New paper by Marthews, Alex and Tucker, Catherine: “This paper uses data from Google Trends on search terms from before and after the surveillance revelations of June 2013 to analyze whether Google users’ search behavior shifted as a result of an exogenous shock in information about how closely their internet searches were being monitored by the U. S. government. We use data from Google Trends on search volume for 282 search terms across eleven different countries. These search terms were independently rated for their degree of privacy-sensitivity along multiple dimensions. Using panel data, our result suggest that cross-nationally, users were less likely to search using search terms that they believed might get them in trouble with the U. S. government. In the U. S., this was the main subset of search terms that were affected. However, internationally there was also a drop in traffic for search terms that were rated as personally sensitive. These results have implications for policy makers in terms of understanding the actual effects on search behavior of disclosures relating to the scale of government surveillance on the Internet and their potential effects on international competitiveness.“
Charities Try New Ways to Test Ideas Quickly and Polish Them Later
Ben Gose in the Chronicle of Philanthropy: “A year ago, a division of TechSoup Global began working on an app to allow donors to buy a hotel room for victims of domestic violence when no other shelter is available. Now that app is a finalist in a competition run by a foundation that combats human trafficking—and a win could mean a grant worth several hundred thousand dollars. The app’s evolution—adding a focus on sex slaves to the initial emphasis on domestic violence—was hardly accidental.
Caravan Studios, the TechSoup division that created the app, has embraced a new management approach popular in Silicon Valley known as “lean start-up.”
The principles, which are increasingly popular among nonprofits, emphasize experimentation over long-term planning and urge groups to get products and services out to clients as early as possible so the organizations can learn from feedback and make changes.
When the app, known as SafeNight, was still early in the design phase, Caravan posted details about the project on its website, including applications for grants that Caravan had not yet received. In lean-start-up lingo, Caravan put out a “minimal viable product” and hoped for feedback that would lead to a better app.
Caravan soon heard from antitrafficking organizations, which were interested in the same kind of service. Caravan eventually teamed up with the Polaris Project and the State of New Jersey, which were working on a similar app, to jointly create an app for the final round of the antitrafficking contest. Humanity United, the foundation sponsoring the contest, plans to award $1.8-million to as many as three winners later this month.
Marnie Webb, CEO of Caravan, which is building an array of apps designed to curb social problems, says lean-start-up principles help Caravan work faster and meet real needs.
“The central idea is that any product that we develop will get better if it lives as much of its life as possible outside of our office,” Ms. Webb says. “If we had kept SafeNight inside and polished it and polished it, it would have been super hard to bring on a partner because we would have invested too much.”….
Nonprofits developing new tech tools are among the biggest users of lean-start-up ideas.
Upwell, an ocean-conservation organization founded in 2011, scans the web for lively ocean-related discussions and then pushes to turn them into full-fledged movements through social-media campaigns.
Lean principles urge groups to steer clear of “vanity metrics,” such as site visits, that may sound impressive but don’t reveal much. Upwell tracks only one number—“social mentions”—the much smaller group of people who actually say something about an issue online.
After identifying a hot topic, Upwell tries to assemble a social-media strategy within 24 hours—what it calls a “minimum viable campaign.”
“We do the least amount of work to get something out the door that will get results and information,” says Rachel Dearborn, Upwell’s campaign director.
Campaigns that don’t catch on are quickly scrapped. But campaigns that do catch on get more time, energy, and money from Upwell.
After Hurricane Sandy, in 2012, a prominent writer on ocean issues and others began pushing the idea that revitalizing the oyster beds near New York City could help protect the shore from future storm surges. Upwell’s “I (Oyster) New York” campaign featured a catchy logo and led to an even bigger spike in attention.
‘Build-Measure-Learn’
Some organizations that could hardly be called start-ups are also using lean principles. GuideStar, the 20-year-old aggregator of financial information about charities, is using the lean approach to develop tools more quickly that meet the needs of its users.
The lean process promotes short “build-measure-learn” cycles, in which a group frequently updates a product or service based on what it hears from its customers.
GuideStar and the Nonprofit Finance Fund have developed a tool called Financial Scan that allows charities to see how they compare with similar groups on various financial measures, such as their mix of earned revenue and grant funds.
When it analyzed who was using the tool, GuideStar found heavy interest from both foundations and accounting firms, says Evan Paul, GuideStar’s senior director of products and marketing.
In the future, he says, GuideStar may create three versions of Financial Scan to meet the distinct interests of charities, foundations, and accountants.
“We want to get more specific about how people are using our data to make decisions so that we can help make those decisions better and faster,” Mr. Paul says….
