Essay by Thomas Carothers: “Adverse political developments in both established and newer democracies, especially the abdication by the United States of its traditional leadership role, have cast international democracy support into doubt. Yet international action on behalf of democracy globally remains necessary and possible. Moreover, some important elements of continuity remain, including overall Western spending on democracy assistance. Democracy support must adapt to its changed circumstances by doing more to take new geopolitical realities into account; effacing the boundary between support for democracy in new and in established democracies; strengthening the economic dimension of democracy assistance; and moving technological issues to the forefront…(More)”.
Essay by Bapu Vaitla, Stefaan Verhulst, Linus Bengtsson, Marta C. González, Rebecca Furst-Nichols & Emily Courey Pryor in Special Issue on Big Data of Nature Medicine: “Women and girls are legally and socially marginalized in many countries. As a result, policymakers neglect key gendered issues such as informal labor markets, domestic violence, and mental health1. The scientific community can help push such topics onto policy agendas, but science itself is riven by inequality: women are underrepresented in academia, and gendered research is rarely a priority of funding agencies.
However, the critical importance of better gender data for societal well-being is clear. Mental health is a particularly striking example. Estimates from the Global Burden of Disease database suggest that depressive and anxiety disorders are the second leading cause of morbidity among females between 10 and 63 years of age2. But little is known about the risk factors that contribute to mental illness among specific groups of women and girls, the challenges of seeking care for depression and anxiety, or the long-term consequences of undiagnosed and untreated illness. A lack of data similarly impedes policy action on domestic and intimate-partner violence, early marriage, and sexual harassment, among many other topics.
‘Big data’ can help fill that gap. The massive amounts of information passively generated by electronic devices represent a rich portrait of human life, capturing where people go, the decisions they make, and how they respond to changes in their socio-economic environment. For example, mobile-phone data allow better understanding of health-seeking behavior as well as the dynamics of infectious-disease transmission3. Social-media platforms generate the world’s largest database of thoughts and emotions—information that, if leveraged responsibly, can be used to infer gendered patterns of mental health4. Remote sensors, especially satellites, can be used in conjunction with traditional data sources to increase the spatial and temporal granularity of data on women’s economic activity and health status5.
But the risk of gendered algorithmic bias is a serious obstacle to the responsible use of big data. Data are not value free; they reproduce the conscious and unconscious attitudes held by researchers, programmers, and institutions. Consider, for example, the training datasets on which the interpretation of big data depends. Training datasets establish the association between two or more directly observed phenomena of interest—for example, the mental health of a platform user (typically collected through a diagnostic survey) and the semantic content of the user’s social-media posts. These associations are then used to develop algorithms that interpret big data streams. In the example here, the (directly unobserved) mental health of a large population of social-media users would be inferred from their observed posts….(More)”.
Marietje Schaake at the Financial Times: “Technology companies have governments over a barrel. Whether they are maximising traffic flow efficiency, matching pupils with their school preferences, trying to anticipate drought based on satellite and soil data, most governments heavily rely on critical infrastructure and artificial intelligence developed by the private sector. This growing dependence has profound implications for democracy.
An unprecedented information asymmetry is growing between companies and governments. We can see this in the long-running investigation into interference in the 2016 US presidential elections. Companies build voter registries, voting machines and tallying tools, while social media companies sell precisely targeted advertisements using information gleaned by linking data on friends, interests, location, shopping and search.
This has big privacy and competition implications, yet oversight is minimal. Governments, researchers and citizens risk being blindsided by the machine room that powers our lives and vital aspects of our democracies. Governments and companies have fundamentally different incentives on transparency and accountability.
While openness is the default and secrecy the exception for democratic governments, companies resist providing transparency about their algorithms and business models. Many of them actively prevent accountability, citing rules that protect trade secrets.
We must revisit these protections when they shield companies from oversight. There is a place for protecting proprietary information from commercial competitors, but the scope and context need to be clarified and balanced when they have an impact on democracy and the rule of law.
Regulators must act to ensure that those designing and running algorithmic processes do not abuse trade secret protections. Tech groups also use the EU’s General Data Protection Regulation to deny access to company information. Although the regulation was enacted to protect citizens against the mishandling of personal data, it is now being wielded cynically to deny scientists access to data sets for research. The European Data Protection Supervisor has intervened, but problems could recur. To mitigate concerns about the power of AI, provider companies routinely promise that the applications will be understandable, explainable, accountable, reliable, contestable, fair and — don’t forget — ethical.
Yet there is no way to test these subjective notions without access to the underlying data and information. Without clear benchmarks and information to match, proper scrutiny of the way vital data is processed and used will be impossible….(More)”.
