a FairShares Company / Co-operative, Investor Shares can be issued to external investors if debt finance is hard to secure. But, even with this, at least 70% of the wealth accumulated will find its way into the hands (and bank balances) of producers and consumers. It enriches the ‘bottom’ 90% as much as the ‘top’ 10%. And if this is not sufficient, FairShares Articles of Association (at Level 3) includes community dividends that act as an asset lock for philanthropic capital if the enterprise is dissolved.
The Articles of Association provided by the FairShares Association are not the only model rules that support FairShares brand principles . But they do represent an ambitious attempt to bring together the most enduring developments in multi?stakeholder ownership, governance and management so that we change the way investments are recognised and valued  . The FairShares Model offers a system for ensuring that capital is allocated to different types of contribution so that wealth and power can be more fairly shared.
Dr Rory Ridley-Duff is Reader of Co-operative and Social Enterprise at Sheffield Hallam University (www.shu.ac.uk/sbs), director of Social Enterprise Europe (www.socialenterpriseeurope.co.uk), and a co-founder of the FairShares Association (www.fairshares.coop).
1. Norton, M. and Ariely, D. (2011), “Building a Better America – a Wealth Quintile at a Time”, Perspectives on Psychological Science, 6(1): 9 – 12.
2. Young, C. and Dworkin, M. (2013) Shift Change, Moving Images, www.shiftchange.org.
3. Melman, S. (2001) After Capitalism: From Managerialism to Workplace Democracy, New York: Alfred Knopf.
4. Erdal, D. (2011) Beyond the Corporation: Humanity Working, London: The Bodley Head.
5. Hayek, F. (1960) The Constitution of Liberty, London: Routledge and Kegan Paul.
6. Hayek, F. (1976) Law, Legislation and Liberty: the Mirage of Social Justice, London: Routledge and Kegan Paul.
7. See Perotin, V. and Robinson, A. (eds), Employee Participation, Firm Performance and Survival, Oxford: Elsevier
8. Birchall, J. (2009) People-Centred Businesses, Basingstoke: Palgrave Macmillan.
9. Davies, P. (2002) Introduction to Company Law, Oxford: Oxford University Press.
10. Chell, E. (2007) “Social enterprise and entrepreneurship: towards a convergent theory of the entrepreneurial process”, International Small Business Journal, 25 (1): 5-26.
11. Coule, T. (2008) Sustainability in Voluntary Organisations: Exploring the Dynamics of Organisational Strategy, unpublished Thesis, Sheffield Hallam University.
12. Erdal, D. (2011) Beyond the Corporation: Humanity Working, London: The Body Head.
13. Rodrick, S. (2005) Leveraged ESOPs and Employee Buyouts, Oakland, CA: The National Center for Employee Ownership.
14. Wilkinson, R. and Pickett, K. (2010) The Spirit Level: Why Equality is Better for Everyone, London: Penguin.
15. Hawken, P. (2010) The Ecology of Commerce: a Declaration of Sustainability, New York: Harper Paperbacks.
16. Laasch, O. and Conway, R. (2014) Principles of Responsible Management, Cengage.
17. ICA/Euricse (2013) The World Co-operative Monitor, International Co-operative Alliance / Euricse, access at:www.euricse.eu/en/WorldCooperativeMonitor/Report2013.
18. Murray, R. (2011) Co-operation in the Age of Google, Manchester: Co-operatives UK, access at: www.uk.coop/ageofgoogle.
19. Ridley-Duff, R. and Bull, M. (2011) Understanding Social Enterprise: Theory and Practice, London Sage Publications.
20. See www.socentstructures.org.uk/, a new joint venture by Social Enterprise Europe and NESEP.
21. Westall, A. (2001) Value-Led, Market-Driven: Social Enterprise Solutions to Public Policy Goals, London: IPPR.
22. Ridley-Duff, R. J. (2012) “New Frontiers in Democratic Self-Management”, in McDonall, D. and MacKnight, E. (eds), The Co?operative Model in Practice,Glasgow: Co-operative Education Trust Scotland, pp. 99 – 117.
Facebook ha vuelto a sorprendernos en las últimas horas. Y es que sin que nadie lo esperara, acaban de dar un salto importante en el campo de la geolocalización y la interconexión de personas en el mundo físico impulsada por la tecnología con el lanzamiento de “Amigos cerca”, una nueva característica implementada en la aplicación móvil de la red social ideada para “ayudar a descubrir si tus amigos se encuentran cerca de ti”.
