Is internet freedom a tool for democracy or authoritarianism?

Curated on Posted on by Stefaan Verhulst

 and  in the Conversation: “The irony of internet freedom was on full display shortly after midnight July 16 in Turkey when President Erdogan used FaceTime and independent TV news to call for public resistance against the military coup that aimed to depose him.

In response, thousands of citizens took to the streets and aided the government in beating back the coup. The military plotters had taken over state TV. In this digital age they apparently didn’t realize television was no longer sufficient to ensure control over the message.

This story may appear like a triumphant example of the internet promoting democracy over authoritarianism.

Not so fast….This duality of the internet, as a tool to promote democracy or authoritarianism, or simultaneously both, is a complex puzzle.

The U.S. has made increasing internet access around the world a foreign policy priority. This policy was supported by both Secretaries of State John Kerry and Hillary Clinton.

The U.S. State Department has allocated tens of millions of dollars to promote internet freedom, primarily in the area of censorship circumvention. And just this month, the United Nations Human Rights Council passed a resolution declaring internet freedom a fundamental human right. The resolution condemns internet shutdowns by national governments, an act that has become increasingly common in variety of countries across the globe, including Turkey, Brazil, India and Uganda.

On the surface, this policy makes sense. The internet is an intuitive boon for democracy. It provides citizens around the world with greater freedom of expression, opportunities for civil society, education and political participation. And previous research, including our own, has been optimistic about the internet’s democratic potential.

However, this optimism is based on the assumption that citizens who gain internet access use it to expose themselves to new information, engage in political discussions, join social media groups that advocate for worthy causes and read news stories that change their outlook on the world.

And some do.

But others watch Netflix. They use the internet to post selfies to an intimate group of friends. They gain access to an infinite stream of music, movies and television shows. They spend hours playing video games.

However, our recent research shows that tuning out from politics and immersing oneself in online spectacle has political consequences for the health of democracy….Political use of the internet ranks very low globally, compared to other uses. Research has found that just 9 percent of internet users posted links to political news and only 10 percent posted their own thoughts about political or social issues. In contrast, almost three-quarters (72 percent) say they post about movies and music, and over half (54 percent) also say they post about sports online.

This inspired our study, which sought to show how the internet does not necessarily serve as democracy’s magical solution. Instead, its democratic potential is highly dependent on how citizens choose to use it….

Ensuring citizens have access to the internet is not sufficient to ensure democracy and human rights. In fact, internet access may negatively impact democracy if exploited for authoritarian gain.

The U.S. government, NGOs and other democracy advocates have invested a great deal of time and resources toward promoting internet access, fighting overt online censorship and creating circumvention technologies. Yet their success, at best, has been limited.

The reason is twofold. First, authoritarian governments have adapted their own strategies in response. Second, the “if we build it, they will come” philosophy underlying a great deal of internet freedom promotion doesn’t take into account basic human psychology in which entertainment choices are preferred over news and attitudes toward the internet determine its use, not the technology itself.

Allies in the internet freedom fight should realize that the locus of the fight has shifted. Greater efforts must be put toward tearing down “psychological firewalls,” building demand for internet freedom and influencing citizens to employ the internet’s democratic potential.

Doing so ensures that the democratic online toolkit is a match for the authoritarian one….(More)”

Human Smart Cities

Curated on Posted on by Stefaan Verhulst

Book edited by Concilio, Grazia and  Rizzo, Francesca: “Within the most recent discussion on smart cities and the way this vision is affecting urban changes and dynamics, this book explores the interplay between planning and design both at the level of the design and planning domains’ theories and practices.
Urban transformation is widely recognized as a complex phenomenon, rich in uncertainty. It is the unpredictable consequence of complex interplay between urban forces (both top-down or bottom-up), urban resources (spatial, social, economic and infrastructural as well as political or cognitive) and transformation opportunities (endogenous or exogenous).

The recent attention to Urban Living Lab and Smart City initiatives is disclosing a promising bridge between the micro-scale environments, with the dynamics of such forces and resources, and the urban governance mechanisms. This bridge is represented by those urban collaborative environments, where processes of smart service co-design take place through dialogic interaction with and among citizens within a situated and cultural-specific frame….(More)”

Big health data: the need to earn public trust

Curated on Posted on by Stefaan Verhulst

Tjeerd-Pieter van Staa et al in the BMJ: “Better use of large scale health data has the potential to benefit patient care, public health, and research. The handling of such data, however, raises concerns about patient privacy, even when the risks of disclosure are extremely small.

