Stefaan Verhulst
Paper by Sarah Giest: “Nudging is seen to complement or replace existing policy tools by altering people’s choice architectures towards behaviors that align with government aims, but has fallen short in meeting those targets. Crucially, governments do not nudge citizens directly, but need private agents to nudge their consumers. Based on this notion, the paper takes on an institutional approach towards nudging. Rather than looking at the relationship between nudger and nudgee, the research analyses the regulatory and market structures that affect nudge implementation by private actors, captured by the ‘budge’ idea. Focusing on the European energy policy domain, the paper analyses the contextual factors of green nudges that are initiated by Member States, and implemented by energy companies. The findings show that in the smart meter context, there are regulatory measures that affect implementation of smart meters and that government has a central role to ‘budge’, due to the dependence on private agents….(More)”.
James Brian Byrd, Anna C. Greene, Deepashree Venkatesh Prasad, Xiaoqian Jiang & Casey S. Greene in Nature: “Data sharing anchors reproducible science, but expectations and best practices are often nebulous. Communities of funders, researchers and publishers continue to grapple with what should be required or encouraged. To illuminate the rationales for sharing data, the technical challenges and the social and cultural challenges, we consider the stakeholders in the scientific enterprise. In biomedical research, participants are key among those stakeholders. Ethical sharing requires considering both the value of research efforts and the privacy costs for participants. We discuss current best practices for various types of genomic data, as well as opportunities to promote ethical data sharing that accelerates science by aligning incentives….(More)”.
UNDP: “Since the COVID-19 pandemic arrived in Mexico, multiple citizen responses[1] have emerged to tackle its impacts: digital aid platforms such as Frena la Curva (Stop the curve) and México Covid19; groups of makers that design medical and protective equipment; Zapotec indigenous women that teach how to make hand sanitizer at home; public buses that turn into mobile markets; and much more.
There are initiatives that aid 10, 20, 3,000 or more people; initiatives that operate inside a housing unit, a municipality or across the City. Some responses have come from civil society organizations; others from collectives of practitioners or from groups of friends and family; there are even those made out of groups of strangers that the pandemic turned into partners working for the same goal….
Within the plurality of initiatives that have emerged, sometimes, seemingly in a spontaneous way, there is a common denominator: people are reacting in a collaboratively way to the crisis to solve the needs that the pandemic is leaving behind.
Different research studies connect social cohesion and social capital with the response’s capacity of a community in situations of crisis and natural disasters; and with its subsequent recovery. These concepts —derived from sociology— include aspects such as the level of union; relationships and networks; and interaction between people in a community.
This can be seen when, for example, a group of people in a neighborhood gets together to buy groceries for neighbors who have lost their incomes. Also, when a collective of professionals react to the shortages of protective equipment for health workers by creating low-cost prototypes, or when a civil organization collaborates with local authorities to bring water to households that lack access to clean water.
It would seem that a high rate of social capital and social cohesion might ease the rise of the citizen initiatives that aim to tackle the challenges that ensue from the pandemic. These do not come out of nowhere….(More)”.
Book by Ronald Niezen: “Social justice and human rights movements are entering a new phase. Social media, artificial intelligence, and digital forensics are reshaping advocacy and compliance. Technicians, lawmakers, and advocates, sometimes in collaboration with the private sector, have increasingly gravitated toward the possibilities and dangers inherent in the nonhuman. #HumanRights examines how new technologies interact with older models of rights claiming and communication, influencing and reshaping the modern-day pursuit of justice.
Ronald Niezen argues that the impacts of information technologies on human rights are not found through an exclusive focus on sophisticated, expert-driven forms of data management but in considering how these technologies are interacting with other, “traditional” forms of media to produce new avenues of expression, public sympathy, redress of grievances, and sources of the self. Niezen considers various ways that the pursuit of justice is happening via new technologies, including crowdsourcing, social media–facilitated mobilizations (and enclosures), WhatsApp activist networks, and the selective attention of Google’s search engine algorithm. He uncovers how emerging technologies of data management and social media influence the ways that human rights claimants and their allies pursue justice, and the “new victimology” that prioritizes and represents strategic lives and types of violence over others. #HumanRights paints a striking and important panoramic picture of the contest between authoritarianism and the new tools by which people attempt to leverage human rights and bring the powerful to account….(More)”.
