mfioretti: data ownership* + percloud*

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  1. Popular internet platforms that currently mediate our everyday communications become more and more efficient in managing vast amounts of information, rendering their users more and more addicted and dependent on them. Alternative, more organic options like community networks do exist and they can empower citizens to build their own local networks from the bottom up. This chapter explores such technological options together with the adoption of a healthier internet diet in the context of a wider vision of sustainable living in an energy-limited world.


    The popular Internet platforms that mediate a significant portion of our everyday communications become thus more and more efficient in managing vast amounts of information. In turn, they also become more and more knowledgeable about designing user interaction design techniques that increase addiction, or “stickiness” when described as a performance metric, and dependency. This renders their users more and more addicted and dependent on them, subject to manipulation and exploitation for commercial and political objectives. This could be characterized as the second watershed of the Internet in the context of Illich’s analysis on the lifecycle of tools. As in the case of medicine and education, the Internet at its early stages was extremely useful. It dramatically increased our access to knowledge and to people all over the world. However, to achieve this, it relied on big organizations offering efficient and reliable services. These services now depend more and more on the participation of people and on the exploitation of the corresponding data produced for platforms to survive. This creates a vicious cycle between addictive design practices and unfair competition which breach the principle of net neutrality, and unethical uses of privately owned knowledge on human behavior which are generated through analyses of the data produced from our everyday online activities.

    In addition to the tremendous social, political, and economic implications of centralizing power on the Internet, there are also significant ecological consequences. At first glance, these seem to be positive. The centralization of online platforms has allowed their owners to build huge data centers in cold climates and invest in technologies that keep servers cool with lower energy costs. However, at the same time, the main aim of online platforms is to maximize the total time spent online as much as possible and to maximize the amount of information exchanged, not only between people but also between “things!” Their profitability depends on the processing of huge amounts of information that produces knowledge which can be sold to advertisers and politicians. Like the pharmaceutical companies, they create and maintain a world in which they are very much needed. This also explains why corporations like Facebook, Google, and Microsoft are at the forefront of the efforts to provide “Internet access to all” and why at the same time local communities face so many economic, political, and legal hurdles that encumber them to build, maintain, and control their own infrastructures.


    To achieve a sustainable level of Internet usage, one needs to provide the appropriate tools and processes for local communities to make decisions on the design of their ICT tools, including appropriate alternative and/or complementary design of places, institutions, and rituals that can impose certain constraints and replace online communications when these are not really necessary. To answer this demand, one should first answer a more fundamental question: How much online communication is needed in an energy-restricted world? In the case of food and housing, there are some reasonable basic needs. For example, each person should consume 2000 calories per day or 35 m2 of habitat (see P.M., 2014). But, how many Mbs does someone need to consume to sustain a good quality of life? What would be the analogy for a restricted vegetarian or even vegan Internet diet?
    The answer might differ depending on the services considered (social activities, collaborative work, or media) and the type of access to the network discussed above. For example, is it really necessary to have wireless connectivity “everywhere, anytime” using expensive mobile devices, or is it enough to have old-fashioned Internet cafes and only wired connections at home? Would it make sense to have Internet-free zones in cities? Can we imagine “shared” Internet usage in public spaces—a group of people interacting together in front of a screen and alternating in showing their favorite YouTube videos (a sort of an Internet jukebox)? There is a variety of more or less novel constraints which could be imposed on different dimensions:

    Time and Volume: A communications network owned by a local community, instead of a global or local corporation, could shut down for certain period of time each day if this is what the community decides. Or community members could agree to have certain time quotas for using the network (e.g., not more than 4 hours per day or 150 hours per month). Such constraints would not only reduce energy consumption; they would also enforce a healthier lifestyle and encourage face-to-face interactions.

    Reducing quotas on the speed (bandwidth) and volume (MB) that each person consumes is another way to restrict Internet consumption. Actually people are already used to such limits especially for 3G/4G connectivity. The difference is that a volume constraint does not necessarily translate to time constraints (if someone uses low volume services such as e-mail). So, volume constraints could encourage the use of less voluminous services (e.g., downloading a movie with low instead of High Definition resolution if this is to be watched in a low definition screen anyway) while time constraints might have the opposite effect (people using as much bandwidth as possible in their available time).

