Twitter releasing trove of user data to scientists for research

Curated on Posted on by Stefaan Verhulst

Joe Silver at ArsTechnica: “Twitter has a 200-million-strong and ever-growing user base that broadcasts 500 million updates daily. It has been lauded for its ability to unsettle repressive political regimes, bring much-needed accountability to corporations that mistreat their customers, and combat other societal ills (whether such characterizations are, in fact, accurate). Now, the company has taken aim at disrupting another important sphere of human society: the scientific research community.
Back in February, the site announced its plan—in collaboration with Gnip—to provide a handful of research institutions with free access to its data sets from 2006 to the present. It’s a pilot program called “Twitter Data Grants,” with the hashtag #DataGrants. At the time, Twitter’s engineering blog explained the plan to enlist grant applications to access its treasure trove of user data:

Twitter has an expansive set of data from which we can glean insights and learn about a variety of topics, from health-related information such as when and where the flu may hit to global events like ringing in the new year. To date, it has been challenging for researchers outside the company who are tackling big questions to collaborate with us to access our public, historical data. Our Data Grants program aims to change that by connecting research institutions and academics with the data they need.

In April, Twitter announced that, after reviewing the more than 1,300 proposals submitted from more than 60 different countries, it had selected six institutions to provide with data access. Projects approved included a study of foodborne gastrointestinal illnesses, a study measuring happiness levels in cities based on images shared on Twitter, and a study using geosocial intelligence to model urban flooding in Jakarta, Indonesia. There’s even a project exploring the relationship between tweets and sports team performance.
Twitter did not directly respond to our questions on Tuesday afternoon regarding the specific amount and types of data the company is providing to the six institutions. But in its privacy policy, Twitter explains that most user information is intended to be broadcast widely. As a result, the company likely believes that sharing such information with scientific researchers is well within its rights, as its services “are primarily designed to help you share information with the world,” Twitter says. “Most of the information you provide us is information you are asking us to make public.”
While mining such data sets will undoubtedly aid scientists in conducting experiments for which similar data was previously either unavailable or quite limited, these applications raise some legal and ethical questions. For example, Scientific American has asked whether Twitter will be able to retain any legal rights to scientific findings and whether mining tweets (many of which are not publicly accessible) for scientific research when Twitter users have not agreed to such uses is ethically sound.
In response, computational epidemiologists Caitlin Rivers and Bryan Lewis have proposed guidelines for ethical research practices when using social media data, such as avoiding personally identifiable information and making all the results publicly available….”

Closing the Feedback Loop: Can Technology Bridge the Accountability Gap

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(WorldBank) Book edited by Björn-Sören Gigler and Savita Bailur:  “This book is a collection of articles, written by both academics and practitioners as an evidence base for citizen engagement through information and communication technologies (ICTs). In it, the authors ask: how do ICTs empower through participation, transparency and accountability? Specifically, the authors examine two principal questions: Are technologies an accelerator to closing the “accountability gap” – the space between the supply (governments, service providers) and demand (citizens, communities, civil society organizations or CSOs) that requires bridging for open and collaborative governance? And under what conditions does this occur? The introductory chapters lay the theoretical groundwork for understanding the potential of technologies to achieving intended goals. Chapter 1 takes us through the theoretical linkages between empowerment, participation, transparency and accountability. In Chapter 2, the authors devise an informational capability framework, relating human abilities and well-being to the use of ICTs. The chapters to follow highlight practical examples that operationalize ICT-led initiatives. Chapter 3 reviews a sample of projects targeting the goals of transparency and accountability in governance to make preliminary conclusions around what evidence exists to date, and where to go from here. In chapter 4, the author reviews the process of interactive community mapping (ICM) with examples that support general local development and others that mitigate natural disasters. Chapter 5 examines crowdsourcing in fragile states to track aid flows, report on incitement or organize grassroots movements. In chapter 6, the author reviews Check My School (CMS), a community monitoring project in the Philippines designed to track the provision of services in public schools. Chapter 7 introduces four key ICT-led, citizen-governance initiatives in primary health care in Karnataka, India. Chapter 8 analyzes the World Bank Institute’s use of ICTs in expanding citizen project input to understand the extent to which technologies can either engender a new “feedback loop” or ameliorate a “broken loop”. The authors’ analysis of the evidence signals ICTs as an accelerator to closing the “accountability gap”. In Chapter 9, the authors conclude with the Loch Ness model to illustrate how technologies contribute to shrinking the gap, why the gap remains open in many cases, and what can be done to help close it. This collection is a critical addition to existing literature on ICTs and citizen engagement for two main reasons: first, it is expansive, covering initiatives that leverage a wide range of technology tools, from mobile phone reporting to crowdsourcing to interactive mapping; second, it is the first of its kind to offer concrete recommendations on how to close feedback loops.”