Paper by Stefan Sauermann et al: “This paper provides insight into how restricted data can be incorporated in an open-be-default-by-design digital infrastructure for scientific data. We focus, in particular, on the ethical component of FAIRER (Findable, Accessible, Interoperable, Ethical, and Reproducible) data, and the pseudo-anonymization and anonymization of COVID-19 datasets to protect personally identifiable information (PII). First we consider the need for the customisation of the existing privacy preservation techniques in the context of rapid production, integration, sharing and analysis of COVID-19 data. Second, the methods for the pseudo-anonymization of direct identification variables are discussed. We also discuss different pseudo-IDs of the same person for multi-domain and multi-organization. Essentially, pseudo-anonymization and its encrypted domain specific IDs are used to successfully match data later, if required and permitted, as well as to restore the true ID (and authenticity) in individual cases of a patient’s clarification.Third, we discuss application of statistical disclosure control (SDC) techniques to COVID-19 disease data. To assess and limit the risk of re-identification of individual persons in COVID-19 datasets (that are often enriched with other covariates like age, gender, nationality, etc.) to acceptable levels, the risk of successful re-identification by a combination of attribute values must be assessed and controlled. This is done using statistical disclosure control for anonymization of data. Lastly, we discuss the limitations of the proposed techniques and provide general guidelines on using disclosure risks to decide on appropriate modes for data sharing to preserve the privacy of the individuals in the datasets….(More)”.
Paper by Alasdair S. Roberts: “The first two decades of this century have shown there is no simple formula for governing well. Leaders must make difficult choices about national priorities and the broad lines of policy – that is, about the substance of their strategy for governing. These strategic choices have important implications for public administration. Scholars in this field should study the processes by which strategy is formulated and executed more closely than they have over the last thirty years. A new agenda for public administration should emphasize processes of top-level decision-making, mechanisms to improve foresight and the management of societal risks, and problems of large-scale reorganization and inter-governmental coordination, among other topics. Many of these themes have been examined more closely by researchers in Canada than by those abroad. This difference should be recognized an advantage rather than a liability….(More)”.
Ryan Panchadsaramarchive at MIT Technology Review: “…When the Trump administration stripped the Centers for Disease Control and Prevention (CDC) of control over coronavirus data, it also took that information away from the public….
This is also an opportunity for HHS to make this data machine readable and thereby more accessible to data scientists and data journalists. The Open Government Data Act, signed into law by President Trump, treats data as a strategic asset and makes it open by default. This act builds upon the Open Data Executive Order, which recognized that the data sets collected by the government are paid for by taxpayers and must be made available to them.
As a country, the United States has lagged behind in so many dimensions of response to this crisis, from the availability of PPE to testing to statewide mask orders. Its treatment of data has lagged as well. On March 7, as this crisis was unfolding, there was no national testing data. Alexis Madrigal, Jeff Hammerbacher, and a group of volunteers started the COVID Tracking Project to aggregate coronavirus information from all 50 state websites into a single Google spreadsheet. For two months, until the CDC began to share data through its own dashboard, this volunteer project was the sole national public source of information on cases and testing.
With more than 150 volunteers contributing to the effort, the COVID Tracking Project sets the bar for how to treat data as an asset. I serve on the advisory board and am awed by what this group has accomplished. With daily updates, an API, and multiple download formats, they’ve made their data extraordinarily useful. Where the CDC’s data is cited 30 times in Google Scholar and approximately 10,000 times in Google search results, the COVID Tracking Project data is cited 299 times in Google Scholar and roughly 2 million times in Google search results.
