Paper by Sara Vannini, Ricardo Gomez and Bryce Clayton Newell: “The forced displacement and transnational migration of millions of people around the world is a growing phenomenon that has been met with increased surveillance and datafication by a variety of actors. Small humanitarian organizations that help irregular migrants in the United States frequently do not have the resources or expertise to fully address the implications of collecting, storing, and using data about the vulnerable populations they serve. As a result, there is a risk that their work could exacerbate the vulnerabilities of the very same migrants they are trying to help. In this study, we propose a conceptual framework for protecting privacy in the context of humanitarian information activities (HIA) with irregular migrants. We draw from a review of the academic literature as well as interviews with individuals affiliated with several US‐based humanitarian organizations, higher education institutions, and nonprofit organizations that provide support to undocumented migrants. We discuss 3 primary issues: (i) HIA present both technological and human risks; (ii) the expectation of privacy self‐management by vulnerable populations is problematic; and (iii) there is a need for robust, actionable, privacy‐related guidelines for HIA. We suggest 5 recommendations to strengthen the privacy protection offered to undocumented migrants and other vulnerable populations….(More)”.
Netnography: The Essential Guide to Qualitative Social Media Research
Book by Robert Kozinets: “Netnography is an adaptation of ethnography for the online world, pioneered by Robert Kozinets, and is concerned with the study of online cultures and communities as distinct social phenomena, rather than isolated content. In this landmark third edition, Netnography: The Essential Guide provides the theoretical and methodological groundwork as well as the practical applications, helping students both understand and do netnographic research projects of their own.
Packed with enhanced learning features throughout, linking concepts to structured activities in a step by step way, the book is also now accompanied by a striking new visual design and further case studies, offering the essential student resource to conducting online ethnographic research. Real world examples provided demonstrate netnography in practice across the social sciences, in media and cultural studies, anthropology, education, nursing, travel and tourism, and others….(More)”.
National SDG Review: data challenges and opportunities
Press Release: “…the Partnership in Statistics for Development in the 21st Century (PARIS21) and Partners for Review launched a landmark new paper that identifies the factors preventing countries from fully exploiting their data ecosystem and proposes solutions to strengthening statistical capacities to achieve the 2030 Agenda for Sustainable Development.
Ninety percent of the data in the world has been created in the past two years, yet many countries with low statistical capacity struggle to produce, analyse and communicate the data necessary to advance sustainable development. At the same time, demand for more and better data and statistics is increasingly massively, with international agreements like the 2030 Agenda placing unprecedented demand on countries to report on more than 230 indicators.
Using PARIS21’s Capacity Development 4.0 (CD 4.0) approach, the paper shows that leveraging data available in the data ecosystem for official reporting requires new capacity in terms of skills and knowledge, management, politics and power. The paper also shows that these capacities need to be developed at both the organisational and systemic level, which involves the various channels and interactions that connect different organisations.
Aimed at national statistics offices, development professionals and others involved in the national data ecosystem, the paper provides a roadmap that can help national statistical systems develop and strengthen the capacities of traditional and new actors in the data ecosystem to improve both the follow-up and review process of the 2030 Agenda as well as the data architecture for sustainable development at the national level…(More)”.
Why Data Is Not the New Oil
Blogpost by Alec Stapp: “Data is the new oil,” said Jaron Lanier in a recent op-ed for The New York Times. Lanier’s use of this metaphor is only the latest instance of what has become the dumbest meme in tech policy. As the digital economy becomes more prominent in our lives, it is not unreasonable to seek to understand one of its most important inputs. But this analogy to the physical economy is fundamentally flawed. Worse, introducing regulations premised upon faulty assumptions like this will likely do far more harm than good. Here are seven reasons why “data is the new oil” misses the mark:
1. Oil is rivalrous; data is non-rivalrous
If someone uses a barrel of oil, it can’t be consumed again. But, as Alan McQuinn, a senior policy analyst at the Information Technology and Innovation Foundation, noted, “when consumers ‘pay with data’ to access a website, they still have the same amount of data after the transaction as before. As a result, users have an infinite resource available to them to access free online services.” Imposing restrictions on data collection makes this infinite resource finite.
2. Oil is excludable; data is non-excludable
Oil is highly excludable because, as a physical commodity, it can be stored in ways that prevent use by non-authorized parties. However, as my colleagues pointed out in a recent comment to the FTC: “While databases may be proprietary, the underlying data usually is not.” They go on to argue that this can lead to under-investment in data collection:
[C]ompanies that have acquired a valuable piece of data will struggle both to prevent their rivals from obtaining the same data as well as to derive competitive advantage from the data. For these reasons, it also means that firms may well be more reluctant to invest in data generation than is socially optimal. In fact, to the extent this is true there is arguably more risk of companies under-investing in data generation than of firms over-investing in order to create data troves with which to monopolize a market. This contrasts with oil, where complete excludability is the norm.
3. Oil is fungible; data is non-fungible
Oil is a commodity, so, by definition, one barrel of oil of a given grade is equivalent to any other barrel of that grade. Data, on the other hand, is heterogeneous. Each person’s data is unique and may consist of a practically unlimited number of different attributes that can be collected into a profile. This means that oil will follow the law of one price, while a dataset’s value will be highly contingent on its particular properties and commercialization potential.