Politics or technology – which will save the world?

Curated on Posted on by Stefaan Verhulst

David Runciman in the Guardian: (Politics by David Runciman is due from Profile ..It is the first in a series of “Ideas in Profile”) “The most significant revolution of the 21st century so far is not political. It is the information technology revolution. Its transformative effects are everywhere. In many places, rapid technological change stands in stark contrast to the lack of political change. Take the United States. Its political system has hardly changed at all in the past 25 years. Even the moments of apparent transformation – such as the election of Obama in 2008 – have only reinforced how entrenched the established order is: once the excitement died away, Obama was left facing the same constrained political choices. American politics is stuck in a rut. But the lives of American citizens have been revolutionised over the same period. The birth of the web and the development of cheap and efficient devices through which to access it have completely altered the way people connect with each other. Networks of people with shared interests, tastes, concerns, fetishes, prejudices and fears have sprung up in limitless varieties. The information technology revolution has changed the way human beings befriend each other, how they meet, date, communicate, medicate, investigate, negotiate and decide who they want to be and what they want to do. Many aspects of our online world would be unrecognisable to someone who was transplanted here from any point in the 20th century. But the infighting and gridlock in Washington would be all too familiar.
This isn’t just an American story. China hasn’t changed much politically since 4 June 1989, when the massacre in Tiananmen Square snuffed out a would-be revolution and secured the current regime’s hold on power. But China itself has been totally altered since then. Economic growth is a large part of the difference. But so is the revolution in technology. A country of more than a billion people, nearly half of whom still live in the countryside, has been transformed by the mobile phone. There are currently over a billion phones in use in China. Ten years ago, fewer than one in 10 Chinese had access to one; today there is nearly one per person. Individuals whose horizons were until very recently constrained by physical geography – to live and die within a radius of a few miles from your birthplace was not unusual for Chinese peasants even into this century – now have access to the wider world. For the present, though maybe not for much longer, the spread of new technology has helped to stifle the call for greater political change. Who needs a political revolution when you’ve got a technological one?

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Technology has the power to make politics seem obsolete. The speed of change leaves government looking slow, cumbersome, unwieldy and often irrelevant. It can also make political thinking look tame by comparison with the big ideas coming out of the tech industry. This doesn’t just apply to far‑out ideas about what will soon be technologically possible: intelligent robots, computer implants in the human brain, virtual reality that is indistinguishable from “real” reality (all things that Ray Kurzweil, co-founder of the Google-sponsored Singularity University, thinks are coming by 2030). In this post-ideological age some of the most exotic political visions are the ones that emerge from discussions about tech. You’ll find more radical libertarians and outright communists among computer scientists than among political scientists. Advances in computing have thrown up fresh ways to think about what it means to own something, what it means to share something and what it means to have a private life at all. These are among the basic questions of modern politics. However, the new answers rarely get expressed in political terms (with the exception of occasional debates about civil rights for robots). More often they are expressions of frustration with politics and sometimes of outright contempt for it. Technology isn’t seen as a way of doing politics better. It’s seen as a way of bypassing politics altogether.
In some circumstances, technology can and should bypass politics. The advent of widespread mobile phone ownership has allowed some of the world’s poorest citizens to wriggle free from the trap of failed government. In countries that lack basic infrastructure – an accessible transport network, a reliable legal system, a usable banking sector – phones enable people to create their own networks of ownership and exchange. In Africa, a grassroots, phone-based banking system has sprung up that for the first time permits money transfers without the physical exchange of cash. This makes it possible for the inhabitants of desperately poor and isolated rural areas to do business outside of their local communities. Technology caused this to happen; government didn’t. For many Africans, phones are an escape route from the constrained existence that bad politics has for so long mired them in.
But it would be a mistake to overstate what phones can do. They won’t rescue anyone from civil war. Africans can use their phones to tell the wider world of the horrors that are still taking place in some parts of the continent – in South Sudan, in Eritrea, in the Niger Delta, in the Central African Republic, in Somalia. Unfortunately the world does not often listen, and nor do the soldiers who are doing the killing. Phones have not changed the basic equation of political security: the people with the guns need a compelling reason not to use them. Technology by itself doesn’t give them that reason. Equally, technology by itself won’t provide the basic infrastructure whose lack it has provided a way around. If there are no functioning roads to get you to market, a phone is a godsend when you have something to sell. But in the long run, you still need the roads. In the end, only politics can rescue you from bad politics…”