Lean Start-Up: a Glossary of Terms for a Hot New Management Approach
Build-Measure-Learn
Instead of spending considerable time developing a product or service for a big rollout, organizations should consider using a continuous feedback loop: “build” a program or service, even if it is not fully fleshed out; “measure” how clients are affected; and “learn” by improving the program or going in a new direction. Repeat the cycle.
Minimum Viable Product
An early version of a product or service that may be lacking some features. This approach allows an organization to obtain feedback from clients and quickly determine the usefulness of a product or service and how to improve it.
Get Out of the Building
To determine whether a product or service is needed, talk to clients and share your ideas with them before investing heavily.
A/B Testing
Create two versions of a product or service, show them to different groups, and see which performs best.
Failing Fast
By quickly realizing that a product or service isn’t viable, organizations save time and money and gain valuable information for their next effort.
Pivot
Making a significant change in strategy when the early testing of a minimum viable product shows that the product or service isn’t working or isn’t needed.
Vanity Metrics
Measures that seem to provide a favorable picture but don’t accurately capture the impact of a product. An example might be a tally of website page views. A more meaningful measure—or an “actionable metric,” in the lean lexicon—might be the number of active users of an online service.
Sources: The Lean Startup, by Eric Ries; The Ultimate Dictionary of Lean for Social Good, a publication by Lean Impact”
Behavioural economics and public policy
Tim Harford in the Financial Times: “The past decade has been a triumph for behavioural economics, the fashionable cross-breed of psychology and economics. First there was the award in 2002 of the Nobel Memorial Prize in economics to a psychologist, Daniel Kahneman – the man who did as much as anything to create the field of behavioural economics. Bestselling books were launched, most notably by Kahneman himself (Thinking, Fast and Slow , 2011) and by his friend Richard Thaler, co-author of Nudge (2008). Behavioural economics seems far sexier than the ordinary sort, too: when last year’s Nobel was shared three ways, it was the behavioural economist Robert Shiller who grabbed all the headlines.
Behavioural economics is one of the hottest ideas in public policy. The UK government’s Behavioural Insights Team (BIT) uses the discipline to craft better policies, and in February was part-privatised with a mission to advise governments around the world. The White House announced its own behavioural insights team last summer.
So popular is the field that behavioural economics is now often misapplied as a catch-all term to refer to almost anything that’s cool in popular social science, from the storycraft of Malcolm Gladwell, author of The Tipping Point (2000), to the empirical investigations of Steven Levitt, co-author of Freakonomics (2005).
Yet, as with any success story, the backlash has begun. Critics argue that the field is overhyped, trivial, unreliable, a smokescreen for bad policy, an intellectual dead-end – or possibly all of the above. Is behavioural economics doomed to reflect the limitations of its intellectual parents, psychology and economics? Or can it build on their strengths and offer a powerful set of tools for policy makers and academics alike?…”
The Unwisdom of Crowds
Anne Applebaum on why people-powered revolutions are overrated in the New Republic: “..Yet a successful street revolution, like any revolution, is never guaranteed to leave anything positive in its aftermath—or anything at all. In the West, we often now associate protests with progress, or at least we assume that big crowds—the March on Washington, Paris in 1968—are the benign face of social change. But street revolutions are not always progressive, positive, or even important. Some replace a corrupt tyranny with violence and a political vacuum, which is what happened in Libya. Ukraine’s own Orange Revolution of 2004–2005 produced a new group of leaders who turned out to be just as incompetent as their predecessors. Crowds can be bullying, they can become violent, and they can give rise to extremists: Think Tehran 1979, or indeed Petrograd 1917.
The crowd may not even represent the majority. Because a street revolution makes good copy, and because it provides great photographs, we often mistakenly confuse “people power” with democracy itself. In fact, the creation of democratic institutions—courts, legal systems, bills of rights—is a long and tedious process that often doesn’t interest foreign journalists at all. Tunisia’s ratification of a new constitution earlier this year represented the most significant achievement of the Arab Spring to date, but the agonizing negotiations that led up to that moment were hard for outsiders to understand—and not remotely telegenic
Equally, it is a dangerous mistake to imagine that “people power” can ever be a substitute for actual elections. On television, a demonstration can loom larger than it should. In both Thailand and Turkey, an educated middle class has recently taken to the streets to protest against democratically elected leaders who have grown increasingly corrupt and autocratic, but who might well be voted back into office tomorrow. In Venezuela, elections are not fair and the media is not free, but the president is supported by many Venezuelans who still have faith in his far-left rhetoric, however much his policies may be damaging the country. Demonstrations might help bring change in some of these countries, but if the change is to be legitimate—and permanent—the electorate will eventually have to endorse it.
