Trivialization and Public Opinion: Slogans, Substance, and Styles of Thought in the Age of Complexity

Curated on Posted on by Stefaan Verhulst

Book by Oldrich Bubak and Henry Jacek: “Centering on public discourse and its fundamental lapses, this book takes a unique look at key barriers to social and political advancement in the information age. Public discourse is replete with confident, easy to manage claims, intuitions, and other shortcuts; outstanding of these is trivialization, the trend to distill multifaceted dilemmas to binary choices, neglect the big picture, gloss over alternatives, or filter reality through a lens of convenience—leaving little room for nuance and hence debate.

Far from superficial, such lapses are symptoms of deeper, intrinsically connected shortcomings inviting further attention. Focusing primarily on industrialized democracies, the authors take their readers on a transdisciplinary journey into the world of trivialization, engaging as they do so the intricate issues borne of a modern environment both enabled and constrained by technology. Ultimately, the authors elaborate upon the emerging counterweights to conventional worldviews and the paradigmatic alternatives that promise to help open new avenues for progress….(More)”.

Drones to deliver medicines to 12m people in Ghana

Curated on Posted on by Stefaan Verhulst

Neil Munshi in the Financial Times: “The world’s largest drone delivery network, ferrying 150 different medicines and vaccines, as well as blood, to 2,000 clinics in remote parts of Ghana, is set to be announced on Wednesday.

The network represents a big expansion for the Silicon Valley start-up Zipline, which began delivering blood in Rwanda in 2016 using pilotless, preprogrammed aircraft. The move, along with a new agreement in Rwanda signed in December, takes the company beyond simple blood distribution to more complicated vaccine and plasma deliveries.

“What this is going to show is that you can reach every GPS co-ordinate, you can serve everybody,” said Keller Rinaudo, Zipline chief executive. “Every human in that region or country [can be] within a 15-25 minute delivery of any essential medical product — it’s a different way of thinking about universal coverage.”

Zipline will deliver vaccines for yellow fever, polio, diptheria and tetanus which are provided by the World Health Organisation’s Expanded Project on Immunisation. The WHO will also use the company’s system for future mass immunisation programmes in Ghana.

Later this year, Zipline has plans to start operations in the US, in North Carolina, and in south-east Asia. The company said it will be able to serve 100m people within a year, up from the 22m that its projects in Ghana and Rwanda will cover.

In Ghana, Zipline said health workers will receive deliveries via a parachute drop within about 30 minutes of placing their orders by text message….(More)”.

Open data promotes citizen engagement at the local level

Curated on Posted on by Stefaan Verhulst

Afua Bruce at the Hill: “The city of Los Angeles recently released three free apps for its citizens: one to report broken street lighting, one to make 311 requests and one to get early alerts about earthquakes. Though it may seem like the city is just following a trend to modernize, the apps are part of a much larger effort to spread awareness of the more than 1,100 datasets that the city has publicized for citizens to view, analyze and share. In other words, the city has officially embraced the open data movement.

In the past few years, communities across the country have realized the power of data once only available to government. Often, the conversation about data focuses on criminal justice, because the demand for this data is being met by high-profile projects like Kamala Harris’ Open Justice Initiative, which makes California criminal justice data available to the citizenry and  the Open Data Policing Project, which provides a publicly searchable database of stop, search and use-of-force data. But the possibilities for data go far beyond justice and show the possibility for use in a variety of spaces, such as efforts to preserve local wildlife, track potholes and  understand community health trends….(More)”.

Selling civic engagement: A unique role for the private sector?

Curated on Posted on by Stefaan Verhulst

Rebecca Winthrop at Brookings: “Much has been written on the worrisome trends in Americans’ faith and participation in our nation’s democracy. According to the World Values Survey, almost 20 percent of millennials in the U.S. think that military rule or an authoritarian dictator is a “fairly good” form of government, and only 29 percent believe that living in a country that is governed democratically is “absolutely important.” In the last year, trust in American democratic institutions has dropped—only 53 percent of Americans view American democracy positively. This decline in faith and participation in our democracy has been ongoing for some time, as noted in the 2005 collection of essays, “Democracy At Risk: How Political Choices Undermine Citizen Participation, and What We Can Do About It.” The essays chart the “erosion of the activities and capacities of citizenship” from voting to broad civic engagement over the past several decades.