Democracy and open data: are the two linked?

Curated on Posted on by Stefaan Verhulst

Molly Shwartz at R-Street: “Are democracies better at practicing open government than less free societies? To find out, I analyzed the 70 countries profiled in the Open Knowledge Foundation’s Open Data Index and compared the rankings against the 2013 Global Democracy Rankings. As a tenet of open government in the digital age, open data practices serve as one indicator of an open government. Overall, there is a strong relationship between democracy and transparency.
Using data collected in October 2013, the top ten countries for openness include the usual bastion-of-democracy suspects: the United Kingdom, the United States, mainland Scandinavia, the Netherlands, Australia, New Zealand and Canada.
There are, however, some noteworthy exceptions. Germany ranks lower than Russia and China. All three rank well above Lithuania. Egypt, Saudi Arabia and Nepal all beat out Belgium. The chart (below) shows the democracy ranking of these same countries from 2008-2013 and highlights the obvious inconsistencies in the correlation between democracy and open data for many countries.
transparency
There are many reasons for such inconsistencies. The implementation of open-government efforts – for instance, opening government data sets – often can be imperfect or even misguided. Drilling down to some of the data behind the Open Data Index scores reveals that even countries that score very well, such as the United States, have room for improvement. For example, the judicial branch generally does not publish data and houses most information behind a pay-wall. The status of legislation and amendments introduced by Congress also often are not available in machine-readable form.
As internationally recognized markers of political freedom and technological innovation, open government initiatives are appealing political tools for politicians looking to gain prominence in the global arena, regardless of whether or not they possess a real commitment to democratic principles. In 2012, Russia made a public push to cultivate open government and open data projects that was enthusiastically endorsed by American institutions. In a June 2012 blog post summarizing a Russian “Open Government Ecosystem” workshop at the World Bank, one World Bank consultant professed the opinion that open government innovations “are happening all over Russia, and are starting to have genuine support from the country’s top leaders.”
Given the Russian government’s penchant for corruption, cronyism, violations of press freedom and increasing restrictions on public access to information, the idea that it was ever committed to government accountability and transparency is dubious at best. This was confirmed by Russia’s May 2013 withdrawal of its letter of intent to join the Open Government Partnership. As explained by John Wonderlich, policy director at the Sunlight Foundation:

While Russia’s initial commitment to OGP was likely a surprising boon for internal champions of reform, its withdrawal will also serve as a demonstration of the difficulty of making a political commitment to openness there.

Which just goes to show that, while a democratic government does not guarantee open government practices, a government that regularly violates democratic principles may be an impossible environment for implementing open government.
A cursory analysis of the ever-evolving international open data landscape reveals three major takeaways:

  1. Good intentions for government transparency in democratic countries are not always effectively realized.
  2. Politicians will gladly pay lip-service to the idea of open government without backing up words with actions.
  3. The transparency we’ve established can go away quickly without vigilant oversight and enforcement.”

What happened to the idea of the Great Society?

