The CrowdLaw Catalog

Curated on Posted on by Stefaan Verhulst

The GovLab: “The CrowdLaw Catalog is a growing repository of 100 CrowdLaw cases from around the world. The goal of the catalog is to help those wishing to start new or improve existing CrowdLaw projects to learn from one another.

Examples are tagged and searchable by four criteria:

  1. Level – What level of government is involved? Search by National, Regional, and/or Local
  2. Stage – At what stage of the law or policymaking process the participation take place? Search by Problem Identification, Solution Identification, Drafting, Decision Making, Implementation and/or Assessment
  3. Task – What are people being asked to contribute? Search by: Ideas, Expertise, Opinions, Evidence and/or Actions.
  4. Technology – What is the platform? Search by: Web, Mobile and/or Offline

The catalog offers brief descriptions of each initiative and links to additional resources….(More)”.

Health Insurers Are Vacuuming Up Details About You — And It Could Raise Your Rates

Curated on Posted on by Stefaan Verhulst

Marshall Allen at ProPublica: “With little public scrutiny, the health insurance industry has joined forces with data brokers to vacuum up personal details about hundreds of millions of Americans, including, odds are, many readers of this story. The companies are tracking your race, education level, TV habits, marital status, net worth. They’re collecting what you post on social media, whether you’re behind on your bills, what you order online. Then they feed this information into complicated computer algorithms that spit out predictions about how much your health care could cost them.

Are you a woman who recently changed your name? You could be newly married and have a pricey pregnancy pending. Or maybe you’re stressed and anxious from a recent divorce. That, too, the computer models predict, may run up your medical bills.

Are you a woman who’s purchased plus-size clothing? You’re considered at risk of depression. Mental health care can be expensive.

Low-income and a minority? That means, the data brokers say, you are more likely to live in a dilapidated and dangerous neighborhood, increasing your health risks.

“We sit on oceans of data,” said Eric McCulley, director of strategic solutions for LexisNexis Risk Solutions, during a conversation at the data firm’s booth. And he isn’t apologetic about using it. “The fact is, our data is in the public domain,” he said. “We didn’t put it out there.”

Insurers contend they use the information to spot health issues in their clients — and flag them so they get services they need. And companies like LexisNexis say the data shouldn’t be used to set prices. But as a research scientist from one company told me: “I can’t say it hasn’t happened.”

At a time when every week brings a new privacy scandal and worries abound about the misuse of personal information, patient advocates and privacy scholars say the insurance industry’s data gathering runs counter to its touted, and federally required, allegiance to patients’ medical privacy. The Health Insurance Portability and Accountability Act, or HIPAA, only protects medical information.

“We have a health privacy machine that’s in crisis,” said Frank Pasquale, a professor at the University of Maryland Carey School of Law who specializes in issues related to machine learning and algorithms. “We have a law that only covers one source of health information. They are rapidly developing another source.”…(More)”.

How Charities Are Using Artificial Intelligence to Boost Impact

Curated on Posted on by Stefaan Verhulst

Nicole Wallace at the Chronicle of Philanthropy: “The chaos and confusion of conflict often separate family members fleeing for safety. The nonprofit Refunite uses advanced technology to help loved ones reconnect, sometimes across continents and after years of separation.

Refugees register with the service by providing basic information — their name, age, birthplace, clan and subclan, and so forth — along with similar facts about the people they’re trying to find. Powerful algorithms search for possible matches among the more than 1.1 million individuals in the Refunite system. The analytics are further refined using the more than 2,000 searches that the refugees themselves do daily.

The goal: find loved ones or those connected to them who might help in the hunt. Since Refunite introduced the first version of the system in 2010, it has helped more than 40,000 people reconnect.

One factor complicating the work: Cultures define family lineage differently. Refunite co-founder Christopher Mikkelsen confronted this problem when he asked a boy in a refugee camp if he knew where his mother was. “He asked me, ‘Well, what mother do you mean?’ ” Mikkelsen remembers. “And I went, ‘Uh-huh, this is going to be challenging.’ ”

Fortunately, artificial intelligence is well suited to learn and recognize different family patterns. But the technology struggles with some simple things like distinguishing the image of a chicken from that of a car. Mikkelsen believes refugees in camps could offset this weakness by tagging photographs — “car” or “not car” — to help train algorithms. Such work could earn them badly needed cash: The group hopes to set up a system that pays refugees for doing such work.

