We Need to Take Back Our Privacy


Zeynep Tufekci in The New York Times: “…Congress, and states, should restrict or ban the collection of many types of data, especially those used solely for tracking, and limit how long data can be retained for necessary functions — like getting directions on a phone.

Selling, trading and merging personal data should be restricted or outlawed. Law enforcement could obtain it subject to specific judicial oversight.

Researchers have been inventing privacy-preserving methods for analyzing data sets when merging them is in the public interest but the underlying data is sensitive — as when health officials are tracking a disease outbreak and want to merge data from multiple hospitals. These techniques allow computation but make it hard, if not impossible, to identify individual records. Companies are unlikely to invest in such methods, or use end-to-end encryption as appropriate to protect user data, if they could continue doing whatever they want. Regulation could make these advancements good business opportunities, and spur innovation.

I don’t think people like things the way they are. When Apple changed a default option from “track me” to “do not track me” on its phones, few people chose to be tracked. And many who accept tracking probably don’t realize how much privacy they’re giving up, and what this kind of data can reveal. Many location collectors get their data from ordinary apps — could be weather, games, or anything else — that often bury that they will share the data with others in vague terms deep in their fine print.

Under these conditions, requiring people to click “I accept” to lengthy legalese for access to functions that have become integral to modern life is a masquerade, not informed consent.

Many politicians have been reluctant to act. The tech industry is generous, cozy with power, and politicians themselves use data analysis for their campaigns. This is all the more reason to press them to move forward…(More)”.

Everyday Data Cultures


Book by Jean Burgess, Kath Albury, Anthony McCosker, and Rowan Wilken: “The AI revolution can seem powerful and unstoppable, extracting data from every aspect of our lives and subjecting us to unprecedented surveillance and control. But at ground level, even the most advanced ‘smart’ technologies are not as all-powerful as either the tech companies or their critics would have us believe.

From gig worker activism to wellness tracking with sex toys and TikTokers’ manipulation of the algorithm, this book shows how ordinary people are negotiating the datafication of society. The book establishes a new theoretical framework for understanding everyday experiences of data and automation, and offers guidance on the ethical responsibilities we share as we learn to live together with data-driven machines…(More)”.

State of Open Data Policy Repository


The GovLab: “To accompany its State of Open Data Policy Summit, the Open Data Policy Lab announced the release of a new resource to assess recent policy developments surrounding open data, data reuse, and data collaboration around the world: State of Open Data Repository of Recent Developments.

This document examines recent legislation, directives, and proposals that affect open data and data collaboration. Its goal is to capture signals of concerns, direction and leadership as to determine what stakeholders may focus on in the future. The review currently surfaced approximately 50 examples of recent legislative acts, proposals, directives, and other policy documents, from which the Open Data Policy Lab draws findings about the need to promote more innovative policy frameworks.

This collection demonstrates that, while there is growing interest in open data and data collaboration, policy development still remains nascent and focused on open data repositories at the expense of other collaborative arrangements. As we indicated in our report on the Third Wave of Open Data, there is an urgent need for governance frameworks at the local, regional, and national level to facilitate responsible reuse…(More)”.

Digital Self-Determination as a Tool for Migrant Empowerment


Blog by Uma Kalkar, Marine Ragnet, and Stefaan Verhulst: “In 2020, there were an estimated 281 million migrants, accounting for 3.6% of the global population. Migrants move for a variety of reasons: some are forced to flee from unsafe situations caused by conflict or climate change, others voluntarily move in search of new opportunities. People on the move bring along a wealth of new data. This information creates new opportunities for data collection, use, and reuse across the migration process and by a variety of public, private, and humanitarian sectors. Increased access and use of data for migration need to be accompanied by increased agency and the empowerment of the data subjects — a concept called “digital self-determination” (DSD).

The Big Data for Migration Alliance (BD4M) is a multisectoral initiative driven by the IOM’s Global Migration Data Analysis Centre (IOM-GMDAC), the European Commission’s Knowledge Centre on Migration and Demography (KCMD), and The GovLab at New York University. Realizing the need for a paradigm change for data in migration policy, the BD4M and International Network on Digital Self-Determination (IDSD) hosted the first studio as part of its Digital Self-Determination Studio Series

Although DSD is a relatively new concept, its roots stem from philosophy, psychology and human rights jurisprudence. Broadly speaking, DSD affirms that a person’s data is an extension of themselves in cyberspace, and we therefore need to consider how to provide a certain level of autonomy and agency to individuals or communities over their digital self. The first studio sought to deconstruct this concept within the context of migration and migrants. Below we list some of the main takeaways from the studio discussions.