The problems are illustrated by recent English initiatives trying to aggregate and improve the accessibility of routinely collected healthcare and related records, sometimes loosely referred to as “big data.” One such initiative, care.data, was set to link and provide access to health and social care information from different settings, including primary care, to facilitate the planning and provision of healthcare and to advance health science.1 Data were to be extracted from all primary care practices in England. A related initiative, the Clinical Practice Research Datalink (CPRD), evolved from the General Practice Research Database (GPRD). CPRD was intended to build on GPRD by linking patients’ primary care records to hospital data, around 50 disease registries and clinical audits, genetic information from UK Biobank, and even the loyalty cards of a large supermarket chain, creating an integrated data repository and linked services for all of England that could be sold to universities, drug companies, and non-healthcare industries. Care.data has now been abandoned and CPRD has stalled. The flawed implementation of care.data plus earlier examples of data mismanagement have made privacy issues a mainstream public concern. We look at what went wrong and how future initiatives might gain public support….(More)”

US start-up aims to steer through flood of data

Curated on Posted on by Stefaan Verhulst

Richard Waters in the Financial Times: “The “open data” movement has produced a deluge of publicly available information this decade, as governments like those in the UK and US have released large volumes of data for general use.

But the flood has left researchers and data scientists with a problem: how do they find the best data sets, ensure these are accurate and up to date, and combine them with other sources of information?

The most ambitious in a spate of start-ups trying to tackle this problem is set to be unveiled on Monday, when data.world opens for limited release. A combination of online repository and social network, the site is designed to be a central platform to support the burgeoning activity around freely available data.

The aim closely mirrors Github, which has been credited with spurring the open source software movement by becoming both a place to store and find free programs as well as a crowdsourcing tool for identifying the most useful.

“We are at an inflection point,” said Jeff Meisel, chief marketing officer for the US Census Bureau. A “massive amount of data” has been released under open data provisions, he said, but “what hasn’t been there are the tools, the communities, the infrastructure to make that data easier to mash up”….

Data.world plans to seed its site with about a thousand data sets and attract academics as its first users, said Mr Hurt. By letting users create personal profiles on the site, follow others and collaborate around the information they are working on, the site hopes to create the kind of social dynamic that makes it more useful the more it is used.

An attraction of the service is the ability to upload data in any format and then use common web standards to link different data sets and create mash-ups with the information, said Dean Allemang, an expert in online data….(More)”

Can mobile usage predict illiteracy in a developing country?

Curated on Posted on by Stefaan Verhulst

Pål Sundsøy at arXiv: “The present study provides the first evidence that illiteracy can be reliably predicted from standard mobile phone logs. By deriving a broad set of mobile phone indicators reflecting users financial, social and mobility patterns we show how supervised machine learning can be used to predict individual illiteracy in an Asian developing country, externally validated against a large-scale survey. On average the model performs 10 times better than random guessing with a 70% accuracy. Further we show how individual illiteracy can be aggregated and mapped geographically at cell tower resolution. Geographical mapping of illiteracy is crucial to know where the illiterate people are, and where to put in resources. In underdeveloped countries such mappings are often based on out-dated household surveys with low spatial and temporal resolution. One in five people worldwide struggle with illiteracy, and it is estimated that illiteracy costs the global economy more than 1 trillion dollars each year. These results potentially enable cost-effective, questionnaire-free investigation of illiteracy-related questions on an unprecedented scale…(More)”.

Enablers for Smart Cities

Curated on Posted on by Stefaan Verhulst

Book by Amal El Fallah Seghrouchni, Fuyuki Ishikawa, Laurent Hérault, and Hideyuki Tokuda: “Smart cities are a new vision for urban development.  They integrate information and communication technology infrastructures – in the domains of artificial intelligence, distributed and cloud computing, and sensor networks – into a city, to facilitate quality of life for its citizens and sustainable growth.  This book explores various concepts for the development of these new technologies (including agent-oriented programming, broadband infrastructures, wireless sensor networks, Internet-based networked applications, open data and open platforms), and how they can provide smart services and enablers in a range of public domains.

