Stefaan Verhulst
Tobias Franke, Paul Lukowicz and Ulf Blanke at the Journal of Internet Services and Applications: “Pedestrian crowds are an integral part of cities. Planning for crowds, monitoring crowds and managing crowds, are fundamental tasks in city management. As a consequence, crowd management is a sprawling R&D area (see related work) that includes theoretical models, simulation tools, as well as various support systems. There has also been significant interest in using computer vision techniques to monitor crowds. However, overall, the topic of crowd management has been given only little attention within the smart city domain. In this paper we report on a platform for smart, city-wide crowd management based on a participatory mobile phone sensing platform. Originally, the apps based on this platform have been conceived as a technology validation tool for crowd based sensing within a basic research project. However, the initial deployments at the Notte Bianca Festival1 in Malta and at the Lord Mayor’s Show in London2 generated so much interest within the civil protection community that it has gradually evolved into a full-blown participatory crowd management system and is now in the process of being commercialized through a startup company. Until today it has been deployed at 14 events in three European countries (UK, Netherlands, Switzerland) and used by well over 100,000 people….
Obtaining knowledge about the current size and density of a crowd is one of the central aspects of crowd monitoring . For the last decades, automatic crowd monitoring in urban areas has mainly been performed by means of image processing . One use case for such video-based applications can be found in, where a CCTV camera-based system is presented that automatically alerts the staff of subway stations when the waiting platform is congested. However, one of the downsides of video-based crowd monitoring is the fact that video cameras tend to be considered as privacy invading. Therefore, presents a privacy preserving approach to video-based crowd monitoring where crowd sizes are estimated without people models or object tracking.
With respect to the mitigation of catastrophes induced by panicking crowds (e.g. during an evacuation), city planners and architects increasingly rely on tools simulating crowd behaviors in order to optimize infrastructures. Murakami et al. presents an agent based simulation for evacuation scenarios. Shendarkar et al. presents a work that is also based on BSI (believe, desire, intent) agents – those agents however are trained in a virtual reality environment thereby giving greater flexibility to the modeling. Kluepfel et al. on the other hand uses a cellular automaton model for the simulation of crowd movement and egress behavior.
With smartphones becoming everyday items, the concept of crowd sourcing information from users of mobile application has significantly gained traction. Roitman et al. presents a smart city system where the crowd can send eye witness reports thereby creating deeper insights for city officials. Szabo et al. takes this approach one step further and employs the sensors built into smartphones for gathering data for city services such as live transit information. Ghose et al. utilizes the same principle for gathering information on road conditions. Pan et al. uses a combination of crowd sourcing and social media analysis for identifying traffic anomalies….(More)”.
ShareAmerica: “A mosquito’s a mosquito, right? Not when it comes to Zika and other mosquito-borne diseases.
Only two of the estimated 3,000 species of mosquitoes are capable of carrying the Zika virus in the United States, but estimates of their precise range remain hazy, according to the U.S. Centers for Disease Control and Prevention.
Scientists could start getting better information about these pesky, but important, insects with the help of plastic cups, brown paper towels and teenage biology students.
As part of the Invasive Mosquito Project from the U.S. Department of Agriculture, secondary-school students nationwide are learning about mosquito populations and helping fill the knowledge gaps.
Simple experiment, complex problem
The experiment works like this: First, students line the cups with paper, then fill two-thirds of the cups with water. Students place the plastic cups outside, and after a week, the paper is dotted with what looks like specks of dirt. These dirt particles are actually mosquito eggs, which the students can identify and classify.
Students then upload their findings to a national crowdsourced database. Crowdsourcing uses the collective intelligence of online communities to “distribute” problem solving across a massive network.
Entomologist Lee Cohnstaedt of the U.S. Department of Agriculture coordinates the program, and he’s already thinking about expansion. He said he hopes to have one-fifth of U.S. schools participate in the mosquito species census. He also plans to adapt lesson plans for middle schools, Scouting troops and gardening clubs.
Already, crowdsourcing has “collected better data than we could have working alone,” he told the Associated Press….
