mfioretti: big data*

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  1. Stratumseind in Eindhoven is one of the busiest nightlife streets in the Netherlands. On a Saturday night, bars are packed, music blares through the street, laughter and drunken shouting bounces off the walls. As the night progresses, the ground becomes littered with empty shot bottles, energy drink cans, cigarette butts and broken glass.

    It’s no surprise that the place is also known for its frequent fights. To change that image, Stratumseind has become one of the “smartest” streets in the Netherlands. Lamp-posts have been fitted with wifi-trackers, cameras and 64 microphones that can detect aggressive behaviour and alert police officers to altercations. There has been a failed experiment to change light intensity to alter the mood. The next plan, starting this spring, is to diffuse the smell of oranges to calm people down. The aim? To make Stratumseind a safer place.

    We get that comment a lot – ‘Big brother is watching you’. I prefer to say, ‘Big brother is helping you’
    Peter van de Crommert

    All the while, data is being collected and stored. “Visitors do not realise they are entering a living laboratory,” says Maša Galic, a researcher on privacy in the public space for the Tilburg Institute of Law, Technology and Society. Since the data on Stratumseind is used to profile, nudge or actively target people, this “smart city” experiment is subject to privacy law. According to the Dutch Personal Data Protection Act, people should be notified in advance of data collection and the purpose should be specified – but in Stratumseind, as in many other “smart cities”, this is not the case.

    Peter van de Crommert is involved at Stratumseind as project manager with the Dutch Institute for Technology, Safety and Security. He says visitors do not have to worry about their privacy: the data is about crowds, not individuals. “We often get that comment – ‘Big brother is watching you’ – but I prefer to say, ‘Big brother is helping you’. We want safe nightlife, but not a soldier on every street corner.”
    Revellers in Eindhoven’s Stratumseind celebrate King’s Day.
    Revellers in Eindhoven’s Stratumseind celebrate King’s Day. Photograph: Filippo Manaresi/Moment Editorial/Getty Images

    When we think of smart cities, we usually think of big projects: Songdo in South Korea, the IBM control centre in Rio de Janeiro or the hundreds of new smart cities in India. More recent developments include Toronto, where Google will build an entirely new smart neighbourhood, and Arizona, where Bill Gates plans to build his own smart city. But the reality of the smart city is that it has stretched into the everyday fabric of urban life – particularly so in the Netherlands.

    In the eastern city of Enschede, city traffic sensors pick up your phone’s wifi signal even if you are not connected to the wifi network. The trackers register your MAC address, the unique network card number in a smartphone. The city council wants to know how often people visit Enschede, and what their routes and preferred spots are. Dave Borghuis, an Enschede resident, was not impressed and filed an official complaint. “I don’t think it’s okay for the municipality to track its citizens in this way,” he said. “If you walk around the city, you have to be able to imagine yourself unwatched.”

    Enschede is enthusiastic about the advantages of the smart city. The municipality says it is saving €36m in infrastructure investments by launching a smart traffic app that rewards people for good behaviour like cycling, walking and using public transport. (Ironically, one of the rewards is a free day of private parking.) Only those who mine the small print will discover that the app creates “personal mobility profiles”, and that the collected personal data belongs to the company Mobidot.
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  2. Finally, there’s what the authors call “political security” – using AI to automate tasks involved in surveillance, persuasion (creating targeted propaganda) and deception (eg, manipulating videos). We can also expect new kinds of attack based on machine-learning’s capability to infer human behaviours, moods and beliefs from available data. This technology will obviously be welcomed by authoritarian states, but it will also further undermine the ability of democracies to sustain truthful public debates. The bots and fake Facebook accounts that currently pollute our public sphere will look awfully amateurish in a couple of years.

    The report is available as a free download and is worth reading in full. If it were about the dangers of future or speculative technologies, then it might be reasonable to dismiss it as academic scare-mongering. The alarming thing is most of the problematic capabilities that its authors envisage are already available and in many cases are currently embedded in many of the networked services that we use every day. William Gibson was right: the future has already arrived.
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  3. The “bad part of town” will be full of algorithms that shuffle you straight from high-school detention into the prison system. The rich part of town will get mirror-glassed limos that breeze through the smart red lights to seamlessly deliver the aristocracy from curb into penthouse.