De momento la característica, en la que han estado trabajando durante los dos últimos años, sólo está disponible en algunas zonas y en cuanto a su funcionamiento, la cosa va más o menos tal que así: una vez activada la funcionalidad en la aplicación móvil, esta comenzará a monitorizar nuestra ubicación geográfica cada 15 minutos y tendremos las siguientes opciones; uno, permitir que todos nuestros contactos puedan ver si estamos cerca de ellos o sólo grupos determinados; o dos, compartir nuestra situación exacta con un contacto determinado.
Por otro lado una vez activado “Amigos cerca”, aparecerán en un listado dentro de la pestaña de la funcionalidad aquellos contactos que se encuentren cerca de nosotros, tengan funcionando la característica y nos hayan añadido y nosotros a ellos. Y también hay notificaciones, que la app nos soltará de vez en cuando -no más de una o dos veces por semana- en el momento que uno o varios de esos contactos se encuentren cerca de nuestra posición (o sea, que el invento sólo funciona entre los amigos que compartan ubicación mutuamente).
Además, aquellos contactos que compartan información de ubicación entre sí, verán en su News Feed extractos de la lista de amigos próximos, y como decíamos tendrán la opción de enviarse su ubicación exacta (respecto a esto, Juanito puedes solicitar a Pepito que le envie su localización exacta, o Pepito compartirla a iniciativa propia con Juanito; sea como fuere, las ubicaciones exactas se comparten durante un tiempo determinado, se puede incluir un mensaje de 40 caracteres y el receptor verá la ubicación del remitente geolocaizada con precisión sobre un mapa).
Y llegados a este punto, nótese que salvo en el supuesto anterior todo el rato hablamos de “amigos cerca” y no de localizaciones exactas. El matiz es muy importante, porque con él Facebook se aleja del enfoque que hasta ahora todo el mundo venía aplicando en este campo, el consistente en ofrecer la posibilidad de ver la ubicación exacta sobre un mapa de las personas cercanas, e inaugura otro diferente: facilitar el compartir ubicaciones estimadas, algo mucho más poderoso que lo primero porque las personas son más propensas a compartir información sobre si están cerca que su localización precisa en un mapa.
Así que importante movimiento de Facebook, con el que pretenden potenciar los encuentros de contactos de la red social en el mundo físico. Ya veremos si la idea cuaja entre los usuarios. Probabilidades hay, porque a nivel privacidad la ejecuciones es casi perfecta (no está exacta de riesgos tampoco claro), porque el enfoque del funcionamiento de la característica no es intimidante, y porque si nos paramos a pensar tiene usos prácticos de valor (por ejemplo imaginemos que estamos tomando un café en un parque y nos apetece compañía; pues sólo tendríamos que abrir la app de Facebook, ver si alguno de nuestros amigos está cerca y en tal caso, enviarle nuestra localización exacta a través de “Amigos cerca” acompañada de un mensaje del tipo “Pepito tira para aquí y charlamos un rato”).
Estamos muy cerca de conseguir una sangre artificial perfectamente viable en seres humanos. Y, además, de tipo O, es decir, el donante universal. Según ha anunciado Wellcome Trust, las primeras pruebas clínicas con seres humanos se iniciarán a finales de 2016 o, a más tardar, a inicios de 2017, por lo que es probable que en la próxima década los donantes de sangre se queden sin la actividad que, de vez en cuando, los deja secos.
El origen del estudio de Wellcome Trust está en las polémicas células madre, que gracias a desarrollos como este mejoran considerablemente su cara más pública. La compañía, básicamente, ha desarrollado un método para convertir con éxito células madre en células sanguíneas.
En primer lugar, los científicos extraen células del cuerpo humano y las hacen involucionar hasta el estado de células madre. Entonces reproducen para ellas las condiciones del cuerpo humano, convirtiendo esas células madre en células sanguíneas que son del tipo del donante universal. Dicho así parece muy sencillo. Aunque no es así. Y tampoco es especialmente barato, como cabría esperar.La cercanía de las pruebas con seres humanos
El potencial de este desarrollo reside en la proximidad de las pruebas con humanos. Que ya hayan llegado a ese estadio en la técnica necesaria supone que la sangre artificial está cerca de su consumo. Y por tanto de su producción en masa, como indica Dvice. De aquí a que llegue ese momento, además de superar las pruebas clínicas, la sangre de Wellcome Trust tiene también el reto de abaratar su producción, de modo que se pueda extender su utilización.
En cuanto a sus usos, además de los más obvios como convivir con los vampiros sin que nos tengamos que exterminar unos a otros, está en primer lugar proporcionar sangre fresca a países del tercer mundo con sistemas de salud que no pueden afrontar la necesidad de sangre y, por extensión, están todos los sistemas de salud del mundo.
Mientras tanto, tenemos más o menos una década para poder disfrutar de ese breve momento de superior moral que dura mientras te comes el bocadillo y te tomas un refresco para recuperar fuerzas después de haber donado sangre.