The most significant research, both established and emerging, is brought together to enable academics and practitioners to investigate the possibilities of smart cities, and to generate the knowledge and solutions required to develop and maintain them…(More)”

The big health data sale

Curated on Posted on by Stefaan Verhulst

Philip Hunter at the EMBO Journal: “Personal health and medical data are a valuable commodity for a number of sectors from public health agencies to academic researchers to pharmaceutical companies. Moreover, “big data” companies are increasingly interested in tapping into this resource. One such firm is Google, whose subsidiary Deep Mind was granted access to medical records on 1.6 million patients who had been treated at some time by three major hospitals in London, UK, in order to develop a diagnostic app. The public discussion it raised was just another sign of the long‐going tensions between drug companies, privacy advocates, regulators, legislators, insurers and patients about privacy, consent, rights of access and ownership of medical data that is generated in pharmacies, hospitals and doctors’ surgeries. In addition, the rapid growth of eHealth will add a boon of even more health data from mobile phones, portable diagnostic devices and other sources.

These developments are driving efforts to create a legal framework for protecting confidentiality, controlling communication and governing access rights to data. Existing data protection and human rights laws are being modified to account for personal medical and health data in parallel to the campaign for greater transparency and access to clinical trial data. Healthcare agencies in particular will have to revise their procedures for handling medical or research data that is associated with patients.

Google’s foray into medical data demonstrates the key role of health agencies, in this case the Royal Free NHS Trust, which operates the three London hospitals that granted Deep Mind access to patient data. Royal Free approached Deep Mind with a request to develop an app for detecting acute kidney injury, which, according to the Trust, affects more than one in six inpatients….(More)”

What Governments Can Learn From Airbnb And the Sharing Economy

Curated on Posted on by Stefaan Verhulst

Arun Sundararajan in Fortune: “….Despite some regulators’ fears, the sharing economy may not result in the decline of regulation but rather in its opposite, providing a basis upon which society can develop more rational, ethical, and participatory models of regulation. But what regulation looks like, as well as who actually creates and enforce the regulation, is also bound to change.

There are three emerging models – peer regulation, self-regulatory organizations, and data-driven delegation – that promise a regulatory future for the sharing economy best aligned with society’s interests. In the adapted book excerpt that follows, I explain how the third of these approaches, of delegating enforcement of regulations to companies that store critical data on consumers, can help mitigate some of the biases Airbnb guests may face, and why this is a superior alternative to the “open data” approach of transferring consumer information to cities and state regulators.

Consider a different problem — of collecting hotel occupancy taxes from hundreds of thousands of Airbnb hosts rather than from a handful of corporate hotel chains. The delegation of tax collection to Airbnb, something a growing number of cities are experimenting with, has a number of advantages. It is likely to yield higher tax revenues and greater compliance than a system where hosts are required to register directly with the government, which is something occasional hosts seem reluctant to do. It also sidesteps privacy concerns resulting from mandates that digital platforms like Airbnb turn over detailed user data to the government. There is also significant opportunity for the platform to build credibility as it starts to take on quasi governmental roles like this.

There is yet another advantage, and the one I believe will be the most significant in the long-run. It asks a platform to leverage its data to ensure compliance with a set of laws in a manner geared towards delegating responsibility to the platform. You might say that the task in question here — computing tax owed, collecting, and remitting it—is technologically trivial. True. But I like this structure because of the potential it represents. It could be a precursor for much more exciting delegated possibilities.

For a couple of decades now, companies of different kinds have been mining the large sets of “data trails” customers provide through their digital interactions. This generates insights of business and social importance. One such effort we are all familiar with is credit card fraud detection. When an unusual pattern of activity is detected, you get a call from your bank’s security team. Sometimes your card is blocked temporarily. The enthusiasm of these digital security systems is sometimes a nuisance, but it stems from your credit card company using sophisticated machine learning techniques to identify patterns that prior experience has told it are associated with a stolen card. It saves billions of dollars in taxpayer and corporate funds by detecting and blocking fraudulent activity swiftly.

A more recent visible example of the power of mining large data sets of customer interaction came in 2008, when Google engineers announced that they could predict flu outbreaks using data collected from Google searches, and track the spread of flu outbreaks in real time, providing information that was well ahead of the information available using the Center for Disease Control’s (CDC) own tracking systems. The Google system’s performance deteriorated after a couple of years, but its impact on public perception of what might be possible using “big data” was immense.

It seems highly unlikely that such a system would have emerged if Google had been asked to hand over anonymized search data to the CDC. In fact, there would have probably been widespread public backlash to this on privacy grounds. Besides, the reason why this capability emerged organically from within Google is partly as a consequence of Google having one of the highest concentrations of computer science and machine learning talent in the world.