    These aren’t the “best practices” beloved by software engineers; they’re just the standard urban practices, with software layered over. It’s urban design as the barbarian’s varnish on urbanism. People could have it otherwise, technically, if they really wanted it and had the political will, but they don’t. So they won’t get it.
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  4. Here’s one example: In 2014, Maine Gov. Paul LePage released data to the public detailing over 3,000 transactions from welfare recipients using EBT cards in the state. (EBT cards are like state-issued debit cards, and can be used to disperse benefits like food stamps.)

    LePage created a list of every time this money had been used in a strip club, liquor store, or bar, and used it to push his political agenda of limiting access to state benefits. LePage’s list represents a tiny fraction of overall EBT withdrawals, but it effectively reinforced negative stereotypes and narratives about who relies on welfare benefits and why.

    I spoke with Eubanks recently about her new book, and why she believes automated technologies are being used to rig the welfare system against the people who need it the most.

    A lightly edited transcript of our conversation follows.
    Sean Illing

    What’s the thesis of your book?
    Virginia Eubanks

    There’s a collision of political forces and technical innovations that are devastating poor and working-class families in America.
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  5. urope has propelled past the United States when it comes to constraining the abuses of Big Tech. In June, the European Union fined Google $2.7 billion for steering web users to its shopping site, and investigations remain active over similar treatment on Android phones. European regulators fined Facebook for lying about whether it could match user profiles with phone numbers on its messaging acquisition WhatsApp. They demanded Apple repay $15.3 billion in back taxes in Ireland. And they forced Amazon to change its e-book contracts, which they claimed inappropriately squeezed publishers.
    AP Photo/Rick Bowmer

    Trust-Busted: In 2002, Microsoft Chairman Bill Gates had to testify at federal court in his company's antitrust case. The public trial led Microsoft to sfoten its aggressive strategy against rivals.

    Unfortunately, these actions were treated mainly as the cost of doing business. The Facebook fine totaled not even 1 percent of the $22 billion purchase price for WhatsApp, and it allowed the two companies to remain partnered. Government policy, in effect, has “told these companies that the smart thing to do is to lie to us and break the law,” said Scott Galloway in his presentation. Google’s remedy in the shopping case still forces rivals to bid for placement at the top of the page, with Google Shopping spun off as a stand-alone competitor. This does weaken Google’s power and solves the “equal treatment” problem, but it doesn’t protect consumers, who will ultimately pay for those costly bids. “The EU got a $2.7 billion fine to hold a party and bail out Greek banks,” said Gary Reback, an antitrust lawyer and critic of the EU’s actions. “No amount of money will make a difference.”

    However, one thing might: Europe’s increasing move toward data privacy. The General Data Protection Regulation (GDPR), scheduled for implementation in May 2018, empowers European web users to affirmatively opt out of having their data collected, with high penalties for non-compliance. Consumers will be able to obtain their personal data and learn how it is used. They can request that their data be erased completely (known as the “right to be forgotten”) as well as prohibited from sale to third parties. Platforms could not condition use of their products on data collection. A separate, not-yet-finalized regulation called ePrivacy would forbid platforms from tracking users across separate apps, websites, and devices.
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  6. Some entries are ambiguous. Take Microsoft, under the “operational services” category. PayPal apparently supplies the tech company with an image of a customer–a photo or video–or their image from an identity document for the purposes of “facial image comparison for fraud protection” and “research and testing as to appropriateness of new products.” The former sounds like some kind of facial recognition system that PayPal uses to look for fraud. But the latter is uneasily broad. What kind of research is Microsoft doing using pictures of PayPal users’ faces? PayPal did not comment on this specific question.
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  7. There are three main factors driving this shift from GIS technologies to location intelligence:

    New data streams. Location intelligence incorporates open data, real-time data streams, and big datasets from all of kinds of internet-connected systems, devices and sensors, many from sources external to the business. GIS has relied primarily on proprietary geographic datasets owned by the business. For example, with LI:

    Insurers are using location intelligence and open weather data to make real-time decisions on how to support their policyholders during a natural disaster.
    Real estate investors are using location intelligence and open transit data to evaluate new opportunities for growth.
    Banks are using credit card transactions and demographic data to understand city dynamics.

