Politics or technology – which will save the world?


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?


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?


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 Weird, Wild World of Citizen Science Is Already Here


David Lang in Wired: “Up and down the west coast of North America, countless numbers of starfish are dying. The affliction, known as Sea Star Wasting Syndrome, is already being called the biggest die-off of sea stars in recorded history, and we’re still in the dark as to what’s causing it or what it means. It remains an unsolved scientific mystery. The situation is also shaping up as a case study of an unsung scientific opportunity: the rise of citizen science and exploration.
The sea star condition was first noticed by Laura James, a diver and underwater videographer based in Seattle. As they began washing up on the shore near her home with lesions and missing limbs, she became concerned and notified scientists. Similar sightings started cropping up all along the West Coast, with gruesome descriptions of sea stars that were disintegrating in a matter of days, and populations that had been decimated. As scientists race to understand what’s happening, they’ve enlisted the help of amateurs like James, to move faster. Pete Raimondi’s lab at UC Santa Cruz has created the Sea Star Wasting Map, the baseline for monitoring the issue, to capture the diverse set of contributors and collaborators.
The map is one of many new models of citizen-powered science–a blend of amateurs and professionals, looking and learning together–that are beginning to emerge. Just this week, NASA endorsed a group of amateur astronomers to attempt to rescue a vintage U.S. spacecraft. NASA doesn’t have the money to do it, and this passionate group of citizen scientists can handle it.
Unfortunately, the term “citizen science” is terrible. It’s vague enough to be confusing, yet specific enough to seem exclusive. It’s too bad, too, because the idea of citizen science is thrilling. I love the notion that I can participate in the expanding pool of human knowledge and understanding, even though the extent of my formal science education is a high school biology class. To me, it seemed a genuine invitation to be curious. A safe haven for beginners. A license to explore.
Not everyone shares my romantic perspective, though. If you ask a university researcher, they’re likely to explain citizen science as a way for the public to contribute data points to larger, professionally run studies, like participating in the galaxy-spotting website Zooniverse or taking part in the annual Christmas Bird Count with the Audubon Society. It’s a model on the scientific fringes; using broad participation to fill the gaps in necessary data.
There’s power in this diffuse definition, though, as long as new interpretations are welcomed and encouraged. By inviting and inspiring people to ask their own questions, citizen science can become much more than a way of measuring bird populations. From the drone-wielding conservationists in South Africa to the makeshift biolabs in Brooklyn, a widening circle of participants are wearing the amateur badge with honor. And all of these groups–the makers, the scientists, the hobbyists–are converging to create a new model for discovery. In other words, the maker movement and the traditional science world are on a collision course.
To understand the intersection, it helps to know where each of those groups is coming from….”

The Golden Record 2.0 Will Crowdsource A Selfie of Human Culture


Helen Thompson in the Smithsonian: “In 1977, the Voyager 1 and 2 spacecraft left our solar system, carrying a “Golden Record”—a gold-plated phonograph record containing analogue images, greetings, and music from Earth. It was meant to be a snapshot of humanity. On the small chance that an alien lifeform encountered Voyager, they could get a sense of who made it.
“This record represents our hope and our determination and our goodwill in a vast and awesome universe,” said Carl Sagan who led the six-member team that created the Golden Record.
No spacecraft has left our solar system since Voyager, but in the next few years, NASA’s New Horizons probe, launched in 2006, will reach Pluto and then pass into the far edges of the solar system and beyond. A new project aims to create a “Golden Record 2.0”. Just like the original record, this new version will represent a sampling of human culture for NASA to transmit to New Horizons just before it soars off into the rest of the universe.
The genesis of the project came from Jon Lomberg, a scientific artist and the designer of the original Golden Record. Over the last year he’s recruited experts in a variety of fields to back the project. To convince NASA of public support, he launched a website and put together a petition, signed by over 10,000 people in 140 countries. When Lomberg presented the idea to NASA earlier this year, the agency was receptive and will be releasing a statement with further details on the project on August 25. In the meantime, he and his colleague Albert Yu-Min Lin, a research scientist at the University of California in San Diego, gave a preview of their plan at Smithsonian’s Future Is Here event in Washington, DC, today.
New Horizons will likely only have a small amount of memory space available for the content, so what should make the cut? Photos of landscapes and animals (including humans), sound bites of great speakers, popular music, or even videos could end up on the digital record. Lin is developing a platform where people will be able to explore and critique the submissions on the site. “We wanted to make this a democratic discussion,” says Lin. “How do we make this not a conversation about cute cats and Justin Beiber?” One can only guess what aliens might make of the Earth’s YouTube video fodder.
What sets this new effort apart from the original is that the content will be crowdsourced. “We thought this time why not let the people of earth speak for themselves,” says Lomberg. “Why not figure out a way to crowd source this message so that people would be able to decide what they wanted to say?” Lomberg has teamed up with Lin, who specializes in crowdsourcing technology, to create a platform where people from all over the world can submit content to be included on the record…”