Idea by Helena Rong and Juncheng Yang: “We propose an interactive design engagement platform which facilitates a continuous conversation between developers, designers and end users from pre-design and planning phases all the way to post-occupancy, adopting a citizen-centric and inclusive-oriented approach which would stimulate trust-building and invite active participation from end users from different age, ethnicity, social and economic background to participate in the design and development process. We aim to explore how collective intelligence through citizen engagement could be enabled by data to allow new collectives to emerge, confronting design as an iterative process involving scalable cooperation of different actors. As a result, design is a collaborative and conscious practice not born out of a single mastermind of the architect. Rather, its agency is reinforced by a cooperative ideal involving institutions, enterprises and single individuals alike enabled by data science….(More)”
Report by Shelly Culbertson, James Dimarogonas, Katherine Costello, and Serafina Lanna: “In the past two decades, the global population of forcibly displaced people has more than doubled, from 34 million in 1997 to 71 million in 2018. Amid this growing crisis, refugees and the organizations that assist them have turned to technology as an important resource, and technology can and should play an important role in solving problems in humanitarian settings. In this report, the authors analyze technology uses, needs, and gaps, as well as opportunities for better using technology to help displaced people and improving the operations of responding agencies. The authors also examine inherent ethical, security, and privacy considerations; explore barriers to the successful deployment of technology; and outline some tools for building a more systematic approach to such deployment. The study approach included a literature review, semi-structured interviews with stakeholders, and focus groups with displaced people in Colombia, Greece, Jordan, and the United States. The authors provide several recommendations for more strategically using and developing technology in humanitarian settings….(More)”.
Tali Sharot & Cass R. Sunstein in Nature: “Immense amounts of information are now accessible to people, including information that bears on their past, present and future. An important research challenge is to determine how people decide to seek or avoid information. Here we propose a framework of information-seeking that aims to integrate the diverse motives that drive information-seeking and its avoidance. Our framework rests on the idea that information can alter people’s action, affect and cognition in both positive and negative ways. The suggestion is that people assess these influences and integrate them into a calculation of the value of information that leads to information-seeking or avoidance. The theory offers a framework for characterizing and quantifying individual differences in information-seeking, which we hypothesize may also be diagnostic of mental health. We consider biases that can lead to both insufficient and excessive information-seeking. We also discuss how the framework can help government agencies to assess the welfare effects of mandatory information disclosure….(More)”.
Data Collaborative Case Study by Michelle Winowatan, Andrew Young, and Stefaan Verhulst: “
Global Fishing Watch, originally set up through a collaboration between Oceana, SkyTruth and Google, is an independent nonprofit organization dedicated to advancing responsible stewardship of our oceans through increased transparency in fishing activity and scientific research. Using big data processing and machine learning, Global Fishing Watch visualizes, tracks, and shares data about global fishing activity in near-real time and for free via their public map. To date, the platform tracks approximately 65,000 commercial fishing vessels globally. These insights have been used in a number of academic publications, ocean advocacy efforts, and law enforcement activities.
Data Collaborative Model: Based on the typology of data collaborative practice areas, Global Fishing Watch is an example of the data pooling model of data collaboration, specifically a public data pool. Public data pools co-mingle data assets from multiple data holders — including governments and companies — and make those shared assets available on the web. This approach enabled the data stewards and stakeholders involved in Global Fishing Watch to bring together multiple data streams from both public- and private-sector entities in a single location. This single point of access provides the public and relevant authorities with user-friendly access to actionable, previously fragmented data that can drive efforts to address compliance in fisheries and illegal fishing around the world.
Data Stewardship Approach: Global Fishing Watch also provides a clear illustration of the importance of data stewards. For instance, representatives from Google Earth Outreach, one of the data holders, played an important stewardship role in seeking to connect and coordinate with SkyTruth and Oceana, two important nonprofit environmental actors who were working separately prior to this initiative. The brokering of this partnership helped to bring relevant data assets from the public and private sectors to bear in support of institutional efforts to address the stubborn challenge of illegal fishing.
Read the full case study here.”
Blog by Michael Cañares: “It was a humid December afternoon in Banda Aceh, a bustling city in north Indonesia. Two women members of an education reform advocacy group were busy preparing infographics on how the city government was spending its education budget and its impact on service delivery quality in schools. The room was abuzz with questions and apprehension because the next day, the group would present its analysis on the data that they were able to access for the first time to education department officials. The analyses uncovered inefficiencies, poor school performance, ineffective allocation of resources, among others.
While worried about how the officials would react, almost everyone in the room was cheerful. One advocate told me she found the whole process liberating. She found it exhilarating to use government-published data to ask civil servants why the state of education in some schools was disappointing. “Armed with data, I am no longer afraid to speak my mind,” she said.
This was five years ago, but the memory has stuck with me. It was one of many experiences that inspired me to continue advocating for governments to publish data proactively, and searching for ways to use data to strengthen people’s voice on matters that are important to them.