“To an American, earning $4 a day just isn’t viable as a living,” Mikkelsen says. “But to the global poor, getting an access point to earning this is revolutionizing.”

Another group, Wild Me, a nonprofit created by scientists and technologists, has created an open-source software platform that combines artificial intelligence and image recognition, to identify and track individual animals. Using the system, scientists can better estimate the number of endangered animals and follow them over large expanses without using invasive techniques….

To fight sex trafficking, police officers often go undercover and interact with people trying to buy sex online. Sadly, demand is high, and there are never enough officers.

Enter Seattle Against Slavery. The nonprofit’s tech-savvy volunteers created chatbots designed to disrupt sex trafficking significantly. Using input from trafficking survivors and law-enforcement agencies, the bots can conduct simultaneous conversations with hundreds of people, engaging them in multiple, drawn-out conversations, and arranging rendezvous that don’t materialize. The group hopes to frustrate buyers so much that they give up their hunt for sex online….

A Philadelphia charity is using machine learning to adapt its services to clients’ needs.

Benefits Data Trust helps people enroll for government-assistance programs like food stamps and Medicaid. Since 2005, the group has helped more than 650,000 people access $7 billion in aid.

The nonprofit has data-sharing agreements with jurisdictions to access more than 40 lists of people who likely qualify for government benefits but do not receive them. The charity contacts those who might be eligible and encourages them to call the Benefits Data Trust for help applying….(More)”.

Activism in the Social Media Age

Curated on Posted on by Stefaan Verhulst

PewInternet: “This month marks the fifth anniversary of the #BlackLivesMatter hashtag, which was first coined following the acquittal of George Zimmerman in the shooting death of unarmed black teenager Trayvon Martin. In the course of those five years, #BlackLivesMatter has become an archetypal example of modern protests and political engagement on social media: A new Pew Research Center analysis of public tweets finds the hashtag has been used nearly 30 million times on Twitter – an average of 17,002 times per day – as of May 1, 2018.

Use of the #BlackLivesMatter hashtag on Twitter periodically spikes in response to major news events

The conversations surrounding this hashtag often center on issues related to race, violence and law enforcement, and its usage periodically surges surrounding real-world events – most prominently, during the police-related deaths of Alton Sterling and Philando Castile and the subsequent shooting of police officers in Dallas, Texas, and Baton Rouge, Louisiana, in July 2016.1

The rise of the #BlackLivesMatter hashtag – along with others like #MeToo and #MAGA (Make America Great Again) – has sparked a broader discussion about the effectiveness and viability of using social media for political engagement and social activism. To that end, a new survey by the Center finds that majorities of Americans do believe these sites are very or somewhat important for accomplishing a range of political goals, such as getting politicians to pay attention to issues (69% of Americans feel these platforms are important for this purpose) or creating sustained movements for social change (67%).

Certain groups of social media users – most notably, those who are black or Hispanic – view these platforms as an especially important tool for their own political engagement. For example, roughly half of black social media users say these platforms are at least somewhat personally important to them as a venue for expressing their political views or for getting involved with issues that are important to them. Those shares fall to around a third among white social media users.2

At the same time, the public as a whole expresses mixed views about the potential broader impact these sites might be having on political discourse and the nature of political activism. Some 64% of Americans feel that the statement “social media help give a voice to underrepresented groups” describes these sites very or somewhat well. But a larger share say social networking sites distract people from issues that are truly important (77% feel this way), and 71% agree with the assertion that “social media makes people believe they’re making a difference when they really aren’t.” Blacks and whites alike offer somewhat mixed assessments of the benefits and costs of activism on social media. But larger majorities of black Americans say these sites promote important issues or give voice to underrepresented groups, while smaller shares of blacks feel that political engagement on social media produces significant downsides in the form of a distracted public or “slacktivism.”…(More)”.