Similar approaches hold great promise as a regulatory approach for sharing economy platforms. Consider the issue of discriminatory practices. There has long been anecdotal evidence that some yellow cabs in New York discriminate against some nonwhite passengers. There have been similar concerns that such behavior may start to manifest on ridesharing platforms and in other peer-to-peer markets for accommodation and labor services.

For example, a 2014 study by Benjamin Edelman and Michael Luca of Harvard suggested that African American hosts might have lower pricing power than white hosts on Airbnb. While the study did not conclusively establish that the difference is due to guests discriminating against African American hosts, a follow-up study suggested that guests with “distinctively African American names” were less likely to receive favorable responses for their requests to Airbnb hosts. This research raises a red flag about the need for vigilance as the lines between personal and professional blur.

One solution would be to apply machine-learning techniques to be able to identify patterns associated with discriminatory behavior. No doubt, many platforms are already using such systems….(More)”

Power to the people: how cities can use digital technology to engage and empower citizens

Curated on Posted on by Stefaan Verhulst

Tom Saunders at NESTA: “You’re sat in city hall one day and you decide it would be a good idea to engage residents in whatever it is you’re working on – next year’s budget, for example, or the redevelopment of a run down shopping mall. How do you go about it?

In the past, you might have held resident meetings and exhibitions where people could view proposed designs or talk to city government employees. You can still do that today, but now there’s digital: apps, websites and social media. So you decide on a digital engagement strategy: you build a website or you run a social media campaign inviting feedback on your proposals. What happens next?

Two scenarios: 1) You get 50 responses, mostly from campaign groups and local political activists; or 2) you receive such a huge number of responses that you don’t know what to do with them. Besides which, you don’t have the power or budget to implement 90 per cent of the suggestions and neither do you have the time to tell people why their proposals will be ignored. The main outcome of your citizen engagement exercise seems to be that you have annoyed the very people you were trying to get buy in from. What went wrong?

Four tips for digital engagement

With all the apps and platforms out there, it’s hard to make sense of what is going on in the world of digital tools for citizen engagement. It seems there are three distinct activities that digital tools enable: delivering council services online – say applying for a parking permit; using citizen generated data to optimise city government processes and engaging citizens in democratic exercises. In Conneced Councils Nesta sets out what future models of online service delivery could look like. Here I want to focus on the ways that engaging citizens with digital technology can help city governments deliver services more efficiently and improve engagement in democratic processes.

  1. Resist the temptation to build an app…

  1. Think about what you want to engage citizens for…

Sometimes engagement is statutory: communities have to be shown new plans for their area. Beyond this, there are a number of activities that citizen engagement is useful for. When designing a citizen engagement exercise it may help to think which of the following you are trying to achieve (note: they aren’t mutually exclusive):

  • Better understanding of the facts

If you want to use digital technologies to collect more data about what is happening in your city, you can buy a large number of sensors and install them across the city, to track everything from people movements to how full bins are. A cheaper and possibly more efficient way for cities to do this might involve working with people to collect this data – making use of the smartphones that an increasing number of your residents carry around with them. Prominent examples of this included flood mapping in Jakarta using geolocated tweets and pothole mapping in Boston using a mobile app.

For developed world cities, the thought of outsourcing flood mapping to citizens might fill government employees with horror. But for cities in developing countries, these technologies present an opportunity, potentially, for them to leapfrog their peers – to reach a level of coverage now that would normally require decades of investment in infrastructure to achieve. This is currently a hypothetical situation: cities around the world are only just starting to pilot these ideas and technologies and it will take a number of years before we know how useful they are to city governments.

  • Generating better ideas and options

The examples above involve passive data collection. Moving beyond this to more active contributions, city governments can engage citizens to generate better ideas and options. There are numerous examples of this in urban planning – the use of Minecraft by the UN in Nairobi to collect and visualise ideas for the future development of the community, or the Carticipe platform in France, which residents can use to indicate changes they would like to see in their city on a map.

It’s all very well to create a digital suggestion box, but there is a lot of evidence that deliberation and debate lead to much better ideas. Platforms like BetterReykjavic include a debate function for any idea that is proposed. Based on feedback, the person who submitted the idea can then edit it, before putting it to a public vote – only then, if the proposal gets the required number of votes, is it sent to the city council for debate.