Sharing reliable data is one of the most economical and effective interventions the United States has to confront this pandemic. With the Coronavirus Task Force daily briefings a thing of the past, it’s more necessary than ever for all covid-related data to be shared with the public. The effort required to defeat the pandemic is not just a federal response. It is a federal, state, local, and community response. Everyone needs to work from the same trusted source of facts about the situation on the ground. Data is not a partisan affair or a bureaucratic preserve. It is a public trust—and a public resource….(More)”.
Indigenous Protocol and Artificial Intelligence Working Group: “This position paper on Indigenous Protocol (IP) and Artificial Intelligence (AI) is a starting place for those who want to design and create AI from an ethical position that centers Indigenous concerns. Each Indigenous community will have its own particular approach to the questions we raise in what follows. What we have written here is not a substitute for establishing and maintaining relationships of reciprocal care and support with specific Indigenous communities. Rather, this document offers a range of ideas to take into consideration when entering into conversations which prioritize Indigenous perspectives in the development of artificial intelligence.
The position paper is an attempt to capture multiple layers of a discussion that happened over 20 months, across 20 time zones, during two workshops, and between Indigenous people (and a few non-Indigenous folks) from diverse communities in Aotearoa, Australia, North America, and the Pacific.
Our aim, however, is not to provide a unified voice. Indigenous ways of knowing are rooted in distinct, sovereign territories across the planet. These extremely diverse landscapes and histories have influenced different communities and their discrete cultural protocols over time. A single ‘Indigenous perspective’ does not exist, as epistemologies are motivated and shaped by the grounding of specific communities in particular territories. Historically, scholarly traditions that homogenize diverse Indigenous cultural practices have resulted in ontological and epistemological violence, and a flattening of the rich texture and variability of Indigenous thought….(More)”.
Paper by Tamar Sharon: “Since the outbreak of COVID-19, governments have turned their attention to digital contact tracing. In many countries, public debate has focused on the risks this technology poses to privacy, with advocates and experts sounding alarm bells about surveillance and mission creep reminiscent of the post 9/11 era. Yet, when Apple and Google launched their contact tracing API in April 2020, some of the world’s leading privacy experts applauded this initiative for its privacy-preserving technical specifications. In an interesting twist, the tech giants came to be portrayed as greater champions of privacy than some democratic governments.
This article proposes to view the Apple/Google API in terms of a broader phenomenon whereby tech corporations are encroaching into ever new spheres of social life. From this perspective, the (legitimate) advantage these actors have accrued in the sphere of the production of digital goods provides them with (illegitimate) access to the spheres of health and medicine, and more worrisome, to the sphere of politics. These sphere transgressions raise numerous risks that are not captured by the focus on privacy harms. Namely, a crowding out of essential spherical expertise, new dependencies on corporate actors for the delivery of essential, public goods, the shaping of (global) public policy by non-representative, private actors and ultimately, the accumulation of decision-making power across multiple spheres. While privacy is certainly an important value, its centrality in the debate on digital contact tracing may blind us to these broader societal harms and unwittingly pave the way for ever more sphere transgressions….(More)”.
Essay by Martin Tisné: “On March 17, 2018, questions about data privacy exploded with the scandal of the previously unknown consulting company Cambridge Analytica. Lawmakers are still grappling with updating laws to counter the harms of big data and AI. In the Spring of 2020, the Covid-19 pandemic brought questions about sufficient legal protections back to the public debate, with urgent warnings about the privacy implications of contact tracing apps. But the surveillance consequences of the pandemic’s aftermath are much bigger than any app: transport, education, health
systems and offices are being turned into vast surveillance networks. If we only consider individual trade-offs between privacy sacrifices and alleged health benefits, we will miss the point. The collective nature of big data means people are more impacted by other people’s data than by data about them. Like climate change, the threat is societal and personal.
In the era of big data and AI, people can suffer because of how the sum of individual data is analysed and sorted into groups by algorithms. Novel forms of collective data-driven harms are appearing as a result: online housing, job and credit ads discriminating on the basis of race and gender, women disqualified from jobs on the basis of gender and foreign actors targeting light-right groups, pulling them to the far-right.2 Our public debate, governments, and laws are ill-equipped to deal with these collective, as opposed to individual, harms….(More)”.