Imagen: Free Images
On 9 April, the Pirate Party of Italy closed the internal debate on the European Elections and largely voted in favour of the motion about the support to the Alexis Tsipras’ list The Other Europe through the resolution 5687 on the e-democracy platform LiquidFeedback. The impossibility of the Party to gather the minimum legal number of signatures, in order to run as an independent party, drove the members to support a candidate on Tsipras’ list. The alternative to the resolution 5687 was to ignore European elections and to think about the future of the party.
Tommaso Fattori will represent the Pirate Party of Italy in the list. He is a founding member of the Italian Forum of Water Movements and was also one of the promoters of the successful referendum on water held in Italy in June 2011. The Party’s aim is to stimulate the debate in the European Parliament upon digital rights and support, the initiatives to protect the freedom of the net, to defend of the autodetermination of information, the freedom of knowledge and culture, the respect of the privacy of citizens, the reform of current anachronistic copyright laws and to support the pillars of our society – the information of the future.
As of 8 April, The Other Europe is polling at 4.5%, which is 0.5% more than the electoral threshold, enough to gain some seats in the European Parliament.
Featured image: CC0
Debido a la cantidad de cuentas que se están hackeando últimamente a través de Internet, los analistas de Kaspersky recomiendan que es conveniente vigilar y estar alerta de las cuentas que tengamos en PayPal, Amazon, Google Checkout y otras cuentas de pago online para poder detectar una actividad sospechosa de inmediato.
Los cibercriminales utilizan diversos ataques para instalar malware en el ordenador de los usuarios y modificar así las páginas webs legítimas con el fin de tomar el control de la actividad de banca online del usuario. Estos ataques son exploits llamados “man-in-the-browser”. De este modo, aunque dirección a la que accede el usuario sea la correcta, los ciberdelincuentes podrán interceptar la transacción, robar lo datos financieros y, en consecuencia, el dinero. Por ello, es necesario contar con una solución de seguridad en el dispositivo.Síntomas de una ciberestafa y para evitarla
Lo primero que ha de hacer un usuario para no ser estafado es estar atento de cualquier actividad no autorizada, ya que aunque las transacciones sean de pequeñas cantidades no autorizadas, estas son un gran peligro y pueden acarrear un problema para el mismo. Así mismo, el cliente no debe ignorar las notificaciones que envíe el banco en forma de correo, ya que pueden estar confirmando que los detalles de la cuenta han cambiado sin su consentimiento, lo que puede hacer que la cuenta esté comprometida.
Revisar los correos electrónicos y no contestar a aquellos que proceden de un emisor desconocido es una forma de evitar las estafas, así como estar atentos a los enlaces que se envían dentro de ellos, ya que nos pueden llevar a páginas de phishing. Es conveniente comprobar, si se detecta alguna actividad fuera de lo común, si se ha pinchado algún enlace.
Por otro lado, hay que recordar que las estafas no solo pueden producirse por Internet, sino también a través del teléfono móvil. Las llamadas falsas son uno de los usos más habituales de los estafadores, por lo que si la llamada se produce desde un número desconocido, es mejor devolverla antes que seguir hablando. Lo mismo pasa con los mensajes de texto que son enviados desde un teléfono que el proveedor no suele utilizar.
El periodista del diario The Guardian Halley Docherty ha llevado a cabo otra de sus famosas series de fotos en las que expone imágenes, obras de artes o diferentes iconos historicos y actuales sobre localizaciones de Google Street View. En esta ocasión el tema protagonista es la música y Docherty mezcla de forma meticulosa portadas de discos con las calles en su apariencia actual a través de los ojos de Google Street View. El resultado es un fabuloso mashup que aúna vida urbana, movimiento, evolución, cultura digital y música.
En la serie podemos encontrar portadas de grupos como Pink Floyd, Bob Dylan, Oasis, Led Zeppelin, PJ Harvey, Rush, Beastie Boys o la Credence Clearwater Revival y comprobar la forma en la que las ubicaciones han cambiado a los largo de los años. Algunas de ellas permanecen prácticamente iguales como si de una mágica pausa del paso del tiempo se tratara. Es el caso por ejempo de Abbey Road, icono indudable de The Beatles, que ha sido conservado prácticamente igual gracias a los esfuerzos de concejo de Westminster en la ciudad de Londres. Otras, por contra, sí han sufrido el inexorable paso del tiempo como el montaje que mostramos sobre la portada de LP “The Marshall Mathers”: la imagen actual ya no muestra la casa en la que el cantante Eminem se crió ya que fue demolida el año pasado.
Read more of this story at Slashdot.
Read more of this story at Slashdot.
Read more of this story at Slashdot.