    However, to enforce such constraints, both time and volume based, on an individual basis, the network needs to know who is connecting to it and keep track of the overall usage. This raises the question of privacy and identification online and again the trade-off of trusting local vs. global institutions to take this role. Enforcing time or volume constraints for groups of people (e.g., the residents of a cooperative housing complex) is an interesting option to be considered when privacy is considered important.

    Devices: Energy consumption depends on the type of equipment used to access the Internet. For example, if access to the Internet happens only through desktop computers or laptops using ethernet cables instead of mobile smartphones, then the total energy consumed for a given service would be significantly reduced. Usage would also be dramatically affected: On the positive side, many people would spend less time online and use the Internet only for important tasks. On the negative side, others might stay at home more often and sacrifice outdoors activities in favor of Internet communications.
    https://rd.springer.com/chapter/10.1007/978-3-319-66592-4_13
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  2. “I believe it’s important to tell people exactly how the information that they share on Facebook is going to be used.

    “That’s why, every single time you go to share something on Facebook, whether it’s a photo in Facebook, or a message, every single time, there’s a control right there about who you’re going to be sharing it with ... and you can change that and control that in line.

    “To your broader point about the privacy policy ... long privacy policies are very confusing. And if you make it long and spell out all the detail, then you’re probably going to reduce the per cent of people who read it and make it accessible to them.”
    https://www.theguardian.com/technolog...testimony-to-congress-the-key-moments
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  3. Di nuovo: dove sta lo scandalo di questi giorni, dunque? Lo scandalo sta nell’evidenza di un errore di fondo nella concezione delle interazioni umane, la concezione che Mark Zuckerberg ha imposto — per sua stessa ammissione, nel tanto agnognato intervento post-Cambridge Analytica — dal 2007. L’idea cioè di costruire un “web dove si è social di default”. Dove cioè la norma è condividere. Un principio che è strutturalmente opposto alla tutela della privacy individuale, che si fonda sulla riservatezza come norma, riguardo ai propri dati personali.

    Zuckerberg lo spiega benissimo nel suo più recente intervento, individuando - giustamente - in quell’errore filosofico e antropologico la radice della tempesta in cui è costretto a destreggiarsi: “Nel 2007, abbiamo lanciato la Facebook Platform nella convinzione (“vision”) che più app dovessero essere social. Il tuo calendario doveva poterti mostrare il compleanno degli amici, le tue mappe mostrare dove vivono i tuoi amici, il tuo address book le loro foto. Per farlo, abbiamo consentito di accedere alle app e condividere chi fossero i tuoi amici e alcune informazioni su di loro”.

    È questo che conduce, nel 2013, Kogan a ottenere l’accesso ai dati di milioni di persone. E certo, quei dati hanno un immenso valore scientifico — ed è giusto che la ricerca, se condotta nel pieno rispetto del consenso informato degli utenti divenuti soggetti sperimentali, possa accedervi. Per soli scopi accademici, però. E anche così, già nel 2014 il famoso esperimento condotto da Facebook stessa sulla manipolazione delle emozioni di centinaia di migliaia di utenti, a cui erano stati mostrati deliberatamente più contenuti positivi o negativi, aveva dimostrato che anche quando non ci sono di mezzo fini commerciali, la questione è ambigua, complessa. E che no, non basta accettare condizioni di utilizzo intricate e che non legge nessuno per dire che allora ogni utente ha, per il fatto stesso di avere accettato di essere su Facebook, di diventare indiscriminatamente un topo di laboratorio arruolato in esperimenti di cui ignora tutto.

    Eppure è proprio la piattaforma a rendersi conto, già in quello stesso anno, che così le cose non vanno. Che a quel modo Facebook perde il controllo su quali terze parti hanno accesso ai dati dei suoi utenti. La policy dunque cambia, e da allora gli “amici” devono acconsentire al trattamento dei propri dati da parte di una app. La nuova filosofia, ricorda Albright, è “people first”. Ma è tardi. E l’incapacità di rientrare davvero in possesso di quell’ammasso di informazioni, dimostrata dal caso Cambridge Analytica – possibile Facebook debba scoprire dai giornali che l’azienda non aveva cancellato i dati che diceva di aver cancellato, o che debba comunque condurre un auditing serio per verificarlo ora, dimostrando di non avere idea se lo siano o meno? – fa capire che il problema va ben oltre il singolo caso in questione, ma è sistematico.

