Twitter Can Now Predict Crime, and This Raises Serious Questions


Motherboard: “Police departments in New York City may soon be using geo-tagged tweets to predict crime. It sounds like a far-fetched sci-fi scenario a la Minority Report, but when I contacted Dr. Matthew Greber, the University of Virginia researcher behind the technology, he explained that the system is far more mathematical than metaphysical.
The system Greber has devised is an amalgam of both old and new techniques. Currently, many police departments target hot spots for criminal activity based on actual occurrences of crime. This approach, called kernel density estimation (KDE), involves pairing a historical crime record with a geographic location and using a probability function to calculate the possibility of future crimes occurring in that area. While KDE is a serviceable approach to anticipating crime, it pales in comparison to the dynamism of Twitter’s real-time data stream, according to Dr. Gerber’s research paper “Predicting Crime Using Twitter and Kernel Density Estimation”.
Dr. Greber’s approach is similar to KDE, but deals in the ethereal realm of data and language, not paperwork. The system involves mapping the Twitter environment; much like how police currently map the physical environment with KDE. The big difference is that Greber is looking at what people are talking about in real time, as well as what they do after the fact, and seeing how well they match up. The algorithms look for certain language that is likely to indicate the imminent occurrence of a crime in the area, Greber says. “We might observe people talking about going out, getting drunk, going to bars, sporting events, and so on—we know that these sort of events correlate with crime, and that’s what the models are picking up on.”
Once this data is collected, the GPS tags in tweets allows Greber and his team to pin them to a virtual map and outline hot spots for potential crime. However, everyone who tweets about hitting the club later isn’t necessarily going to commit a crime. Greber tests the accuracy of his approach by comparing Twitter-based KDE predictions with traditional KDE predictions based on police data alone. The big question is, does it work? For Greber, the answer is a firm “sometimes.” “It helps for some, and it hurts for others,” he says.
According to the study’s results, Twitter-based KDE analysis yielded improvements in predictive accuracy over traditional KDE for stalking, criminal damage, and gambling. Arson, kidnapping, and intimidation, on the other hand, showed a decrease in accuracy from traditional KDE analysis. It’s not clear why these crimes are harder to predict using Twitter, but the study notes that the issue may lie with the kind of language used on Twitter, which is characterized by shorthand and informal language that can be difficult for algorithms to parse.
This kind of approach to high-tech crime prevention brings up the familiar debate over privacy and the use of users’ date for purposes they didn’t explicitly agree to. The case becomes especially sensitive when data will be used by police to track down criminals. On this point, though he acknowledges post-Snowden societal skepticism regarding data harvesting for state purposes, Greber is indifferent. “People sign up to have their tweets GPS tagged. It’s an opt-in thing, and if you don’t do it, your tweets won’t be collected in this way,” he says. “Twitter is a public service, and I think people are pretty aware of that.”…

Twenty-one European Cities Advance in Bloomberg Philanthropies' Mayors Challenge Competition to Create Innovative Solutions to Urban Challenges


Press Release: “Bloomberg Philanthropies today revealed the 21 European cities that have emerged as final contenders in its 2013-2014 Mayors Challenge, a competition to inspire cities to generate innovative ideas that solve major challenges and improve city life, and that ultimately can spread to other cities. One grand prize winner will receive €5 million for the most creative and transferable idea. Four additional cities will be awarded €1 million, and all will be announced in the fall. The finalists’ proposed solutions address some of Europe’s most critical issue areas: youth unemployment, aging populations, civic engagement, economic development, environment and energy concerns, public health and safety, and making government more efficient…
James Anderson, the head of government innovation for Bloomberg Philanthropies, said: “While the ideas are very diverse, we identified key themes. The ideas tended toward networked, distributed solutions as opposed to costly centralized ones. There was a lot of interest in citizen engagement as both a means and end. Technology that concretely and positively affects the lives of individual citizens – from the blind person in Warsaw to the unemployed youth in Amsterdam to the homeowner in Schaerbeek — also played a significant role.”
Bloomberg Philanthropies staff and an independent selection committee of 12 members from across Europe closely considered each application over multiple rounds of review, culminating in feedback and selection earlier this month, resulting in 21 cities’ ideas moving forward for further development. The submissions will be judged on four critieria: vision, potential for impact, implementation plan, and potential to spread to other cities. The finalists and their ideas are:

