Stefaan Verhulst

Twiplomacy: “World leaders vie for attention, connections and followers on Twitter, that’s the latest finding of Burson-Marsteller’s Twiplomacy study 2014, an annual global study looking at the use of Twitter by heads of state and government and ministers of foreign affairs.
While some heads of state and government continue to amass large followings, foreign ministers have established a virtual diplomatic network by following each other on the social media platform.
For many diplomats Twitter has becomes a powerful channel for digital diplomacy and 21^st century statecraft and not all Twitter exchanges are diplomatic, real world differences are spilling over reflected on Twitter and sometimes end up in hashtag wars.
“I am a firm believer in the power of technology and social media to communicate with people across the world,” India’s new Prime Minister Narendra Modi wrote in his inaugural message on his new website. Within weeks of his election in May 2014, the @NarendraModi account has moved into the top four most followed Twitter accounts of world leaders with close to five million followers.
More than half of the world’s foreign ministers and their institutions are active on the social networking site. Twitter has become an indispensable diplomatic networking and communication tool. As Finnish Prime Minister @AlexStubb wrote in a tweet in March 2014: “Most people who criticize Twitter are often not on it. I love this place. Best source of info. Great way to stay tuned and communicate.”
As of 25 June 2014, the vast majority (83 percent) of the 193 UN member countries have a presence on Twitter. More than two-thirds (68 percent) of all heads of state and heads of government have personal accounts on the social network.
As of 24 June 2014, the vast majority (83 percent) of the 193 UN member countries have a presence on Twitter. More than two-thirds (68 percent) of all heads of state and heads of government have personal accounts on the social network.

The White House: “With more than 14 million users and 21 million signatures, We the People, the White House’s online petition platform, has proved more popular than we ever thought possible. In the nearly three years since launch, we’ve heard from you on a huge range of topics, and issued more than 225 responses.

But we’re not stopping there. We’ve been working to make it easier to sign a petition and today we’re proud to announce the next iteration of We the People.

Since launch, we’ve heard from users who wanted a simpler, more streamlined way to sign petitions without creating an account and logging in every time. This latest update makes that a reality.

We’re calling it “simplified signing” and it takes the account creation step out of signing a petition. As of today, just enter your basic information, confirm your signature via email and you’re done. That’s it. No account to create, no logging in, no passwords to remember.

That’s great news for new users, but we’re betting it’ll be welcomed by our returning signers, too. If you signed a petition six months ago and you don’t remember your password, you don’t have to worry about resetting it. Just enter your email address, confirm your signature, and you’re done.

Go check it out right now on petitions.whitehouse.gov.“

Joel Gurin at the SAIS Review of International Affairs: “The international open data movement is beginning to have an impact on government policy, business strategy, and economic development. Roughly sixty countries in the Open Government Partnership have committed to principles that include releasing government data as open data—that is, free public data in forms that can be readily used. Hundreds of businesses are using open data to create jobs and build economic value. Up to now, however, most of this activity has taken place in developed countries, with the United States and United Kingdom in the lead. The use of open data faces more obstacles in developing countries, but has growing promise there, as well.”

The Guardian: “The Los Angeles Police Department, like many urban police forces today, is both heavily armed and thoroughly computerised. The Real-Time Analysis and Critical Response Division in downtown LA is its central processor. Rows of crime analysts and technologists sit before a wall covered in video screens stretching more than 10 metres wide. Multiple news broadcasts are playing simultaneously, and a real-time earthquake map is tracking the region’s seismic activity. Half-a-dozen security cameras are focused on the Hollywood sign, the city’s icon. In the centre of this video menagerie is an oversized satellite map showing some of the most recent arrests made across the city – a couple of burglaries, a few assaults, a shooting.