As we often forget, some of the most successful transitions to democracy did not involve crowds at all. Chile became a democracy because its dictator, Augusto Pinochet, decided it would become one. In early 1989, well before mass demonstrations in Prague or Berlin, the leaders of the Polish opposition sat down at a large round table with their former jailers and negotiated their way out of communism. There are no spectacular photographs of these transitions, and many people found them unsatisfying, even unjust. But Chile and Poland remain democracies today, not least because their new leaders came to power without any overt opposition from the old regime.
It would be nice if these kinds of transitions were more common, but not every dictator is willing to smooth the path toward change. For that reason, the post-revolutionary moment is often more important than the revolution itself, for this is when the emotion of the mob has to be channeled rapidly—immediately—into legitimate institutions. Not everybody finds this easy. In the wake of the Egyptian revolution, demonstrators found it difficult to abandon Tahrir Square. “We won’t leave because we have to make sure this country is set on the right path,” one protester said at the time. In fact, he should already have been at home, back in his neighborhood, perhaps creating the grassroots political party that might have given Egyptians a real alternative to the Muslim Brotherhood…”
Statistics and Open Data: Harvesting unused knowledge, empowering citizens and improving public services
House of Commons Public Administration Committee (Tenth Report):
“1. Open data is playing an increasingly important role in Government and society. It is data that is accessible to all, free of restrictions on use or redistribution and also digital and machine-readable so that it can be combined with other data, and thereby made more useful. This report looks at how the vast amounts of data generated by central and local Government can be used in open ways to improve accountability, make Government work better and strengthen the economy.
2. In this inquiry, we examined progress against a series of major government policy announcements on open data in recent years, and considered the prospects for further development. We heard of government open data initiatives going back some years, including the decision in 2009 to release some Ordnance Survey (OS) data as open data, and the Public Sector Mapping Agreement (PSMA) which makes OS data available for free to the public sector. The 2012 Open Data White Paper ‘Unleashing the Potential’ says that transparency through open data is “at the heart” of the Government’s agenda and that opening up would “foster innovation and reform public services”. In 2013 the report of the independently-chaired review by Stephan Shakespeare, Chief Executive of the market research and polling company YouGov, of the use, re-use, funding and regulation of Public Sector Information urged Government to move fast to make use of data. He criticised traditional public service attitudes to data before setting out his vision:
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- To paraphrase the great retailer Sir Terry Leahy, to run an enterprise without data is like driving by night with no headlights. And yet that is what Government often does. It has a strong institutional tendency to proceed by hunch, or prejudice, or by the easy option. So the new world of data is good for government, good for business, and above all good for citizens. Imagine if we could combine all the data we produce on education and health, tax and spending, work and productivity, and use that to enhance the myriad decisions which define our future; well, we can, right now. And Britain can be first to make it happen for real.
3. This was followed by publication in October 2013 of a National Action Plan which sets out the Government’s view of the economic potential of open data as well as its aspirations for greater transparency.
4. This inquiry is part of our wider programme of work on statistics and their use in Government. A full description of the studies is set out under the heading “Statistics” in the inquiries section of our website, which can be found at www.parliament.uk/pasc. For this inquiry we received 30 pieces of written evidence and took oral evidence from 12 witnesses. We are grateful to all those who have provided evidence and to our Specialist Adviser on statistics, Simon Briscoe, for his assistance with this inquiry.”
Table of Contents:
Summary
1 Introduction
2 Improving accountability through open data
3 Open Data and Economic Growth
4 Improving Government through open data
5 Moving faster to make a reality of open data
6 A strategic approach to open data?
Conclusion
Conclusions and recommendations
How Twitter Could Help Police Departments Predict Crime
Eric Jaffe in Atlantic Cities: “Initially, Matthew Gerber didn’t believe Twitter could help predict where crimes might occur. For one thing, Twitter’s 140-character limit leads to slang and abbreviations and neologisms that are hard to analyze from a linguistic perspective. Beyond that, while criminals occasionally taunt law enforcement via Twitter, few are dumb or bold enough to tweet their plans ahead of time. “My hypothesis was there was nothing there,” says Gerber.
But then, that’s why you run the data. Gerber, a systems engineer at the University of Virginia’s Predictive Technology Lab, did indeed find something there. He reports in a new research paper that public Twitter data improved the predictions for 19 of 25 crimes that occurred early last year in metropolitan Chicago, compared with predictions based on historical crime patterns alone. Predictions for stalking, criminal damage, and gambling saw the biggest bump…..