  1. AMSTERDAM, Netherlands – Youth Unemployment: Tackling widespread youth unemployment by equipping young people with 21st century skills and connecting them with jobs and apprenticeships across Europe through an online game
  2. ATHENS, Greece – Civic Engagement: Empowering citizens with a new online platform to address the large number of small-scale urban challenges accelerated by the Greek economic crisis
  3. BARCELONA, Spain – Aging: Improving quality of life and limiting social isolation by establishing a network of public and private support – including family, friends, social workers, and volunteers – for each elderly citizen
  4. BOLOGNA, Italy – Youth Unemployment: Building an urban scale model of informal education labs and civic engagement to prevent youth unemployment by teaching children aged 6-16 entrepreneurship and 21st century skills
  5. BRISTOL, United Kingdom – Health/Anti-obesity: Tackling obesity and unemployment by creating a new economic system that increases access to locally grown, healthy foods
  6. BRNO, Czech Republic – Public Safety/Civic Engagement: Engaging citizens in keeping their own communities safe to build social cohesion and reduce crime
  7. CARDIFF, United Kingdom – Economic Development: Increasing productivity little by little in residents’ personal and professional lives, so that a series of small improvements add up to a much more productive city
  8. FLORENCE, Italy – Economic Development: Combatting unemployment with a new economic development model that combines technology and social innovation, targeting the city’s historic artisan and maker community
  9. GDAŃSK, Poland – Civic Engagement: Re-instilling faith in local democracy by mandating that city government formally debate local issues put forward by citizens
  10. KIRKLEES, United Kingdom – Social Capital: Pooling the city and community’s idle assets – from vehicles to unused spaces to citizens’ untapped time and expertise – to help the area make the most of what it has and do more with less
  11. KRAKOW, Poland – Transportation: Implementing smart, personalized transportation incentives and a seamless and unified public transit payment system to convince residents to opt for greener modes of transportation
  12. LISBON, Portugal – Energy: Transforming wasted kinetic energy generated by the city’s commuting traffic into electricity, reducing the carbon footprint and increasing environmental sustainability
  13. LONDON, United Kingdom – Public Health: Empowering citizens to monitor and improve their own health through a coordinated, multi-stakeholder platform and new technologies that dramatically improve quality of life and reduce health care costs
  14. MADRID, Spain – Energy: Diversifying its renewable energy options by finding and funding the best ways to harvest underground power, such as wasted heat generated by the city’s below-ground infrastructure
  15. SCHAERBEEK, Belgium – Energy: Using proven flyover and 3D geothermal mapping technology to provide each homeowner and tenant with a personalized energy audit and incentives to invest in energy-saving strategies
  16. SOFIA, Bulgaria – Civic Engagement: Transforming public spaces by deploying mobile art units to work side-by-side with local residents, re-envisioning and rejuvenating underused spaces and increasing civic engagement
  17. STARA ZAGORA, Bulgaria – Economic Development: Reversing the brain-drain of the city’s best and brightest by helping young entrepreneurs turn promising ideas into local high-tech businesses
  18. STOCKHOLM, Sweden – Environment: Combatting climate change by engaging citizens to produce biochar, an organic material that increases tree growth, sequesters carbon, and purifies storm runoff
  19. THE HAGUE, Netherlands – Civic Engagement: Enabling citizens to allocate a portion of their own tax money to support the local projects they most believe in
  20. WARSAW, Poland – Transportation/Accessibility: Enabling the blind and visually impaired to navigate the city as easily as their sighted peers by providing high-tech auditory alerts which will save them travel time and increase their independence
  21. YORK, United Kingdom – Government Systems: Revolutionizing the way citizens, businesses, and others can propose new ideas to solve top city problems, providing a more intelligent way to acquire or develop the best solutions, thus enabling greater civic participation and saving the city both time and money

Further detail and related elements for this year’s Mayors Challenge can be found via: http://mayorschallenge.bloomberg.org/”

In defense of “slacktivism”: The Human Rights Campaign Facebook logo as digital activism