On a slightly smaller screen the division’s top official, Captain John Romero, mans the keyboard and zooms in on a comparably micro-scale section of LA. It represents just 500 feet by 500 feet. Over the past six months, this sub-block section of the city has seen three vehicle burglaries and two property burglaries – an atypical concentration. And, according to a new algorithm crunching crime numbers in LA and dozens of other cities worldwide, it’s a sign that yet more crime is likely to occur right here in this tiny pocket of the city.
The algorithm at play is performing what’s commonly referred to as predictive policing. Using years – and sometimes decades – worth of crime reports, the algorithm analyses the data to identify areas with high probabilities for certain types of crime, placing little red boxes on maps of the city that are streamed into patrol cars. “Burglars tend to be territorial, so once they find a neighbourhood where they get good stuff, they come back again and again,” Romero says. “And that assists the algorithm in placing the boxes.”
Romero likens the process to an amateur fisherman using a fish finder device to help identify where fish are in a lake. An experienced fisherman would probably know where to look simply by the fish species, time of day, and so on. “Similarly, a really good officer would be able to go out and find these boxes. This kind of makes the average guys’ ability to find the crime a little bit better.”
Predictive policing is just one tool in this new, tech-enhanced and data-fortified era of fighting and preventing crime. As the ability to collect, store and analyse data becomes cheaper and easier, law enforcement agencies all over the world are adopting techniques that harness the potential of technology to provide more and better information. But while these new tools have been welcomed by law enforcement agencies, they’re raising concerns about privacy, surveillance and how much power should be given over to computer algorithms.
P Jeffrey Brantingham is a professor of anthropology at UCLA who helped develop the predictive policing system that is now licensed to dozens of police departments under the brand name PredPol. “This is not Minority Report,” he’s quick to say, referring to the science-fiction story often associated with PredPol’s technique and proprietary algorithm. “Minority Report is about predicting who will commit a crime before they commit it. This is about predicting where and when crime is most likely to occur, not who will commit it.”…”

Yves-Alexandre de Montjoye, Arkadiusz Stopczynski, Erez Shmueli, Alex Pentland & Sune Lehmann in Nature (Scientific Reports) : “Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams’ problem solving abilities as a function of both their within-team networks and their members’ extended networks. We show that, while an assigned team’s performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today’s most complex problems.”

Lorelei Kelly at the Huffington Post: “It was hard to miss the giant mechanical giraffe grazing on the White House lawn last week. For the first time ever, the President organized a Maker Faire–inviting entrepreneurs and inventors from across the USA to celebrate American ingenuity in the service of economic progress.
The maker movement is a California original. Think R2D2 serving margaritas to a jester with an LED news scroll. The #nationofmakers Twitter feed has dozens of examples of collaborative production, of making, sharing and learning.
But since this was the White House, I still had to ask myself, what would the maker movement be if the economy was not the starting point? What if it was about civics? What if makers decided to create a modern, hands-on democracy?
What is democracy anyway but a never ending remix of new prototypes? Last week’s White House Maker Faire heralded a new economic bonanza. This revolution’s poster child is 3-D printing– decentralized fabrication that is customized to meet local needs. On the government front, new design rules for democracy are already happening in communities, where civics and technology have generated a front line of maker cities.
But the distance between California’s tech capacity and DC does seem 3000 miles wide. The NSA’s over collection/surveillance problem and Healthcare.gov’s doomed rollout are part of the same system-wide capacity deficit. How do we close the gap between California’s revolution and our institutions?

• In California, disruption is a business plan. In DC, it’s a national security threat.
• In California, hackers are artists. In DC, they are often viewed as criminals.
• In California, “cyber” is a dystopian science fiction word. In DC, cyber security is in a dozen oversight plans for Congress.

• in California, individuals are encouraged to “fail forward.” In DC, risk-aversion is bipartisan.