    Per capirci più chiaramente: come scrive Albright, la prima versione delle API v.1.0 per il Facebook Graph – cioè ciò che gli sviluppatori di applicazioni potevano ottenere dal social network tra il 2010, data di lancio, e il 2014, data in cui la policy è cambiata – consentiva di sapere non su chi si iscriveva a una determinata app, ma dagli amici inconsapevoli, i seguenti dati: “about, azioni, attività, compleanno, check-ins, istruzione, eventi, giochi, gruppi, residenza, interessi, like, luogo, note, status, tag, foto, domande, relazioni, religione/politica, iscrizioni, siti, storia lavorativa”. Davvero si poteva pensare di controllare dove finissero tutti questi dati, per milioni e milioni di persone?

    E davvero Facebook lo scopre oggi? Nel 2011, la Federal Trade Commission americana aveva già segnalato la questione come problematica. Non ha insegnato nulla
    https://www.valigiablu.it/facebook-cambridge-analytica-scandalo
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  4. Mark Zuckerberg also launched Facebook with a disdain for intrusive advertising, but it wasn’t long before the social network giant became Google’s biggest competitor for ad dollars. After going public with 845 million users in 2012, Facebook became a multibillion-dollar company and Zuckerberg one of the richest men on Earth, but with only a promise that the company would figure out how to monetize its platform.

    Facebook ultimately sold companies on its platform by promising “brand awareness” and the best possible data on what consumers actually liked. Brands could start their own Facebook pages, which people would actually “like” and interact with. This provided unparalleled information about what company each individual person wanted to interact with the most. By engaging with companies on Facebook, people gave corporate marketing departments more information than they could have ever dreamed of buying, but here it was offered up free.

    This was the “grand bargain,” as Columbia University law professor Tim Wu called it in his book, The Attention Merchants, that users struck with corporations. Wu wrote that Facebook’s “billions of users worldwide were simply handing over a treasure trove of detailed demographic data and exposing themselves to highly targeted advertising in return for what, exactly?”

    In other words: We will give you every detail of our lives and you will get rich by selling that information to advertisers.

    European regulators are now saying that bargain was a bad deal. The big question that remains is whether their counterparts in the U.S. will follow their lead.
    https://www.huffingtonpost.com/entry/...antitrust_us_5a625023e4b0dc592a088f6c
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  5. The point is that Facebook has a strong, paternalistic view on what’s best for you, and it’s trying to transport you there. “To get people to this point where there’s more openness – that’s a big challenge. But I think we’ll do it,” Zuckerberg has said. He has reason to believe that he will achieve that goal. With its size, Facebook has amassed outsized powers. “In a lot of ways Facebook is more like a government than a traditional company,” Zuckerberg has said. “We have this large community of people, and more than other technology companies we’re really setting policies.”

    Without knowing it, Zuckerberg is the heir to a long political tradition. Over the last 200 years, the west has been unable to shake an abiding fantasy, a dream sequence in which we throw out the bum politicians and replace them with engineers – rule by slide rule. The French were the first to entertain this notion in the bloody, world-churning aftermath of their revolution. A coterie of the country’s most influential philosophers (notably, Henri de Saint-Simon and Auguste Comte) were genuinely torn about the course of the country. They hated all the old ancient bastions of parasitic power – the feudal lords, the priests and the warriors – but they also feared the chaos of the mob. To split the difference, they proposed a form of technocracy – engineers and assorted technicians would rule with beneficent disinterestedness. Engineers would strip the old order of its power, while governing in the spirit of science. They would impose rationality and order.
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    This dream has captivated intellectuals ever since, especially Americans. The great sociologist Thorstein Veblen was obsessed with installing engineers in power and, in 1921, wrote a book making his case. His vision briefly became a reality. In the aftermath of the first world war, American elites were aghast at all the irrational impulses unleashed by that conflict – the xenophobia, the racism, the urge to lynch and riot. And when the realities of economic life had grown so complicated, how could politicians possibly manage them? Americans of all persuasions began yearning for the salvific ascendance of the most famous engineer of his time: Herbert Hoover. In 1920, Franklin D Roosevelt – who would, of course, go on to replace him in 1932 – organised a movement to draft Hoover for the presidency.

    The Hoover experiment, in the end, hardly realised the happy fantasies about the Engineer King. A very different version of this dream, however, has come to fruition, in the form of the CEOs of the big tech companies. We’re not ruled by engineers, not yet, but they have become the dominant force in American life – the highest, most influential tier of our elite.