Globally, there are many examples of how data has enabled people to advocate for their rights, demand better public services or hold governments to account. This blog post shares a few examples, focusing largely on how people are able to access and use data that shape their lives — the first dimension of how we characterize data empowerment….
Poverty Stoplight: People use their own data to improve their lives…
Data Zetu: Giving borrowed data back to citizens…
Article by James W. Weis, Amy Brand and Joi Ito: “Science and technology are propelled forward by the sharing of knowledge. Yet despite their vital importance in today’s innovation-driven economy, our knowledge infrastructures have failed to scale with today’s rapid pace of research and discovery.
For example, academic journals, the dominant dissemination platforms of scientific knowledge, have not been able to take advantage of the linking, transparency, dynamic communication and decentralized authority and review that the internet enables. Many other knowledge-driven sectors, from journalism to law, suffer from a similar bottleneck — caused not by a lack of technological capacity, but rather by an inability to design and implement efficient, open and trustworthy mechanisms of information dissemination.
Fortunately, growing dissatisfaction with current knowledge-sharing infrastructures has led to a more nuanced understanding of the requisite features that such platforms must provide. With such an understanding, higher education institutions around the world can begin to recapture the control and increase the utility of the knowledge they produce.
When the World Wide Web emerged in the 1990s, an era of robust scholarship based on open sharing of scientific advancements appeared inevitable. The internet — initially a research network — promised a democratization of science, universal access to the academic literature and a new form of open publishing that supported the discovery and reuse of knowledge artifacts on a global scale. Unfortunately, however, that promise was never realized. Universities, researchers and funding agencies, for the most part, failed to organize and secure the investment needed to build scalable knowledge infrastructures, and publishing corporations moved in to solidify their position as the purveyors of knowledge.
In the subsequent decade, such publishers have consolidated their hold. By controlling the most prestigious journals, they have been able to charge for access — extracting billions of dollars in subscription fees while barring much of the world from the academic literature. Indeed, some of the world’s wealthiest academic institutions are no longer able or willing to pay the subscription costs required.
Further, by controlling many of the most prestigious journals, publishers have also been able to position themselves between the creation and consumption of research, and so wield enormous power over peer review and metrics of scientific impact. Thus, they are able to significantly influence academic reputation, hirings, promotions, career progressions and, ultimately, the direction of science itself.
But signs suggest that the bright future envisioned in the early days of the internet is still within reach. Increasing awareness of, and dissatisfaction with, the many bottlenecks that the commercial monopoly on research information has imposed are stimulating new strategies for developing the future’s knowledge infrastructures. One of the most promising is the shift toward infrastructures created and supported by academic institutions, the original creators of the information being shared, and nonprofit consortia like the Collaborative Knowledge Foundation and the Center for Open Science.
Those infrastructures should fully exploit the technological capabilities of the World Wide Web to accelerate discovery, encourage more research support and better structure and transmit knowledge. By aligning academic incentives with socially beneficial outcomes, such a system could enrich the public while also amplifying the technological and societal impact of investment in research and innovation.
We’ve outlined below the three areas in which a shift to an academically owned platforms would yield the highest impact.
- Truly Open Access…
- Meaningful Impact Metrics…
- Trustworthy Peer Review….(More)”.
Martin Fougère and Nikodemus Solitander at the Journal of Business Ethics: “Multi-stakeholder initiatives involve actors from several spheres of society (market, civil society and state) in collaborative arrangements to reach objectives typically related to sustainable development. In political CSR literature, these arrangements have been framed as improvements to transnational governance and as being somehow democratic.
We draw on Mouffe’s works on agonistic pluralism to problematize the notion that consensus-led multi-stakeholder initiatives bring more democratic control on corporate power. We examine two initiatives which address two very different issue areas: the Roundtable on Sustainable Palm Oil (RSPO) and the Bangladesh Accord on Fire and Building Safety (The Accord).
We map the different kinds of adversarial relations involved in connection with the issues meant to be governed by the two initiatives, and find those adversarial relations to take six main shapes, affecting the initiatives in different ways: (1) competing regulatory initiatives; (2) pressure-response relations within multi-stakeholder initiatives; (3) pressure-response relations between NGOs and states through multi-stakeholder initiatives; (4) collaboration and competition between multi-stakeholder initiatives and states; (5) pressure-response relations between civil society actors and multi-stakeholder initiatives; and (6) counter-hegemonic movements against multi-stakeholder initiatives as hegemonic projects.
We conclude that multi-stakeholder initiatives cannot be democratic by themselves, and we argue that business and society researchers should not look at democracy or politics only internally to these initiatives, but rather study how issue areas are regulated through interactions between a variety of actors—both within and without the multi-stakeholder initiatives—who get to have a legitimate voice in this regulation….(More)”.