Scaling big problems with local solutions is a maker specialty. Government policymaking needs this kind of help.
Here’s the issue our nation is facing: The inability of the non-military side of our public institutions to process complex problems. Today, this competence and especially the capacity to solve technical challenges often exist only in the private sector. If something is urgent and can’t be monetized, it becomes a national security problem. Which increasingly means that critical decision making that should be in the civilian remit instead migrates to the military. Look at our foreign policy. Good government is a counter terrorism strategy in Afghanistan. Decades of civilian inaction on climate change means that now Miami is referred to as a battle space in policy conversations.
This rhetoric reflects an understandable but unacceptable disconnect for any democracy.
To make matters more confusing, much of the technology in civics (like list building petitions) is suited for elections, not for governing. It is often antagonistic. The result? policy making looks like campaigning. We need some civic tinkering to generate governing technology that comes with relationships. Specifically, this means technology that includes many voices, but has identifiable channels for expertise that can sort complexity and that is not compromised by financial self-interest.
Today, sorting and filtering information is a huge challenge for participation systems around the world. Information now ranks up there with money and people as a lever of power. On the people front, the loud and often destructive individuals are showing up effectively. On the money front, our public institutions are at risk of becoming purely pay to play (wonks call this “transactional”).
Makers, ask yourselves, how can we turn big data into a political constituency for using real evidence–one that can compete with all the negative noise and money in the system? For starters, technologists out West must stop treating government like it’s a bad signal that can be automated out of existence. We are at a moment where our society requires an engineering mindset to develop modern, tech-savvy rules for democracy. We need civic makers….”

Emily Shaw of Sunlight: “In healthcare, the goal-set shared widely throughout the field is known as “the Triple Aim”: improving individual experience of care, improving population health, and reducing the cost of care. Across the wide array of initiatives undertaken by health care data users, the great majority seem to fall within the scope of at least one aspect of the Triple Aim. Below is a set of examples that reveal how data — both open and not — is being used to achieve its elements.

The use of open data to reduce costs:

• The US Centers for Medicaid and Medicare Services (CMS) provided a critical boost to efforts to understand variation in health care pricing by releasing data about millions of payments to hospitals and individual physicians treating Medicare patients. Within CMS itself, this data release has powered visualization tools intended to inform and empower health care consumers; externally, researchers and journalists have used the CMS data to bring attention to unexplained variation in the cost of medical service provision. Through highlighting this variation, these analyses bring pressure to bear on high-cost places and providers.

• Federal action has increased the pressure on states to improve collection and provide access to their health care cost data. Non-profit organizations focused on health care cost observed that while states still have a far way to go before they are providing adequate levels of information about health care costs to their citizens, there has been a substantial amount of policy action and some concrete improvements just in the last year. Cooperation between associations of health care providers, insurance groups, and evaluative NGOs have produced efforts to produce comprehensive standards for health care cost transparency.

• Public-led efforts to increase cost transparency have led to additional non-governmental efforts to create both public-facing databases and price-check tools for private insurance subscribers, adding to the points of access for learning about variation in healthcare costs.

The use of open data to improve quality of care:

• Using open data on a substantial series of individual hospital quality measures, CMS created a hospital comparison tool that allows consumers to compare average quality of care outcomes across their local hospitals.

• Non-profit organizations survey hospitals and have used this data to provide another national measure of hospital quality that consumers can use to select a high-quality hospital.

• In New York state, widely-shared data on cardiac surgery outcomes associated with individual providers has led to improved outcomes and better understanding of successful techniques.

• In the UK, the National Health Service is actively working towards defining concrete metrics to evaluate how the system as a whole is moving towards improved quality. …

• The broad cultural shift towards data-sharing in healthcare appears to have facilitated additional secured sharing in order to achieve the joint goal of improving healthcare quality and effectiveness. The current effort to securely network of millions of patient data records through the federal PCORI system has the potential to advance understanding of disease treatment at an unprecedented pace.

• Through third-party tools, people are able to use the products of aggregated patient data in order to begin diagnosing their own symptoms more accurately, giving them a head start in understanding how to optimize their visit to a provider.

The use of open data to improve population health:

• Out of the three elements of the triple aim, population health may have the longest and deepest relationship with open data. Public datasets like those collected by the Centers for Disease Control and the US Census have for decades been used to monitor disease prevalence, verify access to health insurance, and track mortality and morbidity statistics.

• Population health improvement has been a major focus for newer developments as well. Health data has been a regular feature in tech efforts to improve the ways that governments — including local health departments — reach their constituencies. The use of data in new communication tools improves population health by increasing population awareness of local health trends and disease prevention opportunities. Two examples of this work in action include the Chicago Health Atlas, which combines health data and healthcare consumer problem-solving, and Philadelphia’s map interface to city data about available flu vaccines.