While civil society and government have been the actors most commonly addressing this worrisome trend, is there also a constructive role for the private sector to play? After all, compared to other options like military or authoritarian rule, a functioning democracy is much more likely to provide the conditions for free enterprise that business desires. One only has to look to the current events in Venezuela for a quick reminder of this.

Many companies do engage in a range of activities that broadly support civic engagement, from dedicating corporate social responsibility (CSR) dollars to civically-minded community activities to supporting employee volunteerism. These are worthy activities and should certainly continue, but given the crisis of faith in the foundations of our democratic process, the private sector could play a much bigger role in helping support a movement for renewed understanding of and participation in our political process. Many of the private sector’s most powerful tools for doing this lie not inside companies’ CSR portfolios but in their unique expertise in selling things. Every day companies leverage their expertise in influence—from branding to market-segmentation—to get Americans to use their products and services. What if this expertise were harnessed toward promoting civic understanding and engagement?

Companies could play a particularly useful role by tapping new resources to amplify existing good work and build increasing interest in civic engagement. Two ways of doing this could include the below….(More)”

Group decisions: When more information isn’t necessarily better

Curated on Posted on by Stefaan Verhulst

News Release from the Santa Fee Institute: “In nature, group decisions are often a matter of life or death. At first glance, the way certain groups of animals like minnows branch off into smaller sub-groups might seem counterproductive to their survival. After all, information about, say, where to find some tasty fish roe or which waters harbor more of their predators, would flow more freely and seem to benefit more minnows if the school of fish behaved as a whole. However, new research published in Philosophical Transactions of the Royal Society B sheds light on the complexity of collective decision-making and uncovers new insights into the benefits of the internal structure of animal groups.

In their paper, Albert Kao, a Baird Scholar and Omidyar Fellow at the Santa Fe Institute, and Iain Couzin, Director of the Max Planck Institute for Ornithology and Chair of Biodiversity and Collective Behavior at the University of Konstanz, simulate the information-sharing patterns of animals that prefer to interact with certain individuals over others. The authors’ modeling of such animal groups upends previously held assumptions about internal group structure and improves upon our understanding of the influence of group organization and environment on both the collective decision-making process and its accuracy.

Modular — or cliquey — group structure isolates the flow of communication between individuals, so that only certain animals are privy to certain pieces of information. “A feature of modular structure is that there’s always information loss,” says Kao, “but the effect of that information loss on accuracy depends on the environment.”

In simple environments, the impact of these modular groups is detrimental to accuracy, but when animals face many different sources of information, the effect is actually the opposite. “Surprisingly,” says Kao, “in complex environments, the information loss even helps accuracy in a lot of situations.” More information, in this case, is not necessarily better.

“Modular structure can have a profound — and unexpected — impact on the collective intelligence of groups,” says Couzin. “This may indeed be one of the reasons that we see internal structure in so many group-living species, from schooling fish and flocking birds to wild primate groups.”

Potentially, these new observations could be applied to many different kinds of social networks, from the migration patterns of birds to the navigation of social media landscapes to the organization of new companies, deepening our grasp of complex organization and collective behavior….(More)”.

(The paper, “Modular structure within groups causes information loss but can improve decision accuracy,” is part of a theme issue in the Philosophical Transactions of the Royal Society B entitled “Liquid Brains, Solid Brains: How distributed cognitive architectures process information.” The issue was inspired by a Santa Fe Institute working group and edited by Ricard Solé (Universitat Pompeu Fabra), Melanie Moses (University of New Mexico), and Stephanie Forrest (Arizona State University).

Technology-facilitated Societal Consensus

Curated on Posted on by Stefaan Verhulst

Paper by Timotheus Kampik and Amro Najjar: “The spread of radical opinions, facilitated by homophilic Internet communities (echo chambers), has become a threat to the stability of societies around the globe. The concept of choice architecture–the design of choice information for consumers with the goal of facilitating societally beneficial decisions–provides a promising (although not uncontroversial) general concept to address this problem.

The choice architecture approach is reflected in recent proposals advocating for recommender systems that consider the societal impact of their recommendations and not only strive to optimize revenue streams.

However, the precise nature of the goal state such systems should work towards remains an open question. In this paper, we suggest that this goal state can be defined by considering target opinion spread in a society on different topics of interest as a multivariate normal distribution; i.e., while there is a diversity of opinions, most people have similar opinions on most topics. We explain why this approach is promising, and list a set of crossdisciplinary research challenges that need to be solved to advance the idea….(More)”.

