Stefaan Verhulst

Trust, Security, and Privacy in Crowdsourcing

Curated on August 20, 2018 by Stefaan Verhulst

Guest Editorial to Special Issue of IEEE Internet of Things Journal: “As we become increasingly reliant on intelligent, interconnected devices in every aspect of our lives, critical trust, security, and privacy concerns are raised as well.

First, the sensing data provided by individual participants is not always reliable. It may be noisy or even faked due to various reasons, such as poor sensor quality, lack of sensor calibration, background noise, context impact, mobility, incomplete view of observations, or malicious attacks. The crowdsourcing applications should be able to evaluate the trustworthiness of collected data in order to filter out the noisy and fake data that may disturb or intrude a crowdsourcing system. Second, providing data (e.g., photographs taken with personal mobile devices) or using IoT applications may compromise data providers’ personal data privacy (e.g., location, trajectory, and activity privacy) and identity privacy. Therefore, it becomes essential to assess the trust of the data while preserving the data providers’ privacy. Third, data analytics and mining in crowdsourcing may disclose the privacy of data providers or related entities to unauthorized parities, which lowers the willingness of participants to contribute to the crowdsourcing system, impacts system acceptance, and greatly impedes its further development. Fourth, the identities of data providers could be forged by malicious attackers to intrude the whole crowdsourcing system. In this context, trust, security, and privacy start to attract a special attention in order to achieve high quality of service in each step of crowdsourcing with regard to data collection, transmission, selection, processing, analysis and mining, as well as utilization.

Trust, security, and privacy in crowdsourcing receives increasing attention. Many methods have been proposed to protect privacy in the process of data collection and processing. For example, data perturbation can be adopted to hide the real data values during data collection. When preprocessing the collected data, data anonymization (e.g., k-anonymization) and fusion can be applied to break the links between the data and their sources/providers. In application layer, anonymity is used to mask the real identities of data sources/providers. To enable privacy-preserving data mining, secure multiparty computation (SMC) and homomorphic encryption provide options for protecting raw data when multiple parties jointly run a data mining algorithm. Through cryptographic techniques, no party knows anything else than its own input and expected results. For data truth discovery, applicable solutions include correlation-based data quality analysis and trust evaluation of data sources. But current solutions are still imperfect, incomprehensive, and inefficient….(More)”.

What is mechanistic evidence, and why do we need it for evidence-based policy?

Curated on August 20, 2018October 23, 2018 by Stefaan Verhulst

Paper by Caterina Marchionni and Samuli Reijula: “It has recently been argued that successful evidence-based policy should rely on two kinds of evidence: statistical and mechanistic. The former is held to be evidence that a policy brings about the desired outcome, and the latter concerns how it does so. Although agreeing with the spirit of this proposal, we argue that the underlying conception of mechanistic evidence as evidence that is different in kind from correlational, difference-making or statistical evidence, does not correctly capture the role that information about mechanisms should play in evidence-based policy. We offer an alternative account of mechanistic evidence as information concerning the causal pathway connecting the policy intervention to its outcome. Not only can this be analyzed as evidence of difference-making, it is also to be found at any level and is obtainable by a broad range of methods, both experimental and observational. Using behavioral policy as an illustration, we draw the implications of this revised understanding of mechanistic evidence for debates concerning policy extrapolation, evidence hierarchies, and evidence integration…(More)”.

Data Science Thinking: The Next Scientific, Technological and Economic Revolution

Curated on August 20, 2018 by Stefaan Verhulst

Book by Longbing Cao: “This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists?

Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.

The topics cover an extremely wide spectrum of essential and relevant aspects of data science, spanning its evolution, concepts, thinking, challenges, discipline, and foundation, all the way to industrialization, profession, education, and the vast array of opportunities that data science offers. The book’s three parts each detail layers of these different aspects….(More)”.

The effects of ICT use and ICT Laws on corruption: A general deterrence theory perspective

Curated on August 19, 2018 by Stefaan Verhulst

Anol Bhattacherjee and Utkarsh Shrivastava in Government Information Quarterly: “Investigations of white collar crimes such as corruption are often hindered by the lack of information or physical evidence. Information and communication technologies (ICT), by virtue of their ability to monitor, track, record, analyze, and share vast amounts of information may help countries identify and prosecute criminals, and deter future corruption. While prior studies have demonstrated that ICT is an important tool in reducing corruption at the country level, they provide little explanation as to how ICT influences corruption and when does it work best.

We explore these gaps in the literature using the hypothetico-deductive approach to research, by using general deterrence theory to postulate a series of main and moderating effects relating ICT use and corruption, and then testing those effects using secondary data analysis. Our analysis suggests that ICT use influences corruption by increasing the certainty and celerity of punishment related to corruption. Moreover, ICT laws moderate the effect of ICT use on corruption, suggesting that ICT investments may have limited effect on corruption, unless complemented with appropriate ICT laws. Implications of our findings for research and practice are discussed….(More)”.

Behavioural science and policy: where are we now and where are we going?