Bad Governance and Corruption

Curated on Posted on by Stefaan Verhulst

Textbook by Richard Rose and Caryn Peiffer: “This book explains why the role of corruption varies greatly between public services, between people, between national systems of governance, and between measures of corruption.

More than 1.8 billion people pay the price of bad government each year, by sending a bribe to a public official.

In developing countries, corruption affects social services, such as health care and education, and law enforcement institutions, such as the police. When public officials do not act as bureaucrats delivering services by the book, people can try to get them by hook or by crook. The book’s analysis draws on unique evidence: a data base of sample surveys of 175,000 people in 125 countries in Africa, Asia, the Middle East, Europe, and North and South America. The authors avoid one-size-fits-all proposals for reform and instead provide measures that can be applied to particular public services to reduce or eliminate opportunities for corruption….(More)”.

Virtualization of government‐to‐citizen engagement process: Enablers and constraints

Curated on Posted on by Stefaan Verhulst

Paper by Joshua Ofoeda et al: “The purpose of this study is to investigate the factors that constrain or enable process virtualization in a government‐to‐citizen engagement process. Past research has established that most e‐government projects, especially in developing countries, are regarded as total failure or partial failure.

Citizens’ unwillingness to use government electronic services and lack of awareness are among some of the reasons why these electronic services fail.

Using the process virtualization theory (PVT) as theoretical lens, the authors investigated the various activities within the driver license acquisition process at the Driver and Vehicle Licensing Authority.

The PVT helped in identifying factors which enable or inhibit the virtualization of the driver license acquisition process in Ghana. Based on a survey data of 317 participants, we report that process characteristics in the form of relationship requirements affect citizens’ willingness toward the use of government virtualized processes. Situating the PVT within a developing country context, our findings reveal that some cultural and behavioral attributes such as socialization hinder the virtualization of some activities within the driver licensing process….(More)”.

Essentials of the Right of Access to Public Information: An Introduction

Curated on Posted on by Stefaan Verhulst

Introduction by Blanke, Hermann-Josef and Perlingeiro, Ricardo in the book “The Right of Access to Public Information : An International Comparative Legal Survey”: “The first freedom of information law was enacted in Sweden back in 1766 as the “Freedom of the Press and the Right of Access to Public Records Act”. It sets an example even today. However, the “triumph” of the freedom of information did not take place until much later. Many western legal systems arose from the American Freedom of Information Act, which was signed into law by President L.B. Johnson in 1966. This Act obliges all administrative authorities to provide information to citizens and imposes any necessary limitations. In an exemplary manner, it standardizes the objective of administrative control to protect citizens from government interference with their fundamental rights. Over 100 countries around the world have meanwhile implemented some form of freedom of information legislation. The importance of the right of access to information as an aspect of transparency and a condition for the rule of law and democracy is now also becoming apparent in international treaties at a regional level. This article provides an overview on the crucial elements and the guiding legal principles of transparency legislation, also by tracing back the lines of development of national and international case-law….(More)”.

Data Protection and e-Privacy: From Spam and Cookies to Big Data, Machine Learning and Profiling

Curated on Posted on by Stefaan Verhulst

Chapter by Lilian Edwards in L Edwards ed Law, Policy and the Internet (Hart , 2018): “In this chapter, I examine in detail how data subjects are tracked, profiled and targeted by their activities on line and, increasingly, in the “offline” world as well. Tracking is part of both commercial and state surveillance, but in this chapter I concentrate on the former. The European law relating to spam, cookies, online behavioural advertising (OBA), machine learning (ML) and the Internet of Things (IoT) is examined in detail, using both the GDPR and the forthcoming draft ePrivacy Regulation. The chapter concludes by examining both code and law solutions which might find a way forward to protect user privacy and still enable innovation, by looking to paradigms not based around consent, and less likely to rely on a “transparency fallacy”. Particular attention is drawn to the new work around Personal Data Containers (PDCs) and distributed ML analytics….(More)”.

On Preferring A to B, While Also Preferring B to A

Curated on Posted on by Stefaan Verhulst

Paper by Cass R. Sunstein: “In important contexts, people prefer option A to option B when they evaluate the two separately, but prefer option B to option A when they evaluate the two jointly. In consumer behavior, politics, and law, such preference reversals present serious puzzles about rationality and behavioral biases.

