The promise and peril of a digital ecosystem for the planet


Blog post by Jillian Campbell and David E Jensen: “A range of frontier and digital technologies have dramatically boosted the ways in which we can monitor the health of our planet. And sustain our future on it (Figure 1).

Figure 1. A range of frontier an digital technologies can be combined to monitor our planet and the sustainable use of natural resources (1)

If we can leverage this technology effectively, we will be able to assess and predict risks, increase transparency and accountability in the management of natural resources and inform markets as well as consumer choice. These actions are all required if we are to stand a better chance of achieving the Sustainable Development Goals (SDGs).

However, for this vision to become a reality, public and private sector actors must take deliberate action and collaborate to build a global digital ecosystem for the planet — one consisting of data, infrastructure, rapid analytics, and real-time insights. We are now at a pivotal moment in the history of our stewardship of this planet. A “tipping point” of sorts. And in order to guide the political action which is required to counter the speed, scope and severity of the environmental and climate crises, we must acquire and deploy these data sets and frontier technologies. Doing so can fundamentally change our economic trajectory and underpin a sustainable future.

This article shows how such a global digital ecosystem for the planet can be achieved — as well as what we risk if we do not take decisive action within the next 12 months….(More)”.

Sharing Private Data for Public Good


Stefaan G. Verhulst at Project Syndicate: “After Hurricane Katrina struck New Orleans in 2005, the direct-mail marketing company Valassis shared its database with emergency agencies and volunteers to help improve aid delivery. In Santiago, Chile, analysts from Universidad del Desarrollo, ISI Foundation, UNICEF, and the GovLab collaborated with Telefónica, the city’s largest mobile operator, to study gender-based mobility patterns in order to design a more equitable transportation policy. And as part of the Yale University Open Data Access project, health-care companies Johnson & Johnson, Medtronic, and SI-BONE give researchers access to previously walled-off data from 333 clinical trials, opening the door to possible new innovations in medicine.

These are just three examples of “data collaboratives,” an emerging form of partnership in which participants exchange data for the public good. Such tie-ups typically involve public bodies using data from corporations and other private-sector entities to benefit society. But data collaboratives can help companies, too – pharmaceutical firms share data on biomarkers to accelerate their own drug-research efforts, for example. Data-sharing initiatives also have huge potential to improve artificial intelligence (AI). But they must be designed responsibly and take data-privacy concerns into account.

Understanding the societal and business case for data collaboratives, as well as the forms they can take, is critical to gaining a deeper appreciation the potential and limitations of such ventures. The GovLab has identified over 150 data collaboratives spanning continents and sectors; they include companies such as Air FranceZillow, and Facebook. Our research suggests that such partnerships can create value in three main ways….(More)”.

Aliens in Europe. An open approach to involve more people in invasive species detection


Paper by Sven Schade et al: “Amplified by the phenomenon of globalisation, such as increased human mobility and the worldwide shipping of goods, we observe an increasing spread of animals and plants outside their native habitats. A few of these ‘aliens’ have negative impacts on their environment, including threats to local biodiversity, agricultural productivity, and human health. Our work addresses these threats, particularly within the European Union (EU), where a related legal framework has been established. We follow an open and participatory approach that allows more people to share their experiences of invasive alien species (IAS) in their surroundings. Over the past three years, we developed a mobile phone application, together with the underlying data management and validation infrastructure, which allows smartphone users to report a selected list of IAS. We put quality assurance and data integration mechanisms into place that allows the uptake of information into existing official systems in order to make it accessible to the relevant policy-making at EU level.

This article summarises our scientific methodology and technical approach, explains our decisions, and provides an outlook to the future of IAS monitoring involving citizens and utilising the latest technological advancements. Last but not least we emphasise on software design for reuse, within the domain of IAS monitoring, but also for supporting citizen science apps more generally. Whereas much could already be achieved, many scientific, technical and organizational challenges still remain to be addressed before data can be seamlessly shared and integrated. Here, we particularly highlight issues that emerge in an international setting, which involves many different stakeholders….(More)”.

Tackling Climate Change with Machine Learning


Paper by David Rolnick et al: “Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change….(More)”.

Behavioral Science and Climate Policy


Chapter by Michael Howlett and Stuti Rawat: “Behavioral science consists of the systematic analysis of processes underlying human behavior through experimentation and observation, drawing on knowledge, research, and methods from a variety of fields such as economics, psychology, and sociology. Because policymaking involves efforts to modify or alter the behavior of policy-takers and centers on the processes of decision-making in government, it has always been concerned with behavioral psychology. Classic studies of decision-making in the field derived their frameworks and concepts from psychology, and the founder of policy sciences, Harold Lasswell, was himself trained as a behavioral political scientist. Hence, it should not be surprising that the use of behavioral science is a feature of many policy areas, including climate change policy.

