Stefaan Verhulst

Will Blockchain Disrupt Government Corruption?

Curated on March 8, 2018August 3, 2018 by Stefaan Verhulst

Carlos Santiso in Stanford Social Innovation Review: “Will blockchain technology be the next disrupting technology to revolutionize government? Probably not. Can it be a game changer in the global fight against corruption? Possibly so. New technologies are disrupting our lives and transforming government. Governments around the world are going digital, embracing digital innovations to modernize their bureaucracies and recast their relations with citizens. Technology is changing how governments are expected to meet the rising expectations of citizens in terms of quality, speed, and integrity. Digital citizens are expecting more from their governments, demanding better services and greater accountability. Governments struggle to catch up.

Technology has become the greatest ally of transparency, as it allows one to leverage the insights that can be gleaned from the exponential growth of data. Digitally savvy citizens are far less tolerant about corruption and have more means to uncover it. There are heightened and even inflated expectations about the potential of blockchain to improve the delivery of public services and strengthen integrity in government. Pilots and proofs of concept are mushrooming, driven by a myriad of technology-driven start-ups in a wide variety of industries. This enthusiasm is generating intense debate, and an “expectations bubble” is building up rapidly.

Given the hype, it is important to assess both the promises and the pitfalls of blockchain, thinking through what it can and cannot do, based on hard evidence. Initiatives such as blockchan.ge by New York University’s Governance Lab are starting to look closer at whether and how blockchain technologies can be used for social change. Blockchain has emerged first in the financial industry, building on cryptocurrencies such as Bitcoin. The requirements and implications of blockchain in the public sector, however, are yet to be fully understood. Key issues include being clearer about the problems it is expected to address, its advantages compared to alternative digital solutions, its fitness-for-purpose in different institutional contexts, and, ultimately, the value it could add to existing institutions….(More)”

Exploring the Motives of Citizen Reporting Engagement: Self-Concern and Other-Orientation

Curated on March 8, 2018August 3, 2018 by Stefaan Verhulst

Paper by Gabriel Abu-Tayeh, Oliver Neumann and Matthias Stuermer: “In smart city contexts, voluntary citizen reporting can be a particularly valuable source of information for local authorities. A key question in this regard is what motivates citizens to contribute their data. Drawing on motivation research in social psychology, the paper examines the question of whether self-concern or other-orientation is a stronger driver of citizen reporting engagement.

To test their hypotheses, the authors rely on a sample of users from the mobile application “Zurich as good as new” in Switzerland, which enables citizens to report damages in and other issues with the city’s infrastructure. Data was collected from two different sources: motivation was assessed in an online user survey (n = 650), whereas citizen reporting engagement was measured by the number of reports per user from real platform-use data. The analysis was carried out using negative binomial regression.

The findings suggest that both self-concern and other-orientation are significant drivers of citizen reporting engagement, although the effect of self-concern appears to be stronger in comparison. As such, this study contributes to a better understanding of what motivates citizens to participate in citizen reporting platforms, which are a cornerstone application in many smart cities….(More)”.

Data Science Landscape

Curated on March 8, 2018August 3, 2018 by Stefaan Verhulst

Book edited by Usha Mujoo Munshi and Neeta Verma: “The edited volume deals with different contours of data science with special reference to data management for the research innovation landscape. The data is becoming pervasive in all spheres of human, economic and development activity. In this context, it is important to take stock of what is being done in the data management area and begin to prioritize, consider and formulate adoption of a formal data management system including citation protocols for use by research communities in different disciplines and also address various technical research issues. The volume, thus, focuses on some of these issues drawing typical examples from various domains….

In all, there are 21 chapters (with 21st Chapter addressing four different core aspects) written by eminent researchers in the field which deal with key issues of S&T, institutional, financial, sustainability, legal, IPR, data protocols, community norms and others, that need attention related to data management practices and protocols, coordinate area activities, and promote common practices and standards of the research community globally. In addition to the aspects touched above, the national / international perspectives of data and its various contours have also been portrayed through case studies in this volume. …(More)”.

Nudging the city and residents of Cape Town to save water

Curated on March 7, 2018May 29, 2019 by Stefaan Verhulst

Leila Harris, Jiaying Zhao and Martine Visser in The Conversation: “Cape Town could become the world’s first major city to run out of water – what’s been termed Day Zero….To its credit, the city has worked with researchers at the University of Cape Town to test strategies to nudge domestic users into reducing their water use. Nudges are interventions to encourage behaviour change for better outcomes, or in this context, to achieve environmental or conservation goals.