Curated on August 19, 2018 by Stefaan Verhulst

Michael Sanders et al in Behavioral Public Policy: “The use of behavioural sciences in government has expanded and matured in the last decade. Since the Behavioural Insights Team (BIT) has been part of this movement, we sketch out the history of the team and the current state of behavioural public policy, recognising that other works have already told this story in detail. We then set out two clusters of issues that have emerged from our work at BIT. The first cluster concerns current challenges facing behavioural public policy: the long-term effects of interventions; repeated exposure effects; problems with proxy measures; spillovers and general equilibrium effects and unintended consequences; cultural variation; ‘reverse impact’; and the replication crisis. The second cluster concerns opportunities: influencing the behaviour of government itself; scaling interventions; social diffusion; nudging organisations; and dealing with thorny problems. We conclude that the field will need to address these challenges and take these opportunities in order to realise the full potential of behavioural public policy….(More)”.

Odd Numbers: Algorithms alone can’t meaningfully hold other algorithms accountable

Curated on August 18, 2018 by Stefaan Verhulst

Frank Pasquale at Real Life Magazine: “Algorithms increasingly govern our social world, transforming data into scores or rankings that decide who gets credit, jobs, dates, policing, and much more. The field of “algorithmic accountability” has arisen to highlight the problems with such methods of classifying people, and it has great promise: Cutting-edge work in critical algorithm studies applies social theory to current events; law and policy experts seem to publish new articles daily on how artificial intelligence shapes our lives, and a growing community of researchers has developed a field known as “Fairness, Accuracy, and Transparency in Machine Learning.”

The social scientists, attorneys, and computer scientists promoting algorithmic accountability aspire to advance knowledge and promote justice. But what should such “accountability” more specifically consist of? Who will define it? At a two-day, interdisciplinary roundtable on AI ethics I recently attended, such questions featured prominently, and humanists, policy experts, and lawyers engaged in a free-wheeling discussion about topics ranging from robot arms races to computationally planned economies. But at the end of the event, an emissary from a group funded by Elon Musk and Peter Thiel among others pronounced our work useless. “You have no common methodology,” he informed us (apparently unaware that that’s the point of an interdisciplinary meeting). “We have a great deal of money to fund real research on AI ethics and policy”— which he thought of as dry, economistic modeling of competition and cooperation via technology — “but this is not the right group.” He then gratuitously lashed out at academics in attendance as “rent seekers,” largely because we had the temerity to advance distinctive disciplinary perspectives rather than fall in line with his research agenda.

Most corporate contacts and philanthrocapitalists are more polite, but their sense of what is realistic and what is utopian, what is worth studying and what is mere ideology, is strongly shaping algorithmic accountability research in both social science and computer science. This influence in the realm of ideas has powerful effects beyond it. Energy that could be put into better public transit systems is instead diverted to perfect the coding of self-driving cars. Anti-surveillance activism transmogrifies into proposals to improve facial recognition systems to better recognize all faces. To help payday-loan seekers, developers might design data-segmentation protocols to show them what personal information they should reveal to get a lower interest rate. But the idea that such self-monitoring and data curation can be a trap, disciplining the user in ever finer-grained ways, remains less explored. Trying to make these games fairer, the research elides the possibility of rejecting them altogether….(More)”.

World War Web

Curated on August 17, 2018 by Stefaan Verhulst

Special issue of Foreign Affairs: “The last few decades have witnessed the growth of an American-sponsored Internet open to all. But that was then; conditions have changed.

History is filled with supposed lost utopias, and there is no greater cliché than to see one’s own era as a lamentable decline from a previous golden age. Sometimes, however, clichés are right. And as we explored the Internet’s future for this issue’s lead package, it became clear this was one of those times. Contemplating where we have come from digitally and where we are heading, it’s hard not to feel increasingly wistful and nostalgic.

The last few decades have witnessed the growth of an American-sponsored Internet open to all, and that has helped tie the world together, bringing wide-ranging benefits to billions. But that was then; conditions have changed.

Other great powers are contesting U.S. digital leadership, pushing their own national priorities. Security threats appear and evolve constantly. Platforms that were supposed to expand and enrich the marketplace of ideas have been hijacked by trolls and bots and flooded with disinformation. And real power is increasingly concentrated in the hands of a few private tech giants, whose self-interested choices have dramatic consequences for the entire world around them.

Whatever emerges from this melee, it will be different from, and in many ways worse than, what we have now.

Adam Segal paints the big picture well. “The Internet has long been an American project,” he writes. “Yet today, the United States has ceded leadership in cyberspace to China.” What will happen if Beijing continues its online ascent? “The Internet will be less global and less open. A major part of it will run Chinese applications over Chinese-made hardware. And Beijing will reap the economic, diplomatic, national security, and intelligence benefits that once flowed to Washington.”