Stephanie Vie in First Monday: “This paper examines the Human Rights Campaign (HRC) Marriage Equality logo as an example of a meme to further understandings of memetic transmission in social media technologies. The HRC meme is an important example of how even seemingly insignificant moves such as adopting a logo and displaying it online can serve to combat microaggressions, or the damaging results of everyday bias and discrimination against marginalized groups. This article suggests that even small moves of support, such as changing one’s Facebook status to a memetic image, assist by demonstrating a supportive environment for those who identify with marginalized groups and by drawing awareness to important causes. Often dismissed as “slacktivism,” I argue instead that the digital activism made possible through social media memes can build awareness of crucial issues, which can then lead to action.”

How Cities Can Be Designed to Help—or Hinder—Sharing


Jay Walljasper in Yes!: Centuries before someone first uttered the words “sharing economy,” the steady rise of cities embodied both the principles and promise of that phrase. The reason more than half the people on earth now live in urban areas is the advantages that come from sharing resources, infrastructure, and lives with other people. Essential commons belonging to all of us, ranging from transportation systems to public health safeguards to plentiful social connections, are easier to create and maintain in a populated area.
Think about typical urban dwellers. They are more likely to reside in an apartment building, shared household, or compact living unit (saving on heating, utilities, original construction costs, and other expenses), walk or take transit (saving the environment as well as money), know a wide range of people (expanding their circle of friends and colleagues), and encounter new experiences (increasing their knowledge and skills).
Access to these opportunities for sharing offers economic, social, environmental, and educational rewards. But living in a populated area does not automatically mean more sharing. Indeed, the classic suburban lifestyle—a big, single-family house and a big yard isolated from everything else and reachable only by automobile—makes sharing extremely difficult….
“The suburbs were designed as a landscape to maximize consumption,” Fisher explains. “It worked against sharing of any kind. People had all this stuff in their houses and garages, which was going unused most of the time.”
Autos replaced streetcars. Kids rode school buses instead of walking to school.
Everyone bought their own lawn mower, shovels, tools, sports equipment, and grills.
Even the proverbial cup of sugar borrowed from a neighbor disappeared in favor of the 10-pound bag bought at the supermarket.
As our spending grew, our need for social connections shrank. “Mass consumption was good for the economy, but bad for our well-being,” Fisher notes. He now sees changes ahead for our communities as the economy evolves.
“The new economy is all about innovation, which depends on maximizing interaction, not consumption.”
This means redesigning our communities to bring people together by giving everyone more opportunities to “walk, live close together, and share.”
This shift can already be seen in farmers markets, co-working spaces, tool libraries, bike sharing systems, co-ops, credit unions, public spaces, and other sharing projects everywhere.
“Creative people in cities around the world are rising up…” declares Neal Gorenflo, co-founder of Shareable magazine. “We are not protesting, and we are not asking for permission, and we are not waiting—we are building a people-powered economy right under everyone’s noses.”
Excited by this emerging grassroots movement, Shareable recently launched the Sharing Cities Network to be an independent resource “for sharing innovators to discover together how to create as many sharing cities around the world as fast as possible.”
The aim is to help empower and connect local initiatives around the world through online forums, peer learning, and other ways to boost collaboration, share best practices, and catalyze new projects.”

Why Are Rich Countries Democratic?