What key insights could help inform the city’s strategies? Research from psychology and behavioural economics could prove useful to refine efforts and help to achieve further water savings.

The most effective tactics

Research suggests the following types of nudges could be effective in promoting conservation behaviours.

Social norms: International research, as well as studies conducted in Cape Town, suggest that effective conservation can be promoted by giving feedback to consumers on how they perform relative to their neighbours. To this end, Cape Town introduced a water map that highlights homes that are compliant with targets.

The city has also been bundling information on usage with easy to implement water saving tips, something that research has shown to be particularly effective.

Research also suggests that combining behavioural interventions with traditional measures – such as tariff increases and restrictions – are often effective to reduce use in the short-term.

Real-time feedback: Cape Town is presenting the daily water level in major dams on a dashboard. This approach is consistent with research that shows that real-time information can effectively reduce water and energy consumption.

Such efforts could even be more effective if information is highlighted in relation to the critical level that’s been set for Day Zero, in this case 13.5%.

In the early days of a drought, it is also advisable to make information like this readily accessible through news outlets, social media, or even text messages. The water tracker produced by eighty20, a private Cape Town-based company, provides an example.

Social recognition: There’s evidence that efforts to celebrate successes or encourage competition can be effective – for instance, recognising neighbourhoods for meeting conservation targets. Prizes needn’t be monetary. Sometimes simple recognition, such as a certificate, can be effective.

Social recognition was found to be the most successful intervention among nine others nudges tested in research conducted in Cape Town in 2016. In this experiment, households who reduced consumption by 10% were recognised on the city’s website.

Another study showed that competition between the various floors of a government building in the Western Cape led to energy savings of up to 14%.

Cooperation: In the months ahead, the city would also do well to consider the support it might offer to encourage cooperation, particularly as the situation becomes more acute and as tensions rise.

Past studies have shown that social reputation and efforts to promote reciprocity can go a long way to encourage cooperation. The point is argued in a recent article featuring the importance of cooperation among Capetonians across different income groups.

Some residents of Cape Town are already pushing for a cooperative approach such as helping neighbours who might have difficulty travelling to collection points. Support for these efforts should be an important part of policies in the run up to Day Zero. These are often the examples that provide bright spots in challenging times.

Research also suggests that to navigate moments of crisis effectively, clear and trustworthy communication is critical. This also needs to be a priority….(More)“.

Artificial intelligence could identify gang crimes—and ignite an ethical firestorm

Curated on March 7, 2018August 3, 2018 by Stefaan Verhulst

Matthew Hutson at Science: “When someone roughs up a pedestrian, robs a store, or kills in cold blood, police want to know whether the perpetrator was a gang member: Do they need to send in a special enforcement team? Should they expect a crime in retaliation? Now, a new algorithm is trying to automate the process of identifying gang crimes. But some scientists warn that far from reducing gang violence, the program could do the opposite by eroding trust in communities, or it could brand innocent people as gang members.

That has created some tensions. At a presentation of the new program this month, one audience member grew so upset he stormed out of the talk, and some of the creators of the program have been tight-lipped about how it could be used….

For years, scientists have been using computer algorithms to map criminal networks, or to guess where and when future crimes might take place, a practice known as predictive policing. But little work has been done on labeling past crimes as gang-related.

In the new work, researchers developed a system that can identify a crime as gang-related based on only four pieces of information: the primary weapon, the number of suspects, and the neighborhood and location (such as an alley or street corner) where the crime took place. Such analytics, which can help characterize crimes before they’re fully investigated, could change how police respond, says Doug Haubert, city prosecutor for Long Beach, California, who has authored strategies on gang prevention.

To classify crimes, the researchers invented something called a partially generative neural network. A neural network is made of layers of small computing elements that process data in a way reminiscent of the brain’s neurons. A form of machine learning, it improves based on feedback—whether its judgments were right. In this case, researchers trained their algorithm using data from the Los Angeles Police Department (LAPD) in California from 2014 to 2016 on more than 50,000 gang-related and non–gang-related homicides, aggravated assaults, and robberies.

The researchers then tested their algorithm on another set of LAPD data. The network was “partially generative,” because even when it did not receive an officer’s narrative summary of a crime, it could use the four factors noted above to fill in that missing information and then use all the pieces to infer whether a crime was gang-related. Compared with a stripped-down version of the network that didn’t use this novel approach, the partially generative algorithm reduced errors by close to 30%, the team reported at the Artificial Intelligence, Ethics, and Society (AIES) conference this month in New Orleans, Louisiana. The researchers have not yet tested their algorithm’s accuracy against trained officers.