One final observation for open data advocates to take from health data concerns the way that the sector encourages the two-way information flow: it embraces the notion that data users can also be data producers. Open data ecosystems are properly characterized by multi-directional relationships among governmental and non-governmental actors, with opportunities for feedback, correction and augmentation of open datasets. That this happens at the scale of health data is important and meaningful for open data advocates who can face push-back when they ask their governments to ingest externally-generated data….”

Quentin Hardy in the New York Times: “Microsoft has a new strategy to win cloud business: A supposedly comprehensive predictive analysis service — and all you have to do is store your data in Azure, the Microsoft cloud.

The service, called Microsoft Azure Machine Learning, was announced Monday but won’t be available until July. It combines Microsoft’s own software with publicly available open source software, packaged in a way that is easier to use than most of the arcane strategies currently in use.
“This is drag-and-drop software,” said Joseph Sirosh, vice president for machine learning at Microsoft. “My high schooler is using this.”
That would be a big step forward in popularizing what is currently a difficult process in increasingly high demand. It would also further the ambitions of Satya Nadella, Microsoft’s chief executive, of making Azure the center of Microsoft’s future.
Users of Azure Machine Learning will have to keep their data in Azure, and Microsoft will provide ways to move data from competing services, like Amazon Web Services. Pricing has not yet been finalized, Mr. Sirosh said, but will be based on a premium to Azure’s standard computing and transmission charges.
Machine learning computers examine historical data through different algorithms and programming languages to make predictions. The process is commonly used in Internet search, fraud detection, product recommendations and digital personal assistants, among other things.
As more data is automatically stored online, there are opportunities to use machine learning for performing maintenance, scheduling hospital services, and anticipating disease outbreaks and crime, among other things. The methods have to become easier and cheaper to be popular, however.
That is the goal of Azure Machine Learning. “This is, as far as I know, the first comprehensive machine learning service in the cloud,” Mr. Sirosh said. “I’m leveraging every asset in Microsoft for this.” He is also using ways of accessing an open source version of R, a standard statistical language, while in Azure.
Microsoft is likely to face competition from rival cloud companies, including Google and Amazon. Both Google and Amazon have things like data frameworks used in building machine learning algorithms, as well as their own analysis services. IBM is eager to make use of its predictive software in its cloud business. Visualization companies like Tableau specialize in presenting the results so they can be acted on easily…”

Muchiri Nyaggah at the Open Institute: “There continues to be a great deal of dialogue and debate on what the data revolution from the report of the High Level Panel on the Post-2015 Development Agenda is all about. However, some have raised concerns that the emerging narrative around opening up data, strengthening national statistics offices or building capacity for e-government may not be revolutionary enough. In thinking through this it becomes clear that revolutions are highly contextual events. The Arab spring happened due to the unique factors of the cultural and social-economic environment in the Middle East and North Africa (MENA). A similar ‘spring’ may not happen in the same way in sub-Sahara Africa due to the peculiarities of the region. Attempting to replicate it is therefore an exercise in futility for those hoping for regime change.
We have just published a think piece on the role of public participation in policy making and how a data revolution could play out in that space. None of the ideas are revolutionary. They have been proposed and piloted in various countries to various extents over time. For instance, in some contexts strengthening and safe guarding the autonomy of the national statistics office may not seem revolutionary to some, in some countries it may be unprecedented (this is not part of the report). And that is okay. Nation states should be allowed, in their efforts to build capable and developmental institutions, to interpret the revolution for themselves.
In sub-Sahara Africa the availability of underlying data used to develop public policy is almost non-existent. Even when citizens are expected to participate in the formulation process and implementation of the policies, the data is still difficult to find. This neuters public participation and is a disservice to open government. Therefore making this detailed data and the accompanying rationale publicly available would be a revolutionary change in both culture and policy on access to information and potentially empower citizens to participate.
The data revolution is an opportunity to mainstream statistics into public discourse on public policy in ways that citizens can understand and engage with. I hope African countries will be willing to put an effort in translating the data revolution into an African revolution. If not, there’s a risk we shall continue singing about a revolution and never actually have one.
Download the ThinkPiece here”