This is given extra emphasis, however, because climate change policymaking and the rise of climate change as a policy issue coincides with a resurgence in behaviorally inspired policy analysis and design brought about by the development of behavioral economics. Thus efforts to deal with climate change have come into being at a time when behavioral governance has been gaining traction worldwide under the influence of works by, among others, Kahneman and Tversky, Thaler, and Sunstein. Such behavioral governance studies have focused on the psychological and cognitive behavioral processes in individuals and collectives, in order to inform, design, and implement different modes of governing. They have been promoted by policy scholars, including many economists working in the area who prefer its insights to those put forward by classical or neoclassical economics.

In the context of climate change policy, behavioral science plays two key roles—through its use of behaviorally premised policy instruments as new modes of public policy being used or proposed to be used, in conjunction with traditional climate change policy tools; and as a way of understanding some of the barriers to compliance and policy design encountered by governments in combating the “super wicked problem” of climate change. Five kinds of behavioral tools have been found to be most commonly used in relation to climate change policy: provision of information, use of social norms, goal setting, default rules, and framing. A large proportion of behavioral tools has been used in the energy sector, because of its importance in the context of climate change action and the fact that energy consumption is easy to monitor, thereby facilitating impact assessment….(More)”.

The Impact of Citizen Environmental Science in the United States


Paper by George Wyeth, Lee C. Paddock, Alison Parker, Robert L. Glicksman and Jecoliah Williams: “An increasingly sophisticated public, rapid changes in monitoring technology, the ability to process large volumes of data, and social media are increasing the capacity for members of the public and advocacy groups to gather, interpret, and exchange environmental data. This development has the potential to alter the government-centric approach to environmental governance; however, citizen science has had a mixed record in influencing government decisions and actions. This Article reviews the rapid changes that are going on in the field of citizen science and examines what makes citizen science initiatives impactful, as well as the barriers to greater impact. It reports on 10 case studies, and evaluates these to provide findings about the state of citizen science and recommendations on what might be done to increase its influence on environmental decisionmaking….(More)”,

We Need a Data-Rich Picture of What’s Killing the Planet


Clive Thompson at Wired: “…Marine litter isn’t the only hazard whose contours we can’t fully see. The United Nations has 93 indicators to measure the environmental dimensions of “sustainable development,” and amazingly, the UN found that we have little to no data on 68 percent of them—like how rapidly land is being degraded, the rate of ocean acidification, or the trade in poached wildlife. Sometimes this is because we haven’t collected it; in other cases some data exists but hasn’t been shared globally, or it’s in a myriad of incompatible formats. No matter what, we’re flying blind. “And you can’t manage something if you can’t measure it,” says David Jensen, the UN’s head of environmental peacebuilding.

In other words, if we’re going to help the planet heal and adapt, we need a data revolution. We need to build a “digital eco­system for the environment,” as Jensen puts it.

The good news is that we’ve got the tools. If there’s one thing tech excels at (for good and ill), it’s surveillance, right? We live in a world filled with cameras and pocket computers, titanic cloud computing, and the eerily sharp insights of machine learning. And this stuff can be used for something truly worthwhile: studying the planet.

There are already some remarkable cases of tech helping to break through the fog. Consider Global Fishing Watch, a nonprofit that tracks the world’s fishing vessels, looking for overfishing. They use everything from GPS-like signals emitted by ships to satellite infrared imaging of ship lighting, plugged into neural networks. (It’s massive, cloud-scale data: over 60 million data points per day, making the AI more than 90 percent accurate at classifying what type of fishing activity a boat is engaged in.)

“If a vessel is spending its time in an area that has little tuna and a lot of sharks, that’s questionable,” says Brian Sullivan, cofounder of the project and a senior program manager at Google Earth Outreach. Crucially, Global Fishing Watch makes its data open to anyone­­­—so now the National Geographic Society is using it to lobby for new marine preserves, and governments and nonprofits use it to target illicit fishing.

If we want better environmental data, we’ll need for-profit companies with the expertise and high-end sensors to pitch in too. Planet, a firm with an array of 140 satellites, takes daily snapshots of the entire Earth. Customers like insurance and financial firms love that sort of data. (It helps them understand weather and climate risk.) But Planet also offers it to services like Global Forest Watch, which maps deforestation and makes the information available to anyone (like activists who help bust illegal loggers). Meanwhile, Google’s skill in cloud-based data crunching helps illuminate the state of surface water: Google digitized 30 years of measurements from around the globe—extracting some from ancient magnetic tapes—then created an easy-to-use online tool that lets resource-poor countries figure out where their water needs protecting….(More)”.