It’s an “interesting paper,” says Pete Burnap, a computer scientist at Cardiff University who has studied crime data. But although the predictions could be useful, it’s possible they would be no better than officers’ intuitions, he says. Haubert agrees, but he says that having the assistance of data modeling could sometimes produce “better and faster results.” Such analytics, he says, “would be especially useful in large urban areas where a lot of data is available.”…(More).

Infection forecasts powered by big data

Curated on March 7, 2018July 19, 2019 by Stefaan Verhulst

Michael Eisenstein at Nature: “…The good news is that the present era of widespread access to the Internet and digital health has created a rich reservoir of valuable data for researchers to dive into….By harvesting and combining these streams of big data with conventional ways of monitoring infectious diseases, the public-health community could gain fresh powers to catch and curb emerging outbreaks before they rage out of control.

Going viral

Data scientists at Google were the first to make a major splash using data gathered online to track infectious diseases. The Google Flu Trends algorithm, launched in November 2008, combed through hundreds of billions of users’ queries on the popular search engine to look for small increases in flu-related terms such as symptoms or vaccine availability. Initial data suggested that Google Flu Trends could accurately map the incidence of flu with a lag of roughly one day. “It was a very exciting use of these data for the purpose of public health,” says Brownstein. “It really did start a whole revolution and new field of work in query data.”

Unfortunately, Google Flu Trends faltered when it mattered the most, completely missing the onset in April 2009 of the H1N1 pandemic. The algorithm also ran into trouble later on in the pandemic. It had been trained against seasonal fluctuations of flu, says Viboud, but people’s behaviour changed in the wake of panic fuelled by media reports — and that threw off Google’s data. …

Nevertheless, its work with Internet usage data was inspirational for infectious-disease researchers. A subsequent study from a team led by Cecilia Marques-Toledo at the Federal University of Minas Gerais in Belo Horizonte, Brazil, used Twitter to get high-resolution data on the spread of dengue fever in the country. The researchers could quickly map new cases to specific cities and even predict where the disease might spread to next (C. A. Marques-Toledo et al. PLoS Negl. Trop. Dis. 11, e0005729; 2017). Similarly, Brownstein and his colleagues were able to use search data from Google and Twitter to project the spread of Zika virus in Latin America several weeks before formal outbreak declarations were made by public-health officials. Both Internet services are used widely, which makes them data-rich resources. But they are also proprietary systems for which access to data is controlled by a third party; for that reason, Generous and his colleagues have opted instead to make use of search data from Wikipedia, which is open source. “You can get the access logs, and how many people are viewing articles, which serves as a pretty good proxy for search interest,” he says.

However, the problems that sank Google Flu Trends still exist….Additionally, online activity differs for infectious conditions with a social stigma such as syphilis or AIDS, because people who are or might be affected are more likely to be concerned about privacy. Appropriate search-term selection is essential: Generous notes that initial attempts to track flu on Twitter were confounded by irrelevant tweets about ‘Bieber fever’ — a decidedly non-fatal condition affecting fans of Canadian pop star Justin Bieber.

Alternatively, researchers can go straight to the source — by using smartphone apps to ask people directly about their health. Brownstein’s team has partnered with the Skoll Global Threats Fund to develop an app called Flu Near You, through which users can voluntarily report symptoms of infection and other information. “You get more detailed demographics about age and gender and vaccination status — things that you can’t get from other sources,” says Brownstein. Ten European Union member states are involved in a similar surveillance programme known as Influenzanet, which has generally maintained 30,000–40,000 active users for seven consecutive flu seasons. These voluntary reporting systems are particularly useful for diseases such as flu, for which many people do not bother going to the doctor — although it can be hard to persuade people to participate for no immediate benefit, says Brownstein. “But we still get a good signal from the people that are willing to be a part of this.”…(More)”.

Launching the Data Culture Project

Curated on March 7, 2018August 3, 2018 by Stefaan Verhulst

New project by MIT Center for Civic Media and the Engagement Lab@Emerson College: “Learning to work with data is like learning a new language — immersing yourself in the culture is the best way to do it. For some individuals, this means jumping into tools like Excel, Tableau, programming, or R Studio. But what does this mean for a group of people that work together? We often talk about data literacy as if it’s an individual capacity, but what about data literacy for a community? How does an organization learn how to work with data?