    There’s another way to describe this historical progression. Automation has come in waves. During the industrial revolution, machinery replaced manual workers. At first, machines required human operators. Over time, machines came to function with hardly any human intervention. For centuries, engineers automated physical labour; our new engineering elite has automated thought. They have perfected technologies that take over intellectual processes, that render the brain redundant. Or, as the former Google and Yahoo executive Marissa Mayer once argued, “You have to make words less human and more a piece of the machine.” Indeed, we have begun to outsource our intellectual work to companies that suggest what we should learn, the topics we should consider, and the items we ought to buy. These companies can justify their incursions into our lives with the very arguments that Saint-Simon and Comte articulated: they are supplying us with efficiency; they are imposing order on human life.

    Nobody better articulates the modern faith in engineering’s power to transform society than Zuckerberg. He told a group of software developers, “You know, I’m an engineer, and I think a key part of the engineering mindset is this hope and this belief that you can take any system that’s out there and make it much, much better than it is today. Anything, whether it’s hardware or software, a company, a developer ecosystem – you can take anything and make it much, much better.” The world will improve, if only Zuckerberg’s reason can prevail – and it will.

    The precise source of Facebook’s power is algorithms. That’s a concept repeated dutifully in nearly every story about the tech giants, yet it remains fuzzy at best to users of those sites. From the moment of the algorithm’s invention, it was possible to see its power, its revolutionary potential. The algorithm was developed in order to automate thinking, to remove difficult decisions from the hands of humans, to settle contentious debates.
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    The essence of the algorithm is entirely uncomplicated. The textbooks compare them to recipes – a series of precise steps that can be followed mindlessly. This is different from equations, which have one correct result. Algorithms merely capture the process for solving a problem and say nothing about where those steps ultimately lead.

    These recipes are the crucial building blocks of software. Programmers can’t simply order a computer to, say, search the internet. They must give the computer a set of specific instructions for accomplishing that task. These instructions must take the messy human activity of looking for information and transpose that into an orderly process that can be expressed in code. First do this … then do that. The process of translation, from concept to procedure to code, is inherently reductive. Complex processes must be subdivided into a series of binary choices. There’s no equation to suggest a dress to wear, but an algorithm could easily be written for that – it will work its way through a series of either/or questions (morning or night, winter or summer, sun or rain), with each choice pushing to the next.

    Facebook would never put it this way, but algorithms are meant to erode free will, to relieve humans of the burden of choosing, to nudge them in the right direction. Algorithms fuel a sense of omnipotence, the condescending belief that our behaviour can be altered, without our even being aware of the hand guiding us, in a superior direction. That’s always been a danger of the engineering mindset, as it moves beyond its roots in building inanimate stuff and begins to design a more perfect social world. We are the screws and rivets in the grand design.
    https://www.theguardian.com/technolog...r-on-free-will?CMP=Share_iOSApp_Other
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  6. "All of us, when we are uploading something, when we are tagging people, when we are commenting, we are basically working for Facebook," he says.

    The data our interactions provide feeds the complex algorithms that power the social media site, where, as Mr Joler puts it, our behaviour is transformed into a product.

    Trying to untangle that largely hidden process proved to be a mammoth task.

    "We tried to map all the inputs, the fields in which we interact with Facebook, and the outcome," he says.

    "We mapped likes, shares, search, update status, adding photos, friends, names, everything our devices are saying about us, all the permissions we are giving to Facebook via apps, such as phone status, wifi connection and the ability to record audio."

    All of this research provided only a fraction of the full picture. So the team looked into Facebook's acquisitions, and scoured its myriad patent filings.

    The results were astonishing.

    Visually arresting flow charts that take hours to absorb fully, but which show how the data we give Facebook is used to calculate our ethnic affinity (Facebook's term), sexual orientation, political affiliation, social class, travel schedule and much more.
    Image copyright Share Lab
    Image caption Share Lab presents its information in minutely detailed tables and flow charts

    One map shows how everything - from the links we post on Facebook, to the pages we like, to our online behaviour in many other corners of cyber-space that are owned or interact with the company (Instagram, WhatsApp or sites that merely use your Facebook log-in) - could all be entering a giant algorithmic process.

    And that process allows Facebook to target users with terrifying accuracy, with the ability to determine whether they like Korean food, the length of their commute to work, or their baby's age.