Takeaway #1: DSD is in essence about the power asymmetries between migrants, states, and relevant organizations. Specifically, conversations around DSD centered around “power” and “control” — there is an asymmetry between the migrant and the state or organization they interact with to move within and across borders. These imbalances center around agency (a lack of autonomy over data collection, data consciousness, and data use); choice (in who, how, and where data are used, a lack of transparency over these decisions, and power and control issues faced when seeking to access national or social rights); and participation (who gets to formulate questions and access the data?).

  • Studio participants brought up how structural requirements force migrants to be open about their data; noted the opacity around how data is sourced from migrants; and raised concerns about agency, data literacy, and advocacy across the migrant process.
  • The various hierarchies of power, and how it relates to DSD for migrants, highlighted the discrepancies in power between migrants, the state, private companies, and even NGOs.
  • Information architecture and information asymmetries are some of the central aspects to consider to achieve DSD, suggesting that DSD may relate directly to who is telling the story during a crisis and who has the power to add insights to the narratives being developed. A responsible DSD framework will hinge on the voices of migrants.
  • The right to “data consciousness” was also raised to ensure that vulnerable individuals and groups are aware of when, where, and how data are collected, processed, and stored. Nurturing this awareness helps breed agency around personal data.
Representation of power asymmetries faced by migrants in achieving their DSD.

Takeaway #2: There is a need to understand the dual meaning of DSD.

Takeaway #3: There is a need to engage migrants in needs and expectations.

Takeaway #4: A taxonomy of DSD for the various migration-related steps can support creating effective tools to protect migrants along their journey...

Takeaway #5: DSD can be achieved through policy, technology, and process innovations.

Takeaway #6: DSD opportunities need to be determined across the data life cycle….(More)”.

The Frontlines of Artificial Intelligence Ethics


Book edited by Andrew J. Hampton, and Jeanine A. DeFalco: “This foundational text examines the intersection of AI, psychology, and ethics, laying the groundwork for the importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training.

AI already affects our lives profoundly, in ways both mundane and sensational, obvious and opaque. Much academic and industrial effort has considered the implications of this AI revolution from technical and economic perspectives, but the more personal, humanistic impact of these changes has often been relegated to anecdotal evidence in service to a broader frame of reference. Offering a unique perspective on the emerging social relationships between people and AI agents and systems, Hampton and DeFalco present cutting-edge research from leading academics, professionals, and policy standards advocates on the psychological impact of the AI revolution. Structured into three parts, the book explores the history of data science, technology in education, and combatting machine learning bias, as well as future directions for the emerging field, bringing the research into the active consideration of those in positions of authority.

Exploring how AI can support expert, creative, and ethical decision making in both people and virtual human agents, this is essential reading for students, researchers, and professionals in AI, psychology, ethics, engineering education, and leadership, particularly military leadership…(More)”.

Mobile phone data reveal the effects of violence on internal displacement in Afghanistan


Paper by Nearly 50 million people globally have been internally displaced due to conflict, persecution and human rights violations. However, the study of internally displaced persons—and the design of policies to assist them—is complicated by the fact that these people are often underrepresented in surveys and official statistics. We develop an approach to measure the impact of violence on internal displacement using anonymized high-frequency mobile phone data. We use this approach to quantify the short- and long-term impacts of violence on internal displacement in Afghanistan, a country that has experienced decades of conflict. Our results highlight how displacement depends on the nature of violence. High-casualty events, and violence involving the Islamic State, cause the most displacement. Provincial capitals act as magnets for people fleeing violence in outlying areas. Our work illustrates the potential for non-traditional data sources to facilitate research and policymaking in conflict settings….(More)”.

Automating the Analysis of Online Deliberation? Comparing computational analyses of polarized discussions on climate change to established content analysis


Paper by Lisa Oswald: “High­-quality discussions can help people acquire an adequate understanding of issues and alleviate mechanisms of opinion polarization. However, the extent to which the quality of the online public discourse contributes is contested. Facing the importance and the sheer volume of online discussions, reliable computational approaches to assess the deliberative quality of online discussions at scale would open a new era of deliberation research. But is it possible to automate the assessment of deliberative quality? I compare structural features of discussion threads and sim­ple text­-based measures to established manual content analysis by applying all measures to online discussions on ‘Reddit’ that deal with the 2020 wildfires in Australia and California. I further com­ pare discussions between two ideologically opposite online communities, one featuring discussions in line with the scientific consensus and one featuring climate change skepticism. While no single computational measure can capture the multidimensional concept of deliberative quality, I find that (1) measures of structural complexity capture engagement and participation as preconditions for deliberation, (2) the length of comments is correlated with manual measures of argumentation, and (3) automated toxicity scores are correlated with manual measures of respect. While the presented computational approaches cannot replace in­depth content coding, the findings imply that selected automated measures can be useful, scalable additions to the measurement repertoire for specific dimensions of online deliberation. I discuss implications for communication research and platform regulation and suggest interdisciplinary research to synthesize past content coding efforts using machine learning….(More)”.