    New methods of analysis. Location intelligence embraces new methods of analyzing location data for business process optimization and prediction, while traditional GIS analysis methods focus on reporting historic geographic information. For example, with LI:
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  8. The rise of big data means that probabilities are becoming a larger part of life. And our misunderstandings have real costs

    Surprisingly cogent meditation on probabilistic thinking in the NYT.


    1. People round probabilities up to 100% or down to 0%.

    2. People call probability “wrong” if <50% events happen

    3. People need a story to take <50% scenarios seriously

    I was wrong about a major aspect of probabilities.

    They are inherently hard to grasp. That’s especially true for an individual event, like a war or election. People understand that if they roll a die 100 times, they will get some 1’s. But when they see a probability for one event, they tend to think: Is this going to happen or not?

    They then effectively round to 0 or to 100 percent.

    For an individual event, people can’t resist saying that a probability was “right” if it was above 50 percent and “wrong” if it was below 50 percent. When this happens, those of us who believe in probabilities can’t just shake our heads and mutter about white Christmases. We have to communicate more effectively.

    I think part of the answer lies with Kahneman’s insight: Human beings need a story.

    It’s not enough to say an event has a 10 percent probability. People need a story that forces them to visualize the unlikely event — so they don’t round 10 to zero.

    Imagine that a forecast giving Candidate X a 10 percent chance included a prominent link, “How X wins.” It would explain how the polling could be off and include a winning map for X. It would all but shout: This really may happen.
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  9. no serious scholar of modern geopolitics disputes that we are now at war — a new kind of information-based war, but war, nevertheless — with Russia in particular, but in all honesty, with a multitude of nation states and stateless actors bent on destroying western democratic capitalism. They are using our most sophisticated and complex technology platforms to wage this war — and so far, we’re losing. Badly.

    Why? According to sources I’ve talked to both at the big tech companies and in government, each side feels the other is ignorant, arrogant, misguided, and incapable of understanding the other side’s point of view. There’s almost no data sharing, trust, or cooperation between them. We’re stuck in an old model of lobbying, soft power, and the occasional confrontational hearing.

    Not exactly the kind of public-private partnership we need to win a war, much less a peace.

    Am I arguing that the government should take over Google, Amazon, Facebook, and Apple so as to beat back Russian info-ops? No, of course not. But our current response to Russian aggression illustrates the lack of partnership and co-ordination between government and our most valuable private sector companies. And I am hoping to raise an alarm: When the private sector has markedly better information, processing power, and personnel than the public sector, one will only strengthen, while the latter will weaken. We’re seeing it play out in our current politics, and if you believe in the American idea, you should be extremely concerned.
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  10. Similarly, GOOG in 2014 started reorganizing itself to focus on artificial intelligence only. In January 2014, GOOG bought DeepMind, and in September they shutdown Orkut (one of their few social products which had momentary success in some countries) forever. The Alphabet Inc restructuring was announced in August 2015 but it likely took many months of meetings and bureaucracy. The restructuring was important to focus the web-oriented departments at GOOG towards a simple mission. GOOG sees no future in the simple Search market, and announces to be migrating “From Search to Suggest” (in Eric Schmidt’s own words) and being an “AI first company” (in Sundar Pichai’s own words). GOOG is currently slightly behind FB in terms of how fast it is growing its dominance of the web, but due to their technical expertise, vast budget, influence and vision, in the long run its AI assets will play a massive role on the internet. They know what they are doing.

    These are no longer the same companies as 4 years ago. GOOG is not anymore an internet company, it’s the knowledge internet company. FB is not an internet company, it’s the social internet company. They used to attempt to compete, and this competition kept the internet market diverse. Today, however, they seem mostly satisfied with their orthogonal dominance of parts of the Web, and we are losing diversity of choices. Which leads us to another part of the internet: e-commerce and AMZN.

    AMZN does not focus on making profit.
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