    Another map details the permissions many of us willingly give Facebook via its many smartphone apps, including the ability to read all text messages, download files without permission, and access our precise location.

    Individually, these are powerful tools; combined they amount to a data collection engine that, Mr Joler argues, is ripe for exploitation.

    "If you think just about cookies, just about mobile phone permissions, or just about the retention of metadata - each of those things, from the perspective of data analysis, are really intrusive."
    http://www.bbc.com/news/business-39947942
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  7. earlier this month, The Australian uncovered something that felt like a breach in the social contract: a leaked confidential document prepared by Facebook that revealed the company had offered advertisers the opportunity to target 6.4 million younger users, some only 14 years old, during moments of psychological vulnerability, such as when they felt “worthless,” “insecure,” “stressed,” “defeated,” “anxious,” and like a “failure.”

    The 23-page document had been prepared for a potential advertiser and highlighted Facebook’s ability to micro-target ads down to “moments when young people need a confidence boost.” According to The Australian’s report, Facebook had been monitoring posts, photos, interactions, and internet activity in real time to track these emotional lows. (Facebook confirmed the existence of the report, but declined to respond to questions from WIRED about which types of posts were used to discern emotion.)

    The day the story broke, Facebook quickly issued a public statement arguing that the premise of the article was “misleading”
    https://www.wired.com/2017/05/welcome-next-phase-facebook-backlash
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  8. Facebook, which now owns WhatsApp, is fighting a challenge to its new privacy policy that it unveiled last year. According to the new privacy policy WhatsApp can share some user data with Facebook, which the Mark Zuckerberg-led company can then use in various ways. Although WhatsApp says that it will (still) not share all the information that users generate through their chats, India Today Tech noted earlier , Facebook only needs the phone number of a user to build a full WhatsApp profile for that user. The company most likely already has other details on users.

    Also Read: WhatsApp will ONLY share phone number but that is all Facebook needs

    The new WhatsApp privacy has been criticised worldwide. Just days ago, a court in Germany asked Facebook to stop harvesting user information from WhatsApp. After the court order, Facebook said that it was pausing the sharing of WhatsApp user data with Facebook in whole of Europe. The ruling came even as the European Union privacy watchdog continues to probe the new privacy policy.

    However, in India where privacy laws are non-existent, Facebook and WhatsApp have so far defended their new privacy policy. It is also important to note that India is one of the biggest markets for both Facebook and WhatsApp and that could also be one of the reasons why Facebook wants to enforce its new privacy policies here. Data from Indian users could be commercially very attractive for the company.
    http://indiatoday.intoday.in/technolo...hatsapp-facebook-lawyer/1/940551.html
    Voting 0
  9. Key functions of an ecosystem of collaborative software tools:

    Here are a number of areas that we have decided are critical to this collaborative ecosystem.

    Notifications Dashboard: aggregated notifications of activity that is sourced from activity from tools in the ecosystem
    Chat and Direct Messaging: one-to-one and one-to-many messaging, with tunable privacy as appropriate to communication goals
    Representation of Group Membership and Group Auth: a tool that stores who is a member of which group, who can see the data that the group contains, and can invoke single-purpose tools through “group authentication”
    Representation of which groups are using which tools: this enables the community to understand which tools are part of the set of tools in use in a given environment
    Intent-casting + Collaborative discovery: discovery of aligned intentions + matching of available requests and offers. Can include bounties/price tags in a variety of currencies.
    Collaborative ideation & brainstorming: allows decentralized groups to ideate and brainstorm together
    Collaborative decision making: allows decentralized groups to come to decisions together
    Collaborative budgeting: allows decentralized groups to allocate common-pool resources
    Network visualization: allows users to interact with different types of visual representations of shared data and membership
    __Reputation: allows users to assess the past actions of network participants based on user tunable, context aware preferences
    Identity: allows users to be aware of the identity of other users over time tied to reputation
    Mutual Credit: allows users to create and track mutual credit exchanges
    https://www.hylo.com/p/17726?utm_camp...m_medium=email&utm_source=user_mailer
    Voting 0
  10. Movim
    When social network meets IM,
    you can expect some surprises…

    Our main motto? Don't reinvent the wheel. Since the beginning all the Movim communications are made using XMPP.
    https://movim.eu/#features
    Voting 0

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