In addition to mosquito tracking, crowdsourcing has been used to develop innovative responses to a number of complex challenges, from climate change to archaeologyto protein modeling….(More)”
Chapter by Roberto da Mota Ueti, Daniela Fernandez Espinosa, Laura Rafferty, Patrick C. K. Hung in Big Data Applications and Use Cases: “Big Data is changing our world with masses of information stored in huge servers spread across the planet. This new technology is changing not only companies but governments as well. Mexico and Brazil, two of the most influential countries in Latin America, are entering a new era and as a result, facing challenges in all aspects of public policy. Using Big Data, the Brazilian Government is trying to decrease spending and use public money better by grouping public information with stored information on citizens in public services. With new reforms in education, finances and telecommunications, the Mexican Government is taking on a bigger role in efforts to channel the country’s economic policy into an improvement of the quality of life of their habitants. It is known that technology is an important part for sub-developed countries, who are trying to make a difference in certain contexts such as reducing inequality or regulating the good usage of economic resources. The good use of Big Data, a new technology that is in charge of managing a big quantity of information, can be crucial for the Mexican Government to reach the goals that have been set in the past under Peña Nieto’s administration. This article focuses on how the Brazilian and Mexican Governments are managing the emerging technologies of Big Data and how it includes them in social and industrial projects to enhance the growth of their economies. The article also discusses the benefits of these uses of Big Data and the possible problems that occur related to security and privacy of information….(More)’
Special issue of Internet Policy Review: “Facing general conceptions of the power effects of big data, this thematic edition is interested in studies that scrutinise big data and power in concrete fields of application. It brings together scholars from different disciplines who analyse the fields agriculture, education, border control and consumer policy. As will be made explicit in the following, each of the articles tells us something about firstly, what big data is and how it relates to power. They secondly also shed light on how we should shape “the big data society” and what research questions need to be answered to be able to do so….
The ethics of big data in big agriculture
Isabelle M. Carbonell, University of California, Santa Cruz
Regulating “big data education” in Europe: lessons learned from the US
Yoni Har Carmel, University of Haifa
The borders, they are a-changin’! The emergence of socio-digital borders in the EU
Magdalena König, Maastricht University
Beyond consent: improving data protection through consumer protection law
Michiel Rhoen, Leiden University…
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Book edited by Mathis, Klaus and Tor, Avishalom: “This anthology provides an in-depth analysis and discusses the issues surrounding nudging and its use in legislation, regulation, and policy making more generally. The 17 essays in this anthology provide startling insights into the multifaceted debate surrounding the use of nudges in European Law and Economics.
Nudging is a tool aimed at altering people’s behaviour in a predictable way without forbidding any option or significantly changing economic incentives. It can be used to help people make better decisions to influence human behaviour without forcing them because they can opt out. Its use has sparked lively debates in academia as well as in the public sphere. This book explores who decides which behaviour is desired. It looks at whether or not the state has sufficient information for debiasing, and if there are clear-cut boundaries between paternalism, manipulation and indoctrination. The first part of this anthology discusses the foundations of nudging theory and the problems associated, as well as outlining possible solutions to the problems raised. The second part is devoted to the wide scope of applications of nudges from contract law, tax law and health claim regulations, among others.
This volume is a result of the flourishing annual Law and Economics Conference held at the law faculty of the University of Lucerne. The conferences have been instrumental in establishing a strong and ever-growing Law and Economics movement in Europe, providing unique insights in the challenges faced by Law and Economics when applied in European legal traditions….(More)”
Paper by Philipp Hacker and Bilyana Petkova: “The growing differentiation of services based on Big Data harbors the potential for both greater societal inequality and for greater equality. Anti-discrimination law and transparency alone, however, cannot do the job of curbing Big Data’s negative externalities while fostering its positive effects.