They are often a product of the pervasive problem of “evaluability.” Some important characteristics of options are difficult or impossible to assess in separate evaluation, and hence choosers disregard or downplay them; those characteristics are much easier to assess in joint evaluation, where they might be decisive. But in joint evaluation, certain characteristics of options may receive excessive weight, because they do not much affect people’s actual experience or because the particular contrast between joint options distorts people’s judgments. In joint as well as separate evaluation, people are subject to manipulation, though for different reasons.

It follows that neither mode of evaluation is reliable. The appropriate approach will vary depending on the goal of the task – increasing consumer welfare, preventing discrimination, achieving optimal deterrence, or something else. Under appropriate circumstances, global evaluation would be much better, but it is often not feasible. These conclusions bear on preference reversals in law and policy, where joint evaluation is often better, but where separate evaluation might ensure that certain characteristics or features of situations do not receive excessive weight…(More)”.

I want your (anonymized) social media data

Curated on Posted on by Stefaan Verhulst

Anthony Sanford at The Conversation: “Social media sites’ responses to the Facebook-Cambridge Analytica scandal and new European privacy regulations have given users much more control over who can access their data, and for what purposes. To me, as a social media user, these are positive developments: It’s scary to think what these platforms could do with the troves of data available about me. But as a researcher, increased restrictions on data sharing worry me.

I am among the many scholars who depend on data from social media to gain insights into people’s actions. In a rush to protect individuals’ privacy, I worry that an unintended casualty could be knowledge about human nature. My most recent work, for example, analyzes feelings people express on Twitter to explain why the stock market fluctuates so much over the course of a single day. There are applications well beyond finance. Other scholars have studied mass transit rider satisfaction, emergency alert systems’ function during natural disasters and how online interactions influence people’s desire to lead healthy lifestyles.

This poses a dilemma – not just for me personally, but for society as a whole. Most people don’t want social media platforms to share or sell their personal information, unless specifically authorized by the individual user. But as members of a collective society, it’s useful to understand the social forces at work influencing everyday life and long-term trends. Before the recent crises, Facebook and other companies had already been making it hard for legitimate researchers to use their data, including by making it more difficult and more expensive to download and access data for analysis. The renewed public pressure for privacy means it’s likely to get even tougher….

It’s true – and concerning – that some presumably unethical people have tried to use social media data for their own benefit. But the data are not the actual problem, and cutting researchers’ access to data is not the solution. Doing so would also deprive society of the benefits of social media analysis.

Fortunately, there is a way to resolve this dilemma. Anonymization of data can keep people’s individual privacy intact, while giving researchers access to collective data that can yield important insights.

There’s even a strong model for how to strike that balance efficiently: the U.S. Census Bureau. For decades, that government agency has collected extremely personal data from households all across the country: ages, employment status, income levels, Social Security numbers and political affiliations. The results it publishes are very rich, but also not traceable to any individual.

It often is technically possible to reverse anonymity protections on data, using multiple pieces of anonymized information to identify the person they all relate to. The Census Bureau takes steps to prevent this.

For instance, when members of the public access census data, the Census Bureau restricts information that is likely to identify specific individuals, such as reporting there is just one person in a community with a particularly high- or low-income level.

For researchers the process is somewhat different, but provides significant protections both in law and in practice. Scholars have to pass the Census Bureau’s vetting process to make sure they are legitimate, and must undergo training about what they can and cannot do with the data. The penalties for violating the rules include not only being barred from using census data in the future, but also civil fines and even criminal prosecution.

Even then, what researchers get comes without a name or Social Security number. Instead, the Census Bureau uses what it calls “protected identification keys,” a random number that replaces data that would allow researchers to identify individuals.

Each person’s data is labeled with his or her own identification key, allowing researchers to link information of different types. For instance, a researcher wanting to track how long it takes people to complete a college degree could follow individuals’ education levels over time, thanks to the identification keys.

Social media platforms could implement a similar anonymization process instead of increasing hurdles – and cost – to access their data…(More)” .