Nandan Nilekani, a co-founder of Infosys, outlines India’s unique approach to these issues, which is based on treating “digital infrastructure as a public good and data as something that citizens deserve access to.” Helen Dixon, Ireland’s data protection commissioner, presents a European perspective, arguing that giving individuals control over their own data—as the General Data Protection Regulation, the EU’s historic new regulatory effort, aims to do—is essential to restoring the Internet’s promise. And Karen Kornbluh, a veteran U.S. policymaker, describes how the United States dropped the digital ball and what it could do to pick it up again.

Finally, Michèle Flournoy and Michael Sulmeyer explain the new realities of cyberwarfare, and Viktor Mayer-Schönberger and Thomas Ramge consider the problems caused by Big Tech’s hoarding of data and what can be done to address it.

A generation from now, people across the globe will no doubt revel in the benefits the Internet has brought. But the more thoughtful among them will also lament the eclipse of the founders’ idealistic vision and dream of a world connected the way it could—and should— have been….(More)”.

The Risks of Dangerous Dashboards in Basic Education

Curated on August 16, 2018 by Stefaan Verhulst

Lant Pritchett at the Center for Global Development: “On June 1, 2009 Air France flight 447 from Rio de Janeiro to Paris crashed into the Atlantic Ocean killing all 228 people on board. While the Airbus 330 was flying on auto-pilot, the different speed indicators received by the on-board navigation computers started to give conflicting speeds, almost certainly because the pitot tubes responsible for measuring air speed had iced over. Since the auto-pilot could not resolve conflicting signals and hence did not know how fast the plane was actually going, it turned control of the plane over to the two first officers (the captain was out of the cockpit). Subsequent flight simulator trials replicating the conditions of the flight conclude that had the pilots done nothing at all everyone would have lived—nothing was actually wrong; only the indicators were faulty, not the actual speed. But, tragically, the pilots didn’t do nothing….

What is the connection to education?

Many countries’ systems of basic education are in “stall” condition.

A recent paper of Beatty et al. (2018) uses information from the Indonesia Family Life Survey, a representative household survey that has been carried out in several waves with the same individuals since 2000 and contains information on whether individuals can answer simple arithmetic questions. Figure 1, showing the relationship between the level of schooling and the probability of answering a typical question correctly, has two shocking results.

First, the difference in the likelihood a person can answer a simple mathematics question correctly differs by only 20 percent between individuals who have completed less than primary school (<PS)—who can answer correctly (adjusted for guessing) about 20 percent of the time—and those who have completed senior secondary school or more (>=SSS), who answer correctly only about 40 percent of the time. These are simple multiple choice questions like whether 56/84 is the same fraction as (can be reduced to) 2/3, and whether 1/3-1/6 equals 1/6. This means that in an entire year of schooling, less than 2 additional children per 100 gain the ability to answer simple arithmetic questions.

Second, this incredibly poor performance in 2000 got worse by 2014. …

What has this got to do with education dashboards? The way large bureaucracies prefer to work is to specify process compliance and inputs and then measure those as a means of driving performance. This logistical mode of managing an organization works best when both process compliance and inputs are easily “observable” in the economist’s sense of easily verifiable, contractible, adjudicated. This leads to attention to processes and inputs that are “thin” in the Clifford Geertz sense (adopted by James Scott as his primary definition of how a “high modern” bureaucracy and hence the state “sees” the world). So in education one would specify easily-observable inputs like textbook availability, class size, school infrastructure. Even if one were talking about “quality” of schooling, a large bureaucracy would want this too reduced to “thin” indicators, like the fraction of teachers with a given type of formal degree, or process compliance measures, like whether teachers were hired based on some formal assessment.

Those involved in schooling can then become obsessed with their dashboards and the “thin” progress that is being tracked and easily ignore the loud warning signals saying: Stall!…(More)”.

As democracy goes digital, those offline are being pushed out of politics

Curated on August 16, 2018May 29, 2019 by Stefaan Verhulst

Renata Avila at the Web Foundation: “Free and fair elections require an informed, active body of citizens debating the electoral issues of the day and scrutinising the positions of candidates. Participation at each and every stage of an electoral campaign — not just on the day of the vote — is necessary for a healthy democracy.

Those online have access to an increasingly sophisticated set of tools to do just this: to learn about candidates, to participate in political discussions, to shape debate and raise issues that matter to them. Or even, run for office themselves.

What does this mean for those citizens who don’t have access to the internet? Do online debates capture their needs, concerns and interests? Are the priorities of those not connected represented on the political stage?

The Mexican election: a story of digital inequality

María de Jesús “Marichuy” Patricio Martinez was selected as an independent candidate in Mexico’s recent July 1 elections general election — the first indigenous woman to run for president. But digital barriers doomed her candidacy.

Independent presidential candidates in Mexico are required to collect 866,000 signatures using a mandatory mobile app that only runs on relatively new smartphones. This means that to collect the required endorsements, a candidate and their supporters all need a modern smartphone — which typically costs around three times the minimum monthly salary — plus electricity and mobile data. These are resources many people in indigenous communities simply don’t have. While the electoral authorities exempted some municipalities from this process, it did not cover the mostly poor and indigenous areas that Marichuy wanted to represent. She was unable to gather the signatures needed….(More)”.