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John Micklethwait and Adrian Wooldridge in the Financial Times: “Most of the interesting experiments in government are taking place far from Washington: in Singapore, which delivers much better public services at a fraction of the cost; in Brazil, with its “conditional” welfare payments, dependent on behaviour; in Scandinavia, where “socialist” Sweden has cut state spending from 67 per cent of GDP in 1993 to 49 per cent, introduced school vouchers and brought entitlements into balance by raising the retirement age. In the US, the dynamic bits of government are in its cities, where pragmatic mayors are experimenting with technology.
What will replace the Great Society? For Republicans, the answer looks easy: just shrink government. But this gut instinct runs up against two big problems. The assumption that government is evil means they never take it seriously (Singapore has a tiny state but pays its best civil servants $2m a year). And, in practice, American conservatives are addicted to Big Government: hence the $1.3tn of exemptions in the US tax code, most of which are in effect a welfare state for the rich.
For Democrats, the problem is even worse. Having become used to promising ever more entitlements to voters, they face a series of unedifying choices: whether to serve society at large (by making schools better) or to protect public sector unions (teachers account for many of their activists); and whether to offer ever less generous universal benefits to the entire population or to target spending on the disadvantaged.
This is where the politics of the future will be fought, on both sides of the Atlantic. It will not be as inspiring as the Great Society. It will be about slimming and modernising government, tying pensions to life expectancy and unleashing technology on the public sector.
But what the US – and Europe – needs is cool-headed pragmatism. Government is neither a monster nor a saviour but an indispensable part of a decent society that, like most organisations, works best when it focuses on doing a few things well.”

The Collective Intelligence Handbook: an open experiment

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Michael Bernstein: “Is there really a wisdom of the crowd? How do we get at it and understand it, utilize it, empower it?
You probably have some ideas about this. I certainly do. But I represent just one perspective. What would an economist say? A biologist? A cognitive or social psychologist? An artificial intelligence or human-computer interaction researcher? A communications scholar?
For the last two years, Tom Malone (MIT Sloan) and I (Stanford CS) have worked to bring together all these perspectives into one book. We are nearing completion, and the Collective Intelligence Handbook will be published by the MIT Press later this year. I’m still relatively dumbfounded by the rockstar lineup we have managed to convince to join up.

It’s live.

Today we went live with the authors’ current drafts of the chapters. All the current preprints are here: http://cci.mit.edu/CIchapterlinks.html

And now is when you come in.

But we’re not done. We’d love for you — the crowd — to help us make this book better. We envisioned this as an open process, and we’re excited that all the chapters are now at a point where we’re ready for critique, feedback, and your contributions.
There are two ways you can help:

  • Read the current drafts and leave comments inline in the Google Docs to help us make them better.
  • Drop suggestions in the separate recommended reading list for each chapter. We (the editors) will be using that material to help us write an introduction to each chapter.

We have one month. The authors’ final chapters are due to us in mid-June. So off we go!”

Here’s what’s in the book:

Chapter 1. Introduction
Thomas W. Malone (MIT) and Michael S. Bernstein (Stanford University)
What is collective intelligence, anyway?
Chapter 2. Human-Computer Interaction and Collective Intelligence
Jeffrey P. Bigham (Carnegie Mellon University), Michael S. Bernstein (Stanford University), and Eytan Adar (University of Michigan)
How computation can help gather groups of people to tackle tough problems together.
Chapter 3. Artificial Intelligence and Collective Intelligence
Daniel S. Weld (University of Washington), Mausam (IIT Delhi), Christopher H. Lin (University of Washington), and Jonathan Bragg (University of Washington)
Mixing machine intelligence with human intelligence could enable a synthesized intelligent actor that brings together the best of both worlds.
Chapter 4. Collective Behavior in Animals: An Ecological Perspective
Deborah M. Gordon (Stanford University)
How do groups of animals work together in distributed ways to solve difficult problems?
Chapter 5. The Wisdom of Crowds vs. the Madness of Mobs
Andrew W. Lo (MIT)
Economics has studied a collectively intelligent forum — the market — for a long time. But are we as smart as we think we are?
Chapter 6. Collective Intelligence in Teams and Organizations
Anita Williams Woolley (Carnegie Mellon University), Ishani Aggarwal (Georgia Tech), Thomas W. Malone (MIT)
How do the interactions between groups of people impact how intelligently that group acts?
Chapter 7. Cognition and Collective Intelligence
Mark Steyvers (University of California, Irvine), Brent Miller (University of California, Irvine)
Understanding the conditions under which people are smart individually can help us predict when they might be smart collectively.