Whose Commons? Data Protection as a Legal Limit of Open Science

Curated on Posted on by Stefaan Verhulst

Mark Phillips and Bartha M. Knoppers in the Journal of Law, Medicine and Ethics: “Open science has recently gained traction as establishment institutions have come on-side and thrown their weight behind the movement and initiatives aimed at creation of information commons. At the same time, the movement’s traditional insistence on unrestricted dissemination and reuse of all information of scientific value has been challenged by the movement to strengthen protection of personal data. This article assesses tensions between open science and data protection, with a focus on the GDPR.

Powerful institutions across the globe have recently joined the ranks of those making substantive commitments to “open science.” For example, the European Commission and the NIH National Cancer Institute are supporting large-scale collaborations, such as the Cancer Genome Collaboratory, the European Open Science Cloud, and the Genomic Data Commons, with the aim of making giant stores of genomic and other data readily available for analysis by researchers. In the field of neuroscience, the Montreal Neurological Institute is midway through a novel five-year project through which it plans to adopt open science across the full spectrum of its research. The commitment is “to make publicly available all positive and negative data by the date of first publication, to open its biobank to registered researchers and, perhaps most significantly, to withdraw its support of patenting on any direct research outputs.” The resources and influence of these institutions seem to be tipping the scales, transforming open science from a longstanding aspirational ideal into an existing reality.

Although open science lacks any standard, accepted definition, one widely-cited model proposed by the Austria-based advocacy effort openscienceASAP describes it by reference to six principles: open methodology, open source, open data, open access, open peer review, and open educational resources. The overarching principle is “the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process.” This article adopts this principle as a working definition of open science, with a particular emphasis on open sharing of human data.

As noted above, many of the institutions committed to open science use the word “commons” to describe their initiatives, and the two concepts are closely related. “Medical information commons” refers to “a networked environment in which diverse sources of health, medical, and genomic information on large populations become widely shared resources.” Commentators explicitly link the success of information commons and progress in the research and clinical realms to open science-based design principles such as data access and transparent analysis (i.e., sharing of information about methods and other metadata together with medical or health data).

But what legal, as well as ethical and social, factors will ultimately shape the contours of open science? Should all restrictions be fought, or should some be allowed to persist, and if so, in what form? Given that a commons is not a free-for-all, in that its governing rules shape its outcomes, how might we tailor law and policy to channel open science to fulfill its highest aspirations, such as universalizing practical access to scientific knowledge and its benefits, and avoid potential pitfalls? This article primarily concerns research data, although passing reference is also made to the approach to the terms under which academic publications are available, which are subject to similar debates….(More)”.

Characterizing the Biomedical Data-Sharing Landscape

Curated on Posted on by Stefaan Verhulst

Paper by Angela G. Villanueva et al: “Advances in technologies and biomedical informatics have expanded capacity to generate and share biomedical data. With a lens on genomic data, we present a typology characterizing the data-sharing landscape in biomedical research to advance understanding of the key stakeholders and existing data-sharing practices. The typology highlights the diversity of data-sharing efforts and facilitators and reveals how novel data-sharing efforts are challenging existing norms regarding the role of individuals whom the data describe.

Technologies such as next-generation sequencing have dramatically expanded capacity to generate genomic data at a reasonable cost, while advances in biomedical informatics have created new tools for linking and analyzing diverse data types from multiple sources. Further, many research-funding agencies now mandate that grantees share data. The National Institutes of Health’s (NIH) Genomic Data Sharing (GDS) Policy, for example, requires NIH-funded research projects generating large-scale human genomic data to share those data via an NIH-designated data repository such as the Database of Geno-types and Phenotypes (dbGaP). Another example is the Parent Project Muscular Dystrophy, a non-profit organization that requires applicants to propose a data-sharing plan and take into account an applicant’s history of data sharing.

The flow of data to and from different projects, institutions, and sectors is creating a medical information commons (MIC), a data-sharing ecosystem consisting of networked resources sharing diverse health-related data from multiple sources for research and clinical uses. This concept aligns with the 2018 NIH Strategic Plan for Data Science, which uses the term “data ecosystem” to describe “a distributed, adaptive, open system with properties of self-organization, scalability and sustainability” and proposes to “modernize the biomedical research data ecosystem” by funding projects such as the NIH Data Commons. Consistent with Elinor Ostrom’s discussion of nested institutional arrangements, an MIC is both singular and plural and may describe the ecosystem as a whole or individual components contributing to the ecosystem. Thus, resources like the NIH Data Commons with its associated institutional arrangements are MICs, and also form part of the larger MIC that encompasses all such resources and arrangements.