Free Online Lawmaking Platform for Washington, D.C.


OpenGov Foundation: “At-Large Councilmember David Grosso and The OpenGov Foundation today launched the beta version of MadisonDC, a free online lawmaking tool that empowers citizens to engage directly with their elected officials – and the policymaking process itself – by commenting on, proposing changes to, and debating real D.C. Council legislation.  Grosso is the first-ever District elected official to give citizens the opportunity to log on and legislate, putting him at the forefront of a nation-wide movement reinventing local legislatures with technology.  Three bills are now open for crowdsourcing on MadisonDC: a plan to fully legalize marijuana, a proposal to make zoning laws more friendly to urban farmers, and legislation to create open primary elections….
MadisonDC is the District of Columbia’s version of the freeMadison software that reinvents government for the Internet Age.  Madison 1.0 powered the American people’s successful defense of Internet freedom from Congressional threats.  It delivered the first crowdsourced bill in the history of the U.S. Congress.  And now, the non-partisan, non-profit OpenGov Foundation has released Madison 2.0, empowering you to participate in your government, efficiently access your elected officials, and hold them accountable.”

How Big Data Could Undo Our Civil-Rights Laws


Virginia Eubanks in the American Prospect: “From “reverse redlining” to selling out a pregnant teenager to her parents, the advance of technology could render obsolete our landmark civil-rights and anti-discrimination laws.
Big Data will eradicate extreme world poverty by 2028, according to Bono, front man for the band U2. But it also allows unscrupulous marketers and financial institutions to prey on the poor. Big Data, collected from the neonatal monitors of premature babies, can detect subtle warning signs of infection, allowing doctors to intervene earlier and save lives. But it can also help a big-box store identify a pregnant teenager—and carelessly inform her parents by sending coupons for baby items to her home. News-mining algorithms might have been able to predict the Arab Spring. But Big Data was certainly used to spy on American Muslims when the New York City Police Department collected license plate numbers of cars parked near mosques, and aimed surveillance cameras at Arab-American community and religious institutions.
Until recently, debate about the role of metadata and algorithms in American politics focused narrowly on consumer privacy protections and Edward Snowden’s revelations about the National Security Agency (NSA). That Big Data might have disproportionate impacts on the poor, women, or racial and religious minorities was rarely raised. But, as Wade Henderson, president and CEO of the Leadership Conference on Civil and Human Rights, and Rashad Robinson, executive director of ColorOfChange, a civil rights organization that seeks to empower black Americans and their allies, point out in a commentary at TPM Cafe, while big data can change business and government for the better, “it is also supercharging the potential for discrimination.”
In his January 17 speech on signals intelligence, President Barack Obama acknowledged as much, seeking to strike a balance between defending “legitimate” intelligence gathering on American citizens and admitting that our country has a history of spying on dissidents and activists, including, famously, Dr. Martin Luther King, Jr. If this balance seems precarious, it’s because the links between historical surveillance of social movements and today’s uses of Big Data are not lost on the new generation of activists.
“Surveillance, big data and privacy have a historical legacy,” says Amalia Deloney, policy director at the Center for Media Justice, an Oakland-based organization dedicated to strengthening the communication effectiveness of grassroots racial justice groups. “In the early 1960s, in-depth, comprehensive, orchestrated, purposeful spying was used to disrupt political movements in communities of color—the Yellow Peril, the American Indian Movement, the Brown Berets, or the Black Panthers—to create fear and chaos, and to spread bias and stereotypes.”
In the era of Big Data, the danger of reviving that legacy is real, especially as metadata collection renders legal protection of civil rights and liberties less enforceable….
Big Data and surveillance are unevenly distributed. In response, a coalition of 14 progressive organizations, including the ACLU, ColorOfChange, the Leadership Conference on Civil and Human Rights, the NAACP, National Council of La Raza, and the NOW Foundation, recently released five “Civil Rights Principles for the Era of Big Data.” In their statement, they demand:

  • An end to high-tech profiling;
  • Fairness in automated decisions;
  • The preservation of constitutional principles;
  • Individual control of personal information; and
  • Protection of people from inaccurate data.