Chapter 8. Peer Production: A Modality of Collective Intelligence
Yochai Benkler (Harvard University), Aaron Shaw (Northwestern University), Benjamin Mako Hill (University of Washington)
What have collective efforts such as Wikipedia taught us about how large groups come together to create knowledge and creative artifacts?

The rise of open data driven businesses in emerging markets

Curated on Posted on by Stefaan Verhulst

Alla Morrison at the Worldbank blog:

Key findings —

  • Many new data companies have emerged around the world in the last few years. Of these companies, the majority use some form of government data.
  • There are a large number of data companies in sectors with high social impact and tremendous development opportunities.
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia. The most desired type of financing is equity, followed by quasi-equity in the amounts ranging from $100,000 to $5 million, with averages of between $2 and $3 million depending on the region. The total estimated need for financing may exceed $400 million.

“The economic value of open data is no longer a hypothesis
How can one make money with open data which is akin to air – free and open to everyone? Should the World Bank Group be in the catalyzer role for a sector that is just emerging?  And if so, what set of interventions would be the most effective? Can promoting open data-driven businesses contribute to the World Bank Group’s twin goals of fighting poverty and boosting shared prosperity?
These questions have been top of the mind since the World Bank Open Finances team convened a group of open data entrepreneurs from across Latin America to share their business models, success stories and challenges at the Open Data Business Models workshop in Uruguay in June 2013. We were in Uruguay to find out whether open data could lead to the creation of sustainable new businesses and jobs. To do so, we tested a couple of hypotheses: open data has economic value, beyond the benefits of increased transparency and accountability; and open data companies with sustainable business models already exist in emerging economies.
Encouraged by our findings in Uruguay we set out to further explore the economic development potential of open data, with a focus on:

  • Contribution of open data to countries’ GDP;
  • Innovative solutions to tackle social problems in key sectors like agriculture, health, education, transportation, climate change, financial services, especially those benefiting low income populations;
  • Economic benefits of governments’ buy-in into the commercial value of open data and resulting release of new datasets, which in turn would lead to increased transparency in public resource management (reductions in misallocations, a more level playing field in procurement) and better service delivery; and
  • Creation of data-related private sector jobs, especially suited for the tech savvy young generation.

We proposed a joint IFC/World Bank approach (From open data to development impact – the crucial role of private sector) that envisages providing financing to data-driven companies through a dedicated investment fund, as well as loans and grants to governments to create a favorable enabling environment. The concept was received enthusiastically for the most part by a wide group of peers at the Bank, the IFC, as well as NGOs, foundations, DFIs and private sector investors.
Thanks also in part to a McKinsey report last fall stating that open data could help unlock more than $3 trillion in value every year, the potential value of open data is now better understood. The acquisition of Climate Corporation (whose business model holds enormous potential for agriculture and food security, if governments open up the right data) for close to a billion dollars last November and the findings of the Open Data 500 project led by GovLab of the NYU further substantiated the hypothesis. These days no one asks whether open data has economic value; the focus has shifted to finding ways for companies, both startups and large corporations, and governments to unlock it. The first question though is – is it still too early to plan a significant intervention to spur open data driven economic growth in emerging markets?”

#BringBackOurGirls: Can Hashtag Activism Spur Social Change?

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Nancy Ngo at TechChange: “In our modern times of media cycles fighting for our short attention spans, it is easy to ride the momentum of a highly visible campaign that can quickly fizzle out once another competing story emerges. Since the kidnappings of approximately 300 Nigerian girls by militant Islamist group Boko Haram last month, the international community has embraced the hashtag, “#BringBackOurGirls”, in a very vocal and visible social media campaign demanding action to rescue the Chibok girls. But one month since the mass kidnapping without the rescue of the girls, do we need to take a different approach? Will #BringBackOurGirls be just another campaign we forget about once the next celebrity scandal becomes breaking news?

#BringBackOurGirls goes global starting in Nigeria

Most of the #BringBackOurGirls campaign activity has been highly visible on Twitter, Facebook, and international media outlets. In this fascinating Twitter heat map created using the tool, CartoDB, featured in TIME Magazine, we can see a time-lapsed digital map of how the hashtag, “#BringBackOurGirls” spread globally, starting organically from within Nigeria in mid April.