Of course, the method says nothing about why Twitter data improved the predictions. Gerber speculates that people are tweeting about plans that correlate highly with illegal activity, as opposed to tweeting about crimes themselves.
Let’s use criminal damage as an example. The algorithm identified 700 Twitter topics related to criminal damage; of these, one topic involved the words “united center blackhawks bulls” and so on. Gather enough sports fans with similar tweets and some are bound to get drunk enough to damage public property after the game. Again this scenario extrapolates far more than the data tells, but it offers a possible window into the algorithm’s predictive power.
The map on the left shows predicted crime threat based on historical patterns; the one on the right includes Twitter data. (Via Decision Support Systems)
From a logistical standpoint, it wouldn’t be too difficult for police departments to use this method in their own predictions; both the Twitter data and modeling software Gerber used are freely available. The big question, he says, is whether a department used the same historical crime “hot spot” data as a baseline for comparison. If not, a new round of tests would have to be done to show that the addition of Twitter data still offered a predictive upgrade.
There’s also the matter of public acceptance. Data-driven crime prediction tends to raise any number of civil rights concerns. In 2012, privacy advocates criticized the FBI for a similar plan to use Twitter for crime predictions. In recent months the Chicago Police Department’s own methods have been knocked as a high-tech means of racial profiling. Gerber says his algorithms don’t target any individuals and only cull data posted voluntarily to a public account.”
Building a More Open Government
Corinna Zarek at the White House: “It’s Sunshine Week again—a chance to celebrate transparency and participation in government and freedom of information. Every year in mid-March, we take stock of our progress and where we are headed to make our government more open for the benefit of citizens.
In December, 2013, the Administration announced 23 ambitious commitments to further open up government over the next two years in U.S. Government’s second Open Government National Action Plan. Those commitments are now all underway or in development, including:
· Launching an improved Data.gov: The updated Data.gov debuted in January, 2014, and continues to grow with thousands of updated or new government data sets being proactively made available to the public.
· Increasing public collaboration: Through crowdsourcing, citizen science, and other methods, Federal agencies continue to expand the ways they collaborate with the public. For example, the National Aeronautics and Space Administration, for instance, recently launched its third Asteroid Grand Challenge, a broad call to action, seeking the best and brightest ideas from non-traditional partners to enhance and accelerate the work NASA is already doing for planetary defense.
· Improving We the People: The online petition platform We the People gives the public a direct way to participate in their government and is currently incorporating improvements to make it easier for the public to submit petitions and signatures.”
New Field Guide Explores Open Data Innovations in Disaster Risk and Resilience
In Jakarta, more than 500 community members have been trained to collect data on thousands of hospitals, schools, private buildings, and critical infrastructure. In Sri Lanka, government and academic volunteers mapped over 30,000 buildings and 450 km of roadways using a collaborative online resource called OpenStreetMaps.
These are just a few of the projects that have been catalyzed by the Open Data for Resilience Initiative (OpenDRI), developed by the World Bank’s Global Facility for Disaster Reduction and Recovery (GFDRR). Launched in 2011, OpenDRI is active in more than 20 countries today, mapping tens of thousands of buildings and urban infrastructure, providing more than 1,000 geospatial datasets to the public, and developing innovative application tools.
To expand this work, the World Bank Group has launched the OpenDRI Field Guide as a showcase of successful projects and a practical guide for governments and other organizations to shape their own open data programs….
The field guide walks readers through the steps to build open data programs based on the OpenDRI methodology. One of the first steps is data collation. Relevant datasets are often locked because of proprietary arrangements or fragmented in government bureaucracies. The field guide explores tools and methods to enable the participatory mapping projects that can fill in gaps and keep existing data relevant as cities rapidly expand.
GeoNode: Mapping Disaster Damage for Faster Recovery
One example is GeoNode, a locally controlled and open source cataloguing tool that helps manage and visualize geospatial data. The tool, already in use in two dozen countries, can be modified and easily be integrated into existing platforms, giving communities greater control over mapping information.
GeoNode was used extensively after Typhoon Yolanda (Haiyan) swept the Philippines with 300 km/hour winds and a storm surge of over six meters last fall. The storm displaced nearly 11 million people and killed more than 6,000.
An event-specific GeoNode project was created immediately and ultimately collected more than 72 layers of geospatial data, from damage assessments to situation reports. The data and quick analysis capability contributed to recovery efforts and is still operating in response mode at Yolandadata.org.