To rein in Big Data’s potential, we adapt regulatory strategies from behavioral economics, contracts and criminal law theory. Four instruments stand out: First, active choice may be mandated between data collecting services (paid by data) and data free services (paid by money). Our suggestion provides concrete estimates for the price range of a data free option, sheds new light on the monetization of data collecting services, and proposes an “inverse predatory pricing” instrument to limit excessive pricing of the data free option. Second, we propose using the doctrine of unconscionability to prevent contracts that unreasonably favor data collecting companies. Third, we suggest democratizing data collection by regular user surveys and data compliance officers partially elected by users. Finally, we trace back new Big Data personalization techniques to the old Hartian precept of treating like cases alike and different cases – differently. If it is true that a speeding ticket over $50 is less of a disutility for a millionaire than for a welfare recipient, the income and wealth-responsive fines powered by Big Data that we suggest offer a glimpse into the future of the mitigation of economic and legal inequality by personalized law. Throughout these different strategies, we show how salience of data collection can be coupled with attempts to prevent discrimination against and exploitation of users. Finally, we discuss all four proposals in the context of different test cases: social media, student education software and credit and cell phone markets.
Many more examples could and should be discussed. In the face of increasing unease about the asymmetry of power between Big Data collectors and dispersed users, about differential legal treatment, and about the unprecedented dimensions of economic inequality, this paper proposes a new regulatory framework and research agenda to put the powerful engine of Big Data to the benefit of both the individual and societies adhering to basic notions of equality and non-discrimination….(More)”
Asha Barbaschow at ZDNet: “Patients seeking urgent medical care in Perth can now view emergency waiting times for local hospitals, thanks to a new app developed in Australia.
The app, WA Emergency Waiting Times, uses existing Perth hospital emergency wait time data, and taps into mobile device geolocation, local maps, and traffic data to give people needing to go to the hospital in a non life-threatening emergency an aggregated travel and wait time.
The team behind the app, Sydney-based Readify, said the idea came in response to the concept of using open and cross-departmental data to benefit its citizens.
Readify said using government open data in smart ways was an initiative the government chief information officer (GCIO) Giles Nunis committed to previously, in a bid to demonstrate that innovation can greatly benefit the public without costing a fortune….(More)”
Mohit Kaushal and Margaret Darling at Brookings: “Forty-six million Americans use mobile fitness and health apps. Over half of providers serving Medicare or Medicaid patients are using electronic health records (EHRs). Despite such advances and proliferation of health data and its collection, we are not yet on an inevitable path to unleashing the often-promised “power of data” because data remain proprietary and fragmented among insurers, providers, health record companies, government agencies, and researchers.
Despite the technological integration seen in banking and other industries, health care data has remained scattered and inaccessible. EHRs remain fragmented among 861 distinct ambulatory vendors and 277 inpatient vendors as of 2013. Similarly, insurance claims are stored in the databases of insurers, and information about public health—including information about the social determinants of health, such as housing, food security, safety, and education—is often kept in databases belonging to various governmental agencies. These silos wouldn’t necessarily be a problem, except for the lack of interoperability that has long plagued the health care industry.
For this reason, many are reconsidering if health care data is a public good, provided to all members of the public without profit. This idea is not new. In fact, the Institute of Medicine established the Roundtable on Value and Science-Driven Healthcare, citing that:
“A significant challenge to progress resides in the barriers and restrictions that derive from the treatment of medical care data as a proprietary commodity by the organizations involved. Even clinical research and medical care data developed with public funds are often not available for broader analysis and insights. Broader access and use of healthcare data for new insights require not only fostering data system reliability and interoperability but also addressing the matter of individual data ownership and the extent to which data central to progress in health and health care should constitute a public good.”
Indeed, publicly available health care data holds the potential to unlock many innovations, much like what public goods have done in other industries. As publicly available weather data has shown, the public utility of open access information is not only good for consumers, itis good for businesses…(More)”
the Conversation: “Can a few text messages, a timely email or a letter increase college enrollment and student achievement? Such “nudges,” designed carefully using behavioral economics, can be effective.
But when do they work – and when not?
Barriers to success
Consider students who have just graduated high school intending to enroll in college. Even among those who have been accepted to college, 15 percent of low-income students do not enroll by the next fall. For the large share who intend to enroll in community colleges, this number can be as high as 40 percent….
Can a few text messages or a timely email overcome these barriers? My research uses behavioral economics to design low-cost, scalable interventions aimed at improving education outcomes. Behavioral economics suggests several important features to make a nudge effective: simplify complex information, make tasks easier to complete and ensure that support is timely.
So, what makes for an effective nudge?