The #BringBackOurGirls hashtag has been embraced widely by many public figures and has garnered wide support across the world. Michelle Obama, David Cameron, and Malala Yusafzai have posted images with the hashtag, along with celebrities such as Ellen Degeneres, Angelina Jolie, and Dwayne Johnson. To date, nearly 1 million people signed the Change.org petition. Countries including the USA, UK, China, Israel have pledged to join the rescue efforts, and other human rights campaigns have joined the #BringBackOurGirls Twitter momentum, as seen on this Hashtagify map.

Is #BringBackOurGirls repeating the mistakes of #KONY2012?

Kony_2012_Poster_3

A great example of a past campaign where this happened was with the KONY2012 campaign, which brought some albeit short-lived urgency to addressing the child soldiers recruited by Joseph Kony, leader of the Lord’s Resistance Army (LRA). Michael Poffenberger, who worked on that campaign, will join us a guest expert in TC110: Social Media for Social Change online course in June 2013 and compare it the current #BringBackOurGirls campaign. Many have drawn parallels to both campaigns and warned of the false optimism that hyped social media messages can bring when context is not fully considered and understood.

According to Lauren Wolfe of Foreign Policy magazine, “Understanding what has happened to the Nigerian girls and how to rescue them means beginning to face what has happened to hundreds of thousands, if not millions, of girls over years in global armed conflict.” To some critics, this hashtag trivializes the weaknesses of Nigerian democracy that have been exposed. Critics of using social media in advocacy campaigns have used the term “slacktivism” to describe the passive, minimal effort needed to participate in these movements. Others have cited such media waves being exploited for individual gain, as opposed to genuinely benefiting the girls. Florida State University Political Science professor, Will H. Moore, argues that this hashtag activism is not only hurting the larger cause of rescuing the kidnapped girls, but actually helping Boko Haram. Jumoke Balogun, Co-Founder of CompareAfrique, also highlights the limits of the #BringBackOurGirls hashtag impact.

Hashtag activism, alone, is not enough

With all this social media activity and international press, what actual progress has been made in rescuing the kidnapped girls? If the objective is raising awareness of the issue, yes, the hashtag has been successful. If the objective is to rescue the girls, we still have a long way to go, even if the hashtag campaign has been part of a multi-pronged approach to galvanize resources into action.

The bottom line: social media can be a powerful tool to bring visibility and awareness to a cause, but a hashtag alone is not enough to bring about social change. There are a myriad of resources that must be coordinated to effectively implement this rescue mission, which will only become more difficult as more time passes. However, prioritizing and shining a sustained light on the problem, instead getting distracted by competing media cycles on celebrities getting into petty fights, is the first step toward a solution…”