This historic coalition aims to start a national conversation about the role of big data in social and political inequality. “We’re beginning to ask the right questions,” says O’Neill. “It’s not just about what can we do with this data. How are communities of color impacted? How are women within those communities impacted? We need to fold these concerns into the national conversation.”

The Secret Science of Retweets


Emerging Technology From the arXiv: “If you send a tweet to a stranger asking them to retweet it, you probably wouldn’t be surprised if they ignored you entirely. But if you sent out lots of tweets like this, perhaps a few might end up being passed on.

How come? What makes somebody retweet information from a stranger? That’s the question addressed today by Kyumin Lee from Utah State University in Logan and a few pals from IBM’s Almaden research center in San Jose….by studying the characteristics of Twitter users, it is possible to identify strangers who are more likely to pass on your message than others. And in doing this, the researchers say they’ve been able to improve the retweet rate of messages sent strangers by up to 680 percent.
So how did they do it? The new technique is based on the idea that some people are more likely to tweet than others, particularly on certain topics and at certain times of the day. So the trick is to find these individuals and target them when they are likely to be most effective.
So the approach was straightforward. The idea is to study the individuals on Twitter, looking at their profiles and their past tweeting behavior, looking for clues that they might be more likely to retweet certain types of information. Having found these individuals, send your tweets to them.
That’s the theory. In practice, it’s a little more involved. Lee and co wanted to test people’s response to two types of information: local news (in San Francisco) and tweets about bird flu, a significant issue at the time of their research. They then created several Twitter accounts with a few followers, specifically to broadcast information of this kind.
Next, they selected people to receive their tweets. For the local news broadcasts, they searched for Twitter users geolocated in the Bay area, finding over 34,000 of them and choosing 1,900 at random.
They then a sent a single message to each user of the format:
“@ SFtargetuser “A man was killed and three others were wounded in a shooting … http://bit.ly/KOl2sC” Plz RT this safety news”
So the tweet included the user’s name, a short headline, a link to the story and a request to retweet.
Of these 1,900 people, 52 retweeted the message they received. That’s 2.8 percent.
For the bird flu information, Lee and co hunted for people who had already tweeted about bird flu, finding 13,000 of them and choosing 1,900 at random. Of these, 155 retweeted the message they received, a retweet rate of 8.4 percent.
But Lee and co found a way to significantly improve these retweet rates. They went back to the original lists of Twitter users and collected publicly available information about each of them, such as their personal profile, the number of followers, the people they followed, their 200 most recent tweets and whether they retweeted the message they had received
Next, the team used a machine learning algorithm to search for correlations in this data that might predict whether somebody was more likely to retweet. For example, they looked at whether people with older accounts were more likely to retweet or how the ratio of friends to followers influenced the retweet likelihood, or even how the types of negative or positive words they used in previous tweets showed any link. They also looked at the time of day that people were most active in tweeting.
The result was a machine learning algorithm capable of picking users who were most likely to retweet on a particular topic.
And the results show that it is surprisingly effective. When the team sent local information tweets to individuals identified by the algorithm, 13.3 percent retweeted it, compared to just 2.6 percent of people chosen at random.
And they got even better results when they timed the request to match the periods when people had been most active in the past. In that case, the retweet rate rose to 19.3 percent. That’s an improvement of over 600 percent.
Similarly, the rate for bird flu information rose from 8.3 percent for users chosen at random to 19.7 percent for users chosen by the algorithm.
That’s a significant result that marketers, politicians, news organizations will be eyeing with envy.
An interesting question is how they can make this technique more generally applicable. It raises the prospect of an app that allows anybody to enter a topic of interest and which then creates a list of people most likely to retweet on that topic in the next few hours.
Lee and co do not mention any plans of this kind. But if they don’t exploit it, then there will surely be others who will.
Ref: arxiv.org/abs/1405.3750 : Who Will Retweet This? Automatically Identifying and Engaging Strangers on Twitter to Spread Information”

The Collective Intelligence Handbook: an open experiment


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


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?”