Although many research funders incentivize data sharing, in practice, progress in making biomedical data broadly available to maximize its utility is often hampered by a broad range of technical, legal, cultural, normative, and policy challenges that include achieving interoperability, changing the standards for academic promotion, and addressing data privacy and security concerns. Addressing these challenges requires multi-stakeholder involvement. To identify relevant stakeholders and advance understanding of the contributors to an MIC, we conducted a landscape analysis of existing data-sharing efforts and facilitators. Our work builds on typologies describing various aspects of data sharing that focused on biobanks, research consortia, or where data reside (e.g., degree of data centralization).7 While these works are informative, we aimed to capture the biomedical data-sharing ecosystem with a wider scope. Understanding the components of an MIC ecosystem and how they interact, and identifying emerging trends that test existing norms (such as norms respecting the role of individuals from whom the data describe), is essential to fostering effective practices, policies and governance structures, guiding resource allocation, and promoting the overall sustainability of the MIC….(More)”

How Recommendation Algorithms Run the World

Curated on Posted on by Stefaan Verhulst

Article by Zeynep Tufekci: “What should you watch? What should you read? What’s news? What’s trending? Wherever you go online, companies have come up with very particular, imperfect ways of answering these questions. Everywhere you look, recommendation engines offer striking examples of how values and judgments become embedded in algorithms and how algorithms can be gamed by strategic actors.

Consider a common, seemingly straightforward method of making suggestions: a recommendation based on what people “like you” have read, watched, or shopped for. What exactly is a person like me? Which dimension of me? Is it someone of the same age, gender, race, or location? Do they share my interests? My eye color? My height? Or is their resemblance to me determined by a whole mess of “big data” (aka surveillance) crunched by a machine-learning algorithm?

Deep down, behind every “people like you” recommendation is a computational method for distilling stereotypes through data. Even when these methods work, they can help entrench the stereotypes they’re mobilizing. They might easily recommend books about coding to boys and books about fashion to girls, simply by tracking the next most likely click. Of course, that creates a feedback cycle: If you keep being shown coding books, you’re probably more likely to eventually check one out.

Another common method for generating recommendations is to extrapolate from patterns in how people consume things. People who watched this then watched that; shoppers who purchased this item also added that one to their shopping cart. Amazon uses this method a lot, and I admit, it’s often quite useful. Buy an electric toothbrush? How nice that the correct replacement head appears in your recommendations. Congratulations on your new vacuum cleaner: Here are some bags that fit your machine.

But these recommendations can also be revealing in ways that are creepy. …

One final method for generating recommendations is to identify what’s “trending” and push that to a broader user base. But this, too, involves making a lot of judgments….(More)”.

Leveraging Big Data for Social Responsibility

Curated on Posted on by Stefaan Verhulst

Paper by Cynthia Ann Peterson: “Big data has the potential to revolutionize the way social risks are managed by providing enhanced insight to enable more informed actions to be taken. The objective of this paper is to share the approach taken by PETRONAS to leverage big data to enhance its social performance practice, specifically in social risk assessments and grievance mechanism.

The paper will deliberate on the benefits, challenges and opportunities to improve the management of social risk through analytics, and how PETRONAS has taken those factors into consideration in the enhancement of its social risk assessment and grievance mechanism tools. Key considerations such as disaggregation of data, the appropriate leading and lagging indicators and having a human rights lens to data will also be discussed.

Leveraging on big data is still in its early stages in the social risk space, similar with other areas in the oil and gas industry according to research by Wood Mackenzie. Even so, there are several concerns which include; the aggregation of data may result in risks to minority or vulnerable groups not getting surfaced; privacy breaches which violate human rights and potential discrimination due to prescriptive analysis, such as on a community’s propensity to pose certain social risks to projects or operations. Certainly, there are many challenges ahead which need to be considered, including how best to take a human rights approach to using big data.

Nevertheless, harnessing the power of big data will help social risk practitioners turn a high volume of disparate pieces of raw data from grievance mechanisms and social risk assessments into information that can be used to avoid or mitigate risks now and in the future through predictive technology. Consumer and other industries are benefiting from this leverage now, and social performance practitioners in the oil and gas industry can emulate these proven models….(More)”.