Sharing in a Changing Climate

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Helen Goulden in the Huffington Post: “Every month, a social research agency conducts a public opinion survey on 30,000 UK households. As part of this households are asked about what issues they think are the most important; things such as crime, unemployment, inequality, public health etc. Climate change has ranked so consistently low on these surveys that they don’t both asking any more.
On first glance, it would appear that most people don’t care about a changing climate.
Yet, that’s simply not true. Many people care deeply, but fleetingly – in the same way they may consider their own mortality before getting back to thinking about what to have for tea. And others care, but fail to change their behaviour in a way that’s proportionate to their concerns. Certainly that’s my unhappy stomping ground.
Besides what choices do we really have? Even the most progressive, large organisations have been glacial to move towards any form of real form of sustainability. For many years we have struggled with the Frankenstein-like task of stitching ‘sustainability’ onto existing business and economic models and the results, I think, speak for themselves.
That the Collaborative Economy presents us with an opportunity – in Napster-like ways – to disrupt and evolve toward something more sustainable is compelling idea. Looking out to a future filled with opportunities to reconfigure how we produce, consume and dispose of the things we want and need to live, work and play.
Whether the journey toward sustainability is short or long, it will be punctuated with a good degree of turbulence, disruption and some largely unpredictable events. How we deal with those events and what role communities, collaboration and technology play may set the framework and tone for how that future evolves. Crises and disruption to our entrenched living patterns present ripe opportunities for innovation and space for adopting new behaviours and practices.
No-one is immune from the impact of erratic and extreme weather events. And if we accept that these events are going to increase in frequency, we must draw the conclusion that emergency state and government resources may be drawn more thinly over time.
Across the world, there is a fairly well organised state and international infrastructure for dealing with emergencies , involving everyone from the Disaster Emergency Committee, the UN, central and local government and municipalities, not for profit organisations and of course, the military. There is a clear reason why we need this kind of state emergency response; I’m not suggesting that we don’t.
But through the rise of open data and mass participation in platforms that share location, identity and inventory, we are creating a new kind of mesh; a social and technological infrastructure that could considerably strengthen our ability to respond to unpredictable events.
In the last few years we have seen a sharp rise in the number of tools and crowdsourcing platforms and open source sensor networks that are focused on observing, predicting or responding to extreme events:
• Apps like Shake Alert, which emits a minute warning that an earthquake is coming
• Rio’s sensor network, which measures rainfall outside the city and can predict flooding
• Open Source sensor software Arduino which is being used to crowd-source weather and pollution data
• Propeller Health, which is using Asthma sensors on inhalers to crowd-source pollution hotspots
• Safecast, which was developed for crowdsourcing radiation levels in Japan
Increasingly we have the ability to deploy open source, distributed and networked sensors and devices for capturing and aggregating data that can help us manage our responses to extreme weather (and indeed, other kinds of) events.
Look at platforms like LocalMind and Foursquare. Today, I might be using them to find out whether there’s a free table at a bar or finding out what restaurant my friends are in. But these kind of social locative platforms present an infrastructure that could be life-saving in any kind of situation where you need to know where to go quickly to get out of trouble. We know that in the wake of disruptive events and disasters, like bombings, riots etc, people now intuitively and instinctively take to technology to find out what’s happening, where to go and how to co-ordinate response efforts.
During the 2013 Bart Strike in San Francisco, ventures like Liquid Space and SideCar enabled people to quickly find alternative places to work, or alternatives to public transport, to mitigate the inconvenience of the strike. The strike was a minor inconvenience compared to the impact of a hurricane and flood but nevertheless, in both those instances, ventures decided waive their fees; as did AirBnB when 1,400 New York AirBnB hosts opened their doors to people who had been left homeless through Hurricane Sandy in 2012.
The impulse to help is not new. The matching of people’s offers of help and resources to on-the-ground need, in real time, is.”

The Surprising Accuracy Of Crowdsourced Predictions About The Future

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Adele Peters in FastCo-Exist: “If you have a question about what’s going to happen next in Syria or North Korea, you might get more accurate predictions by asking a group of ordinary people than from foreign policy experts or even, possibly, CIA agents with classified information. Over the last few years, the Good Judgment Project has proven that crowdsourcing predictions is a surprisingly accurate way to forecast the future.

The project, sponsored by the U.S. Director of National Intelligence office, is currently working with 3,000 people to test their ability to predict outcomes in everything from world politics to the economy. They aren’t experts, just people who are interested in the news.

“We just needed lots of people; we had very few restrictions,” says Don Moore, an associate professor at University of California-Berkeley, who co-led the project. “We wanted people who were interested, and curious, who were moderately well-educated and at least aware enough of the world around them that they listened to the news.”
The group has tackled 250 questions in the experiment so far. None of them have been simple; current questions include whether Turkey will get a new constitution and whether the U.S. and the E.U. will reach a trade deal. But the group consistently got answers right more often than individual experts, just through some simple online research and, in some cases, discussions with each other.
The crowdsourced predictions are even reportedly more accurate than those from intelligence agents. One report says that when “superpredictors,” the people who are right most often, are grouped together in teams, they can outperform agents with classified information by as much as 30%. (The researchers can’t confirm this fact, since the accuracy of spies is, unsurprisingly, classified).
…Crowdsourcing could be useful for any type of prediction, Moore says, not only what’s happening in world politics. “Every major decision depends on a forecast of the future,” he explains. “A company deciding to launch a new product has to figure out what sales might be like. A candidate trying to decide whether to run for office has to forecast how they’ll do in the election. In trying to decide whom to marry, you have to decide what your future looks like together.”
“The way corporations do forecasting now is an embarrassment,” he adds. “Many of the tools we’re developing would be enormously helpful.”
The project is currently recruiting new citizen predictors here.”