4. Oil has positive marginal costs; data has zero marginal costs
There is a significant expense to producing and distributing an additional barrel of oil (as low as $5.49 per barrel in Saudi Arabia; as high as $21.66 in the U.K.). Data is merely encoded information (bits of 1s and 0s), so gathering, storing, and transferring it is nearly costless (though, to be clear, setting up systems for collecting and processing can be a large fixed cost). Under perfect competition, the market clearing price is equal to the marginal cost of production (hence why data is traded for free services and oil still requires cold, hard cash)….(More)”.
Principles alone cannot guarantee ethical AI
Paper by Brent Mittelstadt: “Artificial intelligence (AI) ethics is now a global topic of discussion in academic and policy circles. At least 84 public–private initiatives have produced statements describing high-level principles, values and other tenets to guide the ethical development, deployment and governance of AI. According to recent meta-analyses, AI ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics. Despite the initial credibility granted to a principled approach to AI ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach for the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement….(More)”.
Surveillance giants: how the business model of Google and Facebook threatens human rights
Report by Amnesty International: “Google and Facebook help connect the world and provide crucial services to billions. To participate meaningfully in today’s economy and society, and to realize their human rights, people rely on access to the internet—and to the tools Google and Facebook offer. But Google and Facebook’s platforms come at a systemic cost. The companies’ surveillance-based business model is inherently incompatible with the right to privacy and poses a threat to a range of other rights including freedom of opinion and expression, freedom of thought, and the right to equality and non-discrimination….(More)”.
Responsible Data for Children
New Site and Report by UNICEF and The GovLab: “RD4C seeks to build awareness regarding the need for special attention to data issues affecting children—especially in this age of changing technology and data linkage; and to engage with governments, communities, and development actors to put the best interests of children and a child rights approach at the center of our data activities. The right data in the right hands at the right time can significantly improve outcomes for children. The challenge is to understand the potential risks and ensure that the collection, analysis and use of data on children does not undermine these benefits.
Drawing upon field-based research and established good practice, RD4C aims to highlight and support best practice data responsibility; identify challenges and develop practical tools to assist practitioners in evaluating and addressing them; and encourage a broader discussion on actionable principles, insights, and approaches for responsible data management.
AI For Good Is Often Bad
Mark Latonero at Wired: “….Within the last few years, a number of tech companies, from Google to Huawei, have launched their own programs under the AI for Good banner. They deploy technologies like machine-learning algorithms to address critical issues like crime, poverty, hunger, and disease. In May, French president Emmanuel Macron invited about 60 leaders of AI-driven companies, like Facebook’s Mark Zuckerberg, to a Tech for Good Summit in Paris. The same month, the United Nations in Geneva hosted its third annual AI for Global Good Summit sponsored by XPrize. (Disclosure: I have spoken at it twice.) A recent McKinsey report on AI for Social Good provides an analysis of 160 current cases claiming to use AI to address the world’s most pressing and intractable problems.
While AI for good programs often warrant genuine excitement, they should also invite increased scrutiny. Good intentions are not enough when it comes to deploying AI for those in greatest need. In fact, the fanfare around these projects smacks of tech solutionism, which can mask root causes and the risks of experimenting with AI on vulnerable people without appropriate safeguards.
Tech companies that set out to develop a tool for the common good, not only their self-interest, soon face a dilemma: They lack the expertise in the intractable social and humanitarian issues facing much of the world. That’s why companies like Intel have partnered with National Geographic and the Leonardo DiCaprio Foundation on wildlife trafficking. And why Facebook partnered with the Red Cross to find missing people after disasters. IBM’s social-good program alone boasts 19 partnerships with NGOs and government agencies. Partnerships are smart. The last thing society needs is for engineers in enclaves like Silicon Valley to deploy AI tools for global problems they know little about….(More)”.
Meaningfully Engaging Youth in the Governance of the Global Refugee System
Bushra Ebadi at the World Refugee Council Research Paper Series: “Young people aged 15 to 35 comprise one-third of the world’s population, yet they are largely absent from decision-making fora and, as such, unaccounted for in policy making, programming and laws. The disenfranchisement of displaced youth is a particular problem, because it further marginalizes young people who have already experienced persecution and been forcibly displaced.
This paper aims to demonstrate the importance of including displaced youth in governance and decision making, to identify key barriers to engagement that displaced youth face, and to highlight effective strategies for engaging youth. Comprehensive financial, legal, social and governance reforms are needed in order to facilitate and support the meaningful engagement of youth in the refugee and IDP systems. Without these reforms and partnerships between youth and other diverse stakeholders, it will be difficult to achieve sustainable solutions for forcibly displaced populations and the communities that host them….(More)”.
Policy Entrepreneurs and Dynamic Change
Paper by Michael Mintrom: “Policy entrepreneurs are energetic actors who engage in collaborative efforts in and around government to promote policy innovations. Interest in policy entrepreneurs has grown over recent years. Increasingly, they are recognized as a unique class of political actors, who display common attributes, deploy common strategies, and can propel dynamic shifts in societal practices.
This Element assesses the current state of knowledge on policy entrepreneurs, their actions, and their impacts. It explains how various global forces are creating new demand for policy entrepreneurship, and suggests directions for future research on policy entrepreneurs and their efforts to drive dynamic change….(More)”.