Ricardo Hausmann at Project Syndicate: “When Adam Smith was 22, he famously proclaimed that, “Little else is requisite to carry a state to the highest degree of opulence from the lowest barbarism, but peace, easy taxes, and a tolerable administration of justice: all the rest being brought about by the natural course of things.” Today, almost 260 years later, we know that nothing could be further from the truth.
The disappearance of Malaysia Airlines Flight 370 shows how wrong Smith was, for it highlights the intricate interaction between modern production and the state. To make air travel feasible and safe, states ensure that pilots know how to fly and that aircraft pass stringent tests. They build airports and provide radar and satellites that can track planes, air traffic controllers to keep them apart, and security services to keep terrorists on the ground. And, when something goes wrong, it is not peace, easy taxes, and justice that are called in to assist; it is professional, well-resourced government agencies.
All advanced economies today seem to need much more than the young Smith assumed. And their governments are not only large and complex, comprising thousands of agencies that administer millions of pages of rules and regulations; they are also democratic – and not just because they hold elections every so often. Why?
By the time he published The Wealth of Nations, at age 43, Smith had become the first complexity scientist. He understood that the economy was a complex system that needed to coordinate the work of thousands of people just to make things as simple as a meal or a suit.
But Smith also understood that while the economy was too intricate to be organized by anybody, it has the capacity to self-organize. It possesses an “invisible hand,” which operates through market prices to provide an information system that can be used to calculate whether using resources for a given purpose is worthwhile – that is, profitable.
Profit is an incentive system that leads firms and individuals to respond to the information provided by prices. And capital markets are a resource-mobilization system that provides money to those companies and projects that are expected to be profitable – that is, the ones that respond adequately to market prices.
But modern production requires many inputs that markets do not provide. And, as in the case of airlines, these inputs – rules, standards, certifications, infrastructure, schools and training centers, scientific labs, security services, among others – are deeply complementary to the ones that can be procured in markets. They interact in the most intricate ways with the activities that markets organize.
So here’s the question: Who controls the provision of the publicly provided inputs? The prime minister? The legislature? Which country’s top judges have read the millions of pages of legislation or considered how they complement or contradict each other, much less applied them to the myriad different activities that comprise the economy? Even a presidential executive cannot be fully aware of the things that are done or not done by the thousands of government agencies and how they affect each part of society.
This is an information-rich problem, and, like the social-coordination challenge that the market addresses, it does not allow for centralized control. What is needed is something like the invisible hand of the market: a mechanism for self-organization. Elections clearly are not enough, because they typically occur at two- or four-year intervals and collect very little information per voter.
Instead, successful political systems have had to create an alternative invisible hand – a system that decentralizes the power to identify problems, propose solutions, and monitor performance, such that decisions are made with much more information.
To take just one example, the United States’ federal government accounts for just 537 of the country’s roughly 500,000 elected positions. Clearly, there is much more going on elsewhere.
The US Congress has 100 senators with 40 aides each, and 435 representatives with 25 aides each. They are organized into 42 committees and 182 subcommittees, meaning that there are 224 parallel conversations going on. And this group of more than 15,000 people is not alone. Facing them are some 22,000 registered lobbyists, whose mission is (among other goals) to sit down with legislators and draft legislation.
This, together with a free press, is part of the structure that reads the millions of pages of legislation and monitors what government agencies do and do not do. It generates the information and the incentives to respond to it. It affects the allocation of budgetary resources. It is an open system in which anybody can create news or find a lobbyist to make his case, whether it is to save the whales or to eat them.
Without such a mechanism, the political system cannot provide the kind of environment that modern economies need. That is why all rich countries are democracies, and it is why some countries, like my own (Venezuela), are becoming poorer. Although some of these countries do hold elections, they tend to stumble at even the simplest of coordination problems. Lining up to vote is no guarantee that citizens will not also have to line up for toilet paper.”

Big data: are we making a big mistake?


Tim Harford in the Financial Times: “Cheerleaders for big data have made four exciting claims, each one reflected in the success of Google Flu Trends: that data analysis produces uncannily accurate results; that every single data point can be captured, making old statistical sampling techniques obsolete; that it is passé to fret about what causes what, because statistical correlation tells us what we need to know; and that scientific or statistical models aren’t needed because, to quote “The End of Theory”, a provocative essay published in Wired in 2008, “with enough data, the numbers speak for themselves”. Unfortunately, these four articles of faith are at best optimistic oversimplifications. At worst, according to David Spiegelhalter, Winton Professor of the Public Understanding of Risk at Cambridge university, they can be “complete bollocks. Absolute nonsense.”…
But big data do not solve the problem that has obsessed statisticians and scientists for centuries: the problem of insight, of inferring what is going on, and figuring out how we might intervene to change a system for the better.
“We have a new resource here,” says Professor David Hand of Imperial College London. “But nobody wants ‘data’. What they want are the answers.”
To use big data to produce such answers will require large strides in statistical methods.
“It’s the wild west right now,” says Patrick Wolfe of UCL. “People who are clever and driven will twist and turn and use every tool to get sense out of these data sets, and that’s cool. But we’re flying a little bit blind at the moment.”
Statisticians are scrambling to develop new methods to seize the opportunity of big data. Such new methods are essential but they will work by building on the old statistical lessons, not by ignoring them.
Recall big data’s four articles of faith. Uncanny accuracy is easy to overrate if we simply ignore false positives, as with Target’s pregnancy predictor. The claim that causation has been “knocked off its pedestal” is fine if we are making predictions in a stable environment but not if the world is changing (as with Flu Trends) or if we ourselves hope to change it. The promise that “N = All”, and therefore that sampling bias does not matter, is simply not true in most cases that count. As for the idea that “with enough data, the numbers speak for themselves” – that seems hopelessly naive in data sets where spurious patterns vastly outnumber genuine discoveries.
“Big data” has arrived, but big insights have not. The challenge now is to solve new problems and gain new answers – without making the same old statistical mistakes on a grander scale than ever.”