  • Better decision making

As well as enabling better decision making by giving city government employees, better data and better ideas, digital technologies can give the power to make decisions directly to citizens. This is best encapsulated by participatory budgeting – which involves allowing citizens to decide how a percentage of the city budget is spent. Participatory budgeting emerged in Brazil in the 1980s, but digital technologies help city governments reach a much larger audience. ‘Madame Mayor, I have an idea’ is a participatory budgeting process that lets citizens propose and vote on ideas for projects in Paris. Over 20,000 people have registered on the platform and the pilot phase of the project received over 5000 submissions.

  1. Remember that there’s a world beyond the internet…

  1. Pick the right question for the right crowd…

When we talk to city governments and local authorities, they express a number of fears about citizen engagement: Fear of relying on the public for the delivery of critical services, fear of being drowned in feedback and fear of not being inclusive – only engaging with those that are online and motivated. Hopefully, thinking through the issues discussed above may help alleviate some of these fears and make city government more enthusiastic about digital engagement….(More)

How Twitter gives scientists a window into human happiness and health

Curated on Posted on by Stefaan Verhulst

 at the Conversation: “Since its public launch 10 years ago, Twitter has been used as a social networking platform among friends, an instant messaging service for smartphone users and a promotional tool for corporations and politicians.

But it’s also been an invaluable source of data for researchers and scientists – like myself – who want to study how humans feel and function within complex social systems.

By analyzing tweets, we’ve been able to observe and collect data on the social interactions of millions of people “in the wild,” outside of controlled laboratory experiments.

It’s enabled us to develop tools for monitoring the collective emotions of large populations, find the happiest places in the United States and much more.

So how, exactly, did Twitter become such a unique resource for computational social scientists? And what has it allowed us to discover?

Twitter’s biggest gift to researchers

On July 15, 2006, Twittr (as it was then known) publicly launched as a “mobile service that helps groups of friends bounce random thoughts around with SMS.” The ability to send free 140-character group texts drove many early adopters (myself included) to use the platform.

With time, the number of users exploded: from 20 million in 2009 to 200 million in 2012 and 310 million today. Rather than communicating directly with friends, users would simply tell their followers how they felt, respond to news positively or negatively, or crack jokes.

For researchers, Twitter’s biggest gift has been the provision of large quantities of open data. Twitter was one of the first major social networks to provide data samples through something called Application Programming Interfaces (APIs), which enable researchers to query Twitter for specific types of tweets (e.g., tweets that contain certain words), as well as information on users.

This led to an explosion of research projects exploiting this data. Today, a Google Scholar search for “Twitter” produces six million hits, compared with five million for “Facebook.” The difference is especially striking given that Facebook has roughly five times as many users as Twitter (and is two years older).

Twitter’s generous data policy undoubtedly led to some excellent free publicity for the company, as interesting scientific studies got picked up by the mainstream media.

Studying happiness and health

With traditional census data slow and expensive to collect, open data feeds like Twitter have the potential to provide a real-time window to see changes in large populations.

The University of Vermont’s Computational Story Lab was founded in 2006 and studies problems across applied mathematics, sociology and physics. Since 2008, the Story Lab has collected billions of tweets through Twitter’s “Gardenhose” feed, an API that streams a random sample of 10 percent of all public tweets in real time.

I spent three years at the Computational Story Lab and was lucky to be a part of many interesting studies using this data. For example, we developed a hedonometer that measures the happiness of the Twittersphere in real time. By focusing on geolocated tweets sent from smartphones, we were able to map the happiest places in the United States. Perhaps unsurprisingly, we found Hawaii to be the happiest state and wine-growing Napa the happiest city for 2013.

A map of 13 million geolocated U.S. tweets from 2013, colored by happiness, with red indicating happiness and blue indicating sadness. PLOS ONE, Author provided

These studies had deeper applications: Correlating Twitter word usage with demographics helped us understand underlying socioeconomic patterns in cities. For example, we could link word usage with health factors like obesity, so we built a lexicocalorimeter to measure the “caloric content” of social media posts. Tweets from a particular region that mentioned high-calorie foods increased the “caloric content” of that region, while tweets that mentioned exercise activities decreased our metric. We found that this simple measure correlates with other health and well-being metrics. In other words, tweets were able to give us a snapshot, at a specific moment in time, of the overall health of a city or region.

Using the richness of Twitter data, we’ve also been able to see people’s daily movement patterns in unprecedented detail. Understanding human mobility patterns, in turn, has the capacity to transform disease modeling, opening up the new field of digital epidemiology….(More)”