About a year ago we (Rahul Bhargava and Catherine D’Ignazio) found that more and more users of our DataBasic.io suite of tools and activities were asking this question — online and in workshops. In response, with support from the Stanford Center on Philanthropy and Civil Society, we’ve worked together with 25 organizations to create the Data Culture Project. We’re happy to launch it publicly today! Visit datacultureproject.org to learn more.

The Data Culture Project is a hands-on learning program to kickstart a data culture within your organization. We provide facilitation videos to help you run creative introductions to get people across your organization talking to each other — from IT to marketing to programs to evaluation. These are not boring spreadsheet trainings! Try running our fun activities — one per month works as a brown bag lunch to focus people on a common learning goal. For example, “Sketch a Story” brings people together around basic concepts of quantitative text analysis and visual storytelling. “Asking Good Questions” introduces principles of exploratory data analysis in a fun environment. What’s more, you can use the sample data that we provide, or you can integrate your organization’s data as the topic of conversation and learning….(More)”.

Your Data Is Crucial to a Robotic Age. Shouldn’t You Be Paid for It?

Curated on March 7, 2018August 3, 2018 by Stefaan Verhulst

Eduardo Porter at The New York Times: “The idea has been around for a bit. Jaron Lanier, the tech philosopher and virtual-reality pioneer who now works for Microsoft Research, proposed it in his 2013 book, “Who Owns the Future?,” as a needed corrective to an online economy mostly financed by advertisers’ covert manipulation of users’ consumer choices.

It is being picked up in “Radical Markets,” a book due out shortly from Eric A. Posner of the University of Chicago Law School and E. Glen Weyl, principal researcher at Microsoft. And it is playing into European efforts to collect tax revenue from American internet giants.

In a report obtained last month by Politico, the European Commission proposes to impose a tax on the revenue of digital companies based on their users’ location, on the grounds that “a significant part of the value of a business is created where the users are based and data is collected and processed.”

Users’ data is a valuable commodity. Facebook offers advertisers precisely targeted audiences based on user profiles. YouTube, too, uses users’ preferences to tailor its feed. Still, this pales in comparison with how valuable data is about to become, as the footprint of artificial intelligence extends across the economy.

Data is the crucial ingredient of the A.I. revolution. Training systems to perform even relatively straightforward tasks like voice translation, voice transcription or image recognition requires vast amounts of data — like tagged photos, to identify their content, or recordings with transcriptions.

“Among leading A.I. teams, many can likely replicate others’ software in, at most, one to two years,” notes the technologist Andrew Ng. “But it is exceedingly difficult to get access to someone else’s data. Thus data, rather than software, is the defensible barrier for many businesses.”

We may think we get a fair deal, offering our data as the price of sharing puppy pictures. By other metrics, we are being victimized: In the largest technology companies, the share of income going to labor is only about 5 to 15 percent, Mr. Posner and Mr. Weyl write. That’s way below Walmart’s 80 percent. Consumer data amounts to work they get free….

The big question, of course, is how we get there from here. My guess is that it would be naïve to expect Google and Facebook to start paying for user data of their own accord, even if that improved the quality of the information. Could policymakers step in, somewhat the way the European Commission did, demanding that technology companies compute the value of consumer data?…(More)”.

New game aims to inoculate people against fake news

Curated on March 7, 2018August 3, 2018 by Stefaan Verhulst

Springwise: “The term ‘fake news’ has become all too common in media coverage. However, a news item doesn’t have to be entirely made up to be misleading. Many fake news stories intend to deceive, often with a political agenda. Disinformation works because many people fail to recognise false information. A recent study, conducted by Britain’s Channel 4, found that only four percent of those surveyed could tell fake news from real. So how to inoculate people against fake news? Dutch organisation DROG, which works against the spread of disinformation, has teamed up with researchers at Cambridge University in the United Kingdom to develop a game that they claim can help confer resistance against false or misleading information.

The game, titled The Bad News Game, works by putting players in the position of creating fake news, so that they gain insight into the tactics and methods used by ‘real’ fake news-mongers to spread their message. This, in turn, builds up resistance to fake news. In the game, players are shown short texts or images and can react to them in a variety of ways. Choosing an option similar to that followed by a ‘real’ producer of disinformation earns the player more followers and credibility. Lying too blatantly, choosing an option that is obviously ridiculous, or acting in line with journalistic best practices, and the player will lose followers and credibility. The aim of the game is to gather as many followers as possible without losing too much credibility.

The Bad News Game is suitable for use in schools and takes around 20 minutes to complete. It joins other recent socially conscious educational innovations such as a cooking app that encourages healthy eating and a board game that eases discussions about arranged marriages….(More)”.