The data gold rush


Neelie KROES (European Commission):  “Nearly 200 years ago, the industrial revolution saw new networks take over. Not just a new form of transport, the railways connected industries, connected people, energised the economy, transformed society.
Now we stand facing a new industrial revolution: a digital one.
With cloud computing its new engine, big data its new fuel. Transporting the amazing innovations of the internet, and the internet of things. Running on broadband rails: fast, reliable, pervasive.
My dream is that Europe takes its full part. With European industry able to supply, European citizens and businesses able to benefit, European governments able and willing to support. But we must get all those components right.
What does it mean to say we’re in the big data era?
First, it means more data than ever at our disposal. Take all the information of humanity from the dawn of civilisation until 2003 – nowadays that is produced in just two days. We are also acting to have more and more of it become available as open data, for science, for experimentation, for new products and services.
Second, we have ever more ways – not just to collect that data – but to manage it, manipulate it, use it. That is the magic to find value amid the mass of data. The right infrastructure, the right networks, the right computing capacity and, last but not least, the right analysis methods and algorithms help us break through the mountains of rock to find the gold within.
Third, this is not just some niche product for tech-lovers. The impact and difference to people’s lives are huge: in so many fields.
Transforming healthcare, using data to develop new drugs, and save lives. Greener cities with fewer traffic jams, and smarter use of public money.
A business boost: like retailers who communicate smarter with customers, for more personalisation, more productivity, a better bottom line.
No wonder big data is growing 40% a year. No wonder data jobs grow fast. No wonder skills and profiles that didn’t exist a few years ago are now hot property: and we need them all, from data cleaner to data manager to data scientist.
This can make a difference to people’s lives. Wherever you sit in the data ecosystem – never forget that. Never forget that real impact and real potential.
Politicians are starting to get this. The EU’s Presidents and Prime Ministers have recognised the boost to productivity, innovation and better services from big data and cloud computing.
But those technologies need the right environment. We can’t go on struggling with poor quality broadband. With each country trying on its own. With infrastructure and research that are individual and ineffective, separate and subscale. With different laws and practices shackling and shattering the single market. We can’t go on like that.
Nor can we continue in an atmosphere of insecurity and mistrust.
Recent revelations show what is possible online. They show implications for privacy, security, and rights.
You can react in two ways. One is to throw up your hands and surrender. To give up and put big data in the box marked “too difficult”. To turn away from this opportunity, and turn your back on problems that need to be solved, from cancer to climate change. Or – even worse – to simply accept that Europe won’t figure on this mapbut will be reduced to importing the results and products of others.
Alternatively: you can decide that we are going to master big data – and master all its dependencies, requirements and implications, including cloud and other infrastructures, Internet of things technologies as well as privacy and security. And do it on our own terms.
And by the way – privacy and security safeguards do not just have to be about protecting and limiting. Data generates value, and unlocks the door to new opportunities: you don’t need to “protect” people from their own assets. What you need is to empower people, give them control, give them a fair share of that value. Give them rights over their data – and responsibilities too, and the digital tools to exercise them. And ensure that the networks and systems they use are affordable, flexible, resilient, trustworthy, secure.
One thing is clear: the answer to greater security is not just to build walls. Many millennia ago, the Greek people realised that. They realised that you can build walls as high and as strong as you like – it won’t make a difference, not without the right awareness, the right risk management, the right security, at every link in the chain. If only the Trojans had realised that too! The same is true in the digital age: keep our data locked up in Europe, engage in an impossible dream of isolation, and we lose an opportunity; without gaining any security.
But master all these areas, and we would truly have mastered big data. Then we would have showed technology can take account of democratic values; and that a dynamic democracy can cope with technology. Then we would have a boost to benefit every European.
So let’s turn this asset into gold. With the infrastructure to capture and process. Cloud capability that is efficient, affordable, on-demand. Let’s tackle the obstacles, from standards and certification, trust and security, to ownership and copyright. With the right skills, so our workforce can seize this opportunity. With new partnerships, getting all the right players together. And investing in research and innovation. Over the next two years, we are putting 90 million euros on the table for big data and 125 million for the cloud.
I want to respond to this economic imperative. And I want to respond to the call of the European Council – looking at all the aspects relevant to tomorrow’s digital economy.
You can help us build this future. All of you. Helping to bring about the digital data-driven economy of the future. Expanding and depening the ecosystem around data. New players, new intermediaries, new solutions, new jobs, new growth….”