GDPR and the Lost Generation of Innovative Apps


Paper by Rebecca Janßen, Reinhold Kesler, Michael E. Kummer & Joel Waldfogel: “Using data on 4.1 million apps at the Google Play Store from 2016 to 2019, we document that GDPR induced the exit of about a third of available apps; and in the quarters following implementation, entry of new apps fell by half. We estimate a structural model of demand and entry in the app market. Comparing long-run equilibria with and without GDPR, we find that GDPR reduces consumer surplus and aggregate app usage by about a third. Whatever the privacy benefits of GDPR, they come at substantial costs in foregone innovation…(More)”.

Behavioral Jurisprudence: Law Needs a Behavioral Revolution


Article by Benjamin van Rooij and Adam Fine: “Laws are supposed to protect us. At work, they should eliminate unsafe working conditions and harassment. On our streets, they should curb speeding, distracted driving, and driving under the influence. And throughout our countries, they should protect citizens against their own governments.

The law is the most important behavioral system we have. Yet it is designed and operated by behavioral novices. Lawyers draft legislation, interpret rules, and create policies, but legal training does not teach them how laws affect human and organizational behavior.

Law needs a behavioral revolution, like the one that rocked the field of economics. There is now a large body of empirical work that calls into question the traditional legal assumptions about how law shapes behavior. This empirical work also offers a path forward. It can help lawyers and others shaping the law understand the law’s behavioral impact and help align its intended influence on behavior to its actual effects.

For instance, the law has traditionally focused on punishment as a means to deal with harmful behavior. Yet there is no conclusive evidence that threats of incarceration or fines reduce misconduct. Most people do not understand or know the law, and thus never come to weigh the law’s incentives in deciding whether to comply with it.

The law also fails to account for the social and moral factors that affect how people interpret and follow it. For instance, social norms—what people see others do or think others hold they should do—can shape what we think the laws say. Research also shows that people are more likely to follow rules they deem legitimate, and that rules that are made and enforced in a procedurally just and fair manner enhance compliance.

And, traditionally, the law has focused on motivational aspects of wrongdoing. But behavioral responses to the law are highly situational. Here, work in criminology, particularly within environmental criminology, shows that criminal opportunities are a chief driver of criminal behavior. Relatedly, when people have their needs met, for instance when they have a livable wage or sufficient schooling, they are more likely to follow the law…(More)”.

How Secure Is Our Data, Really?


Essay by Michael Kende: “Stepping back, a 2019 study showed that 95 percent of such data breaches could have been prevented. There are two main causes of breaches that can be averted.

First, many breaches attack known vulnerabilities in online systems. We are all used to updating the operating system on our computer or phone. One of the reasons is to patch a defect that could allow a breach. But not all of us update each patch all of the time, and that leaves us exposed. Organizations operating hundreds or thousands of devices with different systems connecting them may not devote enough resources to security or may be worried about testing the compatibility of upgrades, and this leaves them exposed to hackers searching for systems that have not been updated. These challenges were exacerbated with employees working from home during pandemic restrictions, often on their own devices with less protected networks.

Second is the phenomenon known as social engineering in which an employee is tricked into providing their password. We have all received phishing emails asking us to log into a familiar site to address an urgent matter. Doing so allows the hacker to capture the user’s email address or user name and the associated password. The hacker can then use that information directly to enter the real version of the website or may find out where else the user may go and hope they use the same login details — which, human nature being what it is, is quite common. These phishing attacks highlight the asymmetric advantage held by the hackers. They can send out millions of emails and just need one person to click on the wrong link to start their attack.

Of course, if 95 percent of breaches are preventable, that means 5 percent are not. For instance, though many breaches result from known vulnerabilities in systems, a vulnerability is by definition unknown before it is discovered. Such a vulnerability, known as zero-day vulnerability, is valuable for hackers because it cannot be defended against, and they are often hoarded or sold, sometimes back to the company responsible so they can create a patch…(More)”.