InaSAFE: Targeting Risk Reduction
A sister project, InaSAFE, is an open, easy-to-use tool for creating impact assessments for targeted risk reduction. The assessments are based on how an impact layer – such as a tsunami, flood, or earthquake – affects exposure data, such as population or buildings.
With InaSAFE, users can generate maps and statistical information that can be easily disseminated and even fed back into projects like GeoNode for simple, open source sharing.
The initiative, developed in collaboration with AusAID and the Government of Indonesia, was put to the test in the 2012 flood season in Jakarta, and its successes provoked a rapid national rollout and widespread interest from the international community.
Open Cities: Improving Urban Planning & Resilience
The Open Cities project, another program operating under the OpenDRI platform, aims to catalyze the creation, management and use of open data to produce innovative solutions for urban planning and resilience challenges across South Asia.
In 2013, Kathmandu was chosen as a pilot city, in part because the population faces the highest mortality threat from earthquakes in the world. Under the project, teams from the World Bank assembled partners and community mobilizers to help execute the largest regional community mapping project to date. The project surveyed more than 2,200 schools and 350 health facilities, along with road networks, points of interest, and digitized building footprints – representing nearly 340,000 individual data nodes.”
After the Protests
Zeynep Tufekc in the New York Times on why social media is fueling a boom-and-bust cycle of political: “LAST Wednesday, more than 100,000 people showed up in Istanbul for a funeral that turned into a mass demonstration. No formal organization made the call. The news had come from Twitter: Berkin Elvan, 15, had died. He had been hit in the head by a tear-gas canister on his way to buy bread during the Gezi protests last June. During the 269 days he spent in a coma, Berkin’s face had become a symbol of civic resistance shared on social media from Facebook to Instagram, and the response, when his family tweeted “we lost our son” and then a funeral date, was spontaneous.
Protests like this one, fueled by social media and erupting into spectacular mass events, look like powerful statements of opposition against a regime. And whether these take place in Turkey, Egypt or Ukraine, pundits often speculate that the days of a ruling party or government, or at least its unpopular policies, must be numbered. Yet often these huge mobilizations of citizens inexplicably wither away without the impact on policy you might expect from their scale.
This muted effect is not because social media isn’t good at what it does, but, in a way, because it’s very good at what it does. Digital tools make it much easier to build up movements quickly, and they greatly lower coordination costs. This seems like a good thing at first, but it often results in an unanticipated weakness: Before the Internet, the tedious work of organizing that was required to circumvent censorship or to organize a protest also helped build infrastructure for decision making and strategies for sustaining momentum. Now movements can rush past that step, often to their own detriment….
But after all that, in the approaching local elections, the ruling party is expected to retain its dominance.
Compare this with what it took to produce and distribute pamphlets announcing the Montgomery bus boycott in 1955. Jo Ann Robinson, a professor at Alabama State College, and a few students sneaked into the duplicating room and worked all night to secretly mimeograph 52,000 leaflets to be distributed by hand with the help of 68 African-American political, religious, educational and labor organizations throughout the city. Even mundane tasks like coordinating car pools (in an era before there were spreadsheets) required endless hours of collaborative work.
By the time the United States government was faced with the March on Washington in 1963, the protest amounted to not just 300,000 demonstrators but the committed partnerships and logistics required to get them all there — and to sustain a movement for years against brutally enforced Jim Crow laws. That movement had the capacity to leverage boycotts, strikes and demonstrations to push its cause forward. Recent marches on Washington of similar sizes, including the 50th anniversary march last year, also signaled discontent and a desire for change, but just didn’t pose the same threat to the powers that be.
Social media can provide a huge advantage in assembling the strength in numbers that movements depend on. Those “likes” on Facebook, derided as slacktivism or clicktivism, can have long-term consequences by defining which sentiments are “normal” or “obvious” — perhaps among the most important levers of change. That’s one reason the same-sex marriage movement, which uses online and offline visibility as a key strategy, has been so successful, and it’s also why authoritarian governments try to ban social media.
During the Gezi protests, Prime Minister Recep Tayyip Erdogan called Twitter and other social media a “menace to society.” More recently, Turkey’s Parliament passed a law greatly increasing the government’s ability to censor online content and expand surveillance, and Mr. Erdogan said he would consider blocking access to Facebook and YouTube. It’s also telling that one of the first moves by President Vladimir V. Putin of Russia before annexing Crimea was to shut down the websites of dissidents in Russia.
Media in the hands of citizens can rattle regimes. It makes it much harder for rulers to maintain legitimacy by controlling the public sphere. But activists, who have made such effective use of technology to rally supporters, still need to figure out how to convert that energy into greater impact. The point isn’t just to challenge power; it’s to change it.”
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….”