Coordinating the Commons: Diversity & Dynamics in Open Collaborations


Dissertation by Jonathan T. Morgan: “The success of Wikipedia demonstrates that open collaboration can be an effective model for organizing geographically-distributed volunteers to perform complex, sustained work at a massive scale. However, Wikipedia’s history also demonstrates some of the challenges that large, long-term open collaborations face: the core community of Wikipedia editors—the volunteers who contribute most of the encyclopedia’s content and ensure that articles are correct and consistent — has been gradually shrinking since 2007, in part because Wikipedia’s social climate has become increasingly inhospitable for newcomers, female editors, and editors from other underrepresented demographics. Previous research studies of change over time within other work contexts, such as corporations, suggests that incremental processes such as bureaucratic formalization can make organizations more rule-bound and less adaptable — in effect, less open— as they grow and age. There has been little research on how open collaborations like Wikipedia change over time, and on the impact of those changes on the social dynamics of the collaborating community and the way community members prioritize and perform work. Learning from Wikipedia’s successes and failures can help researchers and designers understand how to support open collaborations in other domains — such as Free/Libre Open Source Software, Citizen Science, and Citizen Journalism.

In this dissertation, I examine the role of openness, and the potential antecedents and consequences of formalization, within Wikipedia through an analysis of three distinct but interrelated social structures: community-created rules within the Wikipedia policy environment, coordination work and group dynamics within self-organized open teams called WikiProjects, and the socialization mechanisms that Wikipedia editors use to teach new community members how to participate.To inquire further, I have designed a new editor peer support space, the Wikipedia Teahouse, based on the findings from my empirical studies. The Teahouse is a volunteer-driven project that provides a welcoming and engaging environment in which new editors can learn how to be productive members of the Wikipedia community, with the goal of increasing the number and diversity of newcomers who go on to make substantial contributions to Wikipedia …”

Overcoming 'Tragedies of the Commons' with a Self-Regulating, Participatory Market Society


Paper by Dirk Helbing; “Our society is fundamentally changing. These days, almost nothing works without a computer chip. Processing power doubles every 18 months and will exceed the capabilities of human brains in about ten years from now. Some time ago, IBM’s Big Blue computer already beat the best chess player. Meanwhile, computers perform about 70 percent of all financial transactions, and IBM’s Watson advises customers better than human telephone hotlines. Will computers and robots soon replace skilled labor? In many European countries, unemployment is reaching historical heights. The forthcoming economic and social impact of future information and communication technologies (ICT) will be huge – probably more significant than that caused by the steam engine, or by nano- or biotechnology.
The storage capacity for data is growing even faster than computational capacity. Within just a year we will soon generate more data than in the entire history of humankind. The “Internet of Things” will network trillions of sensors. Unimaginable amounts of data will be collected. Big Data is already being praised as the “oil of the 21st century”. What opportunities and risks does this create for our society, economy, and environment?”