Can we nudge farmers into saving water? Evidence from a randomised experiment


Paper by Sylvain Chabé-Ferret, Philippe Le Coent, Arnaud Reynaud, Julie Subervie and Daniel Lepercq: “We test whether social comparison nudges can promote water-saving behaviour among farmers as a complement to traditional CAP measures. We conducted a randomised controlled trial among 200 farmers equipped with irrigation smart meters in South-West France. Treated farmers received weekly information on individual and group water consumption over four months. Our results rule out medium to large effect-sizes of the nudge. Moreover, they suggest that the nudge was effective at reducing the consumption of those who irrigate the most, although it appears to have reduced the proportion of those who do not consume water at all….(More)”.

The 100 Questions Initiative: Sourcing 100 questions on key societal challenges that can be answered by data insights


100Q Screenshot

Press Release: “The Governance Lab at the NYU Tandon School of Engineering announced the launch of the 100 Questions Initiative — an effort to identify the most important societal questions whose answers can be found in data and data science if the power of data collaboratives is harnessed.

The initiative, launched with initial support from Schmidt Futures, seeks to address challenges on numerous topics, including migration, climate change, poverty, and the future of work.

For each of these areas and more, the initiative will seek to identify questions that could help unlock the potential of data and data science with the broader goal of fostering positive social, environmental, and economic transformation. These questions will be sourced by leveraging “bilinguals” — practitioners across disciplines from all over the world who possess both domain knowledge and data science expertise.

The 100 Questions Initiative starts by identifying 10 key questions related to migration. These include questions related to the geographies of migration, migrant well-being, enforcement and security, and the vulnerabilities of displaced people. This inaugural effort involves partnerships with the International Organization for Migration (IOM) and the European Commission, both of which will provide subject-matter expertise and facilitation support within the framework of the Big Data for Migration Alliance (BD4M).

“While there have been tremendous efforts to gather and analyze data relevant to many of the world’s most pressing challenges, as a society, we have not taken the time to ensure we’re asking the right questions to unlock the true potential of data to help address these challenges,” said Stefaan Verhulst, co-founder and chief research and development officer of The GovLab. “Unlike other efforts focused on data supply or data science expertise, this project seeks to radically improve the set of questions that, if answered, could transform the way we solve 21st century problems.”

In addition to identifying key questions, the 100 Questions Initiative will also focus on creating new data collaboratives. Data collaboratives are an emerging form of public-private partnership that help unlock the public interest value of previously siloed data. The GovLab has conducted significant research in the value of data collaboration, identifying that inter-sectoral collaboration can both increase access to information (e.g., the vast stores of data held by private companies) as well as unleash the potential of that information to serve the public good….(More)”.

So­cial me­dia data re­veal where vis­it­ors to nature loca­tions provide po­ten­tial be­ne­fits or threats to biodiversity


University of Helsinki: “In a new article published in the journal Science of the Total Environment, a team of researchers assessed global patterns of visitation rates, attractiveness and pressure to more than 12,000 Important Bird and Biodiversity Areas (IBAs), which are sites of international significance for nature conservation, by using geolocated data mined from social media (Twitter and Flickr).

The study found that Important Bird and Biodiversity Areas located in Europe and Asia, and in temperate biomes, had the highest density of social media users. Results also showed that sites of importance for congregatory species, which were also more accessible, more densely populated and provided more tourism facilities, received higher visitation than did sites richer in bird species.

 “Resources in biodiversity conservation are woefully inadequate and novel data sources from social media provide openly available user-generated information about human-nature interactions, at an unprecedented spatio-temporal scale”, says Dr Anna Hausmann from the University of Helsinki, a conservation scientist leading the study. “Our group has been exploring and validating data retrieved from social media to understand people´s preferences for experiencing nature in national parks at a local, national and continental scale”, she continues, “in this study, we expand our analyses at a global level”. …

“Social media content and metadata contain useful information for understanding human-nature interactions in space and time”, says Prof. Tuuli Toivonen, another co-author in the paper and the leader of the Digital Geography Lab at the University of Helsinki. “Social media data can also be used to cross-validate and enrich data collected by conservation organizations”, she continues. The study found that the 17 percent of all Important Bird and Biodiversity Areas (IBA) that were assessed by experts to be under greater human disturbance also had higher density of social media users….(More)”.