Improving college enrollment
In 2012, researchers Ben Castleman and Lindsay Page sent 10 text messages to nearly 2,000 college-intending students the summer after high school graduation. These messages provided just-in-time reminders on key financial aid, housing and enrollment deadlines from early July to mid August.
Instead of set meetings with counselors, students could reply to messages and receive on-demand support from college guidance counselors to complete key tasks.
In another intervention – the Expanding College Opportunities Project (ECO) – researchers Caroline Hoxby and Sarah Turner worked to help high-achieving, low-income students enroll in colleges on par with their achievement. The intervention arrived to students as a packet in the mail.
The mailer simplified information by providing a list of colleges tailored to each student’s location along with information about net costs, graduation rates, and application deadlines. Moreover, the mailer included easy-to-claim application fee waivers. All these features reduced both the complexity and cost in applying to a wider range of colleges.
In both cases, researchers found that it significantly improved college outcomes. College enrollment went up by 15 percent in the intervention designed to reduce summer melt for community college students. The ECO project increased the likelihood of admission to a selective college by 78 percent.
…
When there is no impact
While these interventions are promising, there are important caveats.
For instance, our preliminary findings from ongoing research show that information alone may not be enough. We sent emails and letters to more than one hundred thousand college applicants about financial aid and education-related tax benefits. However, we didn’t provide any additional support to help families through the process of claiming these benefits.
In other words, we didn’t provide any support to complete the tasks – no fee waivers, no connection to guidance counselors – just the email and the letter. Without this support to answer questions or help families complete forms to claim the benefits, we found no impact, even when students opened the emails.
More generally, “nudges” often lead to modest impacts and should be considered only a part of the solution. But there’s a dearth of low-cost, scalable interventions in education, and behavioral economics can help.
Identifying the crucial decision points – when applications are due, forms need to be filled out or school choices are made – and supplying the just-in-time support to families is key….(More).”
Anne Milgram in the Atlantic: “…One area in which the potential of data analysis is still not adequately realized,however, is criminal justice. This is somewhat surprising given the success of CompStat, a law enforcement management tool that uses data to figure out how police resources can be used to reduce crime and hold law enforcement officials accountable for results. CompStat is widely credited with contributing to New York City’s dramatic reduction in serious crime over the past two decades. Yet data-driven decision-making has not expanded to the whole of the criminal justice system.
But it could. And, in this respect, the front end of the system — the part of the process that runs from arrest through sentencing — is particularly important. Atthis stage, police, prosecutors, defenders, and courts make key choices about how to deal with offenders — choices that, taken together, have an enormous impact on crime. Yet most jurisdictions do not collect or analyze the data necessary to know whether these decisions are being made in a way that accomplishes the most important goals of the criminal justice system: increased public safety,decreased recidivism, reduced cost, and the fair, efficient administration of justice.
Even in jurisdictions where good data exists, a lack of technology is often an obstacle to using it effectively. Police, jails, courts, district attorneys, and public defenders each keep separate information systems, the data from which is almost never pulled together and analyzed in a way that could answer the questions that matter most: Who is in our criminal justice system? What crimes have been charged? What risks do individual offenders pose? And which option would best protect the public and make the best use of our limited resources?
While debates about prison over-crowding, three strikes laws, and mandatory minimum sentences have captured public attention, the importance of what happens between arrest and sentencing has gone largely unnoticed. Even though I ran the criminal justice system in New Jersey, one of the largest states in the country, I had not realized the magnitude of the pretrial issues until I was tasked by theLaura and John Arnold Foundation with figuring out which aspects of criminal justice had the most need and presented the greatest opportunity for reform….
Technology could help us leverage data to identify offenders who will pose unacceptable risks to society if they are not behind bars and distinguish them from those defendants who will have lower recidivism rates if they are supervised in the community or given alternatives to incarceration before trial. Likewise, it could help us figure out which terms of imprisonment, alternatives to incarceration, and other interventions work best–and for whom. And the list does not end there.
The truth is our criminal justice system already makes these decisions every day.But it makes them without knowing whether they’re the right ones. That needs to change. If data is powerful enough to transform baseball, health care, and education, it can do the same for criminal justice….(More)”
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