How Technology is Crowd-Sourcing the Fight Against Hunger

Curated on Posted on by Stefaan Verhulst

Beth Noveck at Media Planet: “There is more than enough food produced to feed everyone alive today. Yet access to nutritious food is a challenge everywhere and depends on getting every citizen involved, not just large organizations. Technology is helping to democratize and distribute the job of tackling the problem of hunger in America and around the world.

Real-time research

One of the hardest problems is the difficulty of gaining real-time insight into food prices and shortages. Enter technology. We no longer have to rely on professional inspectors slowly collecting information face-to-face. The UN World Food Programme, which provides food assistance to 80 million people each year, together with Nielsen is conducting mobile phone surveys in 15 countries (with plans to expand to 30), asking people by voice and text about what they are eating. Formerly blank maps are now filled in with information provided quickly and directly by the most affected people, making it easy to prioritize the allocation of resources.

Technology helps the information flow in both directions, enabling those in need to reach out, but also to become more effective at helping themselves. The Indian Ministry of Agriculture, in collaboration with Reuters Market Light, provides information services in nine Indian languages to 1.4 million registered farmers in 50,000 villages across 17 Indian states via text and voice messages.

“In the United States, 40 percent of the food produced here is wasted, and yet 1 in 4 American children (and 1 in 6 adults) remain food insecure…”

Data to the people

New open data laws and policies that encourage more transparent publication of public information complement data collection and dissemination technologies such as phones and tablets. About 70 countries and hundreds of regions and cities have adopted open data policies, which guarantee that the information these public institutions collect be available for free use by the public. As a result, there are millions of open datasets now online on websites such as the Humanitarian Data Exchange, which hosts 4,000 datasets such as country-by-country stats on food prices and undernourishment around the world.

Companies are compiling and sharing data to combat food insecurity, too. Anyone can dig into the data on the Global Open Data for Agriculture and Nutrition platform, a data collaborative where 300 private and public partners are sharing information.

Importantly, this vast quantity of open data is available to anyone, not only to governments. As a result, large and small entrepreneurs are able to create new apps and programs to combat food insecurity, such as Plantwise, which uses government data to offer a knowledge bank and run “plant clinics” that help farmers lose less of what they grow to pests. Google uses open government data to show people the location of farmers markets near their homes.

Students, too, can learn to play a role. For the second summer in a row, the Governance Lab at New York University, in partnership with the United States Department of Agriculture (USDA), mounted a two-week open data summer camp for 40 middle and high school students. The next generation of problem solvers is learning new data science skills by working on food safety and other projects using USDA open data.

Enhancing connection

Ultimately, technology enables greater communication and collaboration among the public, social service organizations, restaurants, farmers and other food producers who must work together to avoid food crises. The European Food Safety Authority in Italy has begun exploring how to use internet-based collaboration (often called citizen science or crowdsourcing) to get more people involved in food and feed risk assessment.

In the United States, 40 percent of the food produced here is wasted, and yet 1 in 4 American children (and 1 in 6 adults) remain food insecure, according to the Rockefeller Foundation. Copia, a San Francisco based smartphone app facilitates donations and deliveries of those with excess food in six cities in the Bay Area. Zero Percent in Chicago similarly attacks the distribution problem by connecting restaurants to charities to donate their excess food. Full Harvest is a tech platform that facilitates the selling of surplus produce that otherwise would not have a market.

Mobilizing the world

Prize-backed challenges create the incentives for more people to collaborate online and get involved in the fight against hunger….(More)”

Beware of the gaps in Big Data

Curated on Posted on by Stefaan Verhulst

Edd Gent at E&T: “When the municipal authority in charge of Boston, Massachusetts, was looking for a smarter way to find which roads it needed to repair, it hit on the idea of crowdsourcing the data. The authority released a mobile app called Street Bump in 2011 that employed an elegantly simple idea: use a smartphone’s accelerometer to detect jolts as cars go over potholes and look up the location using the Global Positioning System. But the approach ran into a pothole of its own.The system reported a disproportionate number of potholes in wealthier neighbourhoods. It turned out it was oversampling the younger, more affluent citizens who were digitally clued up enough to download and use the app in the first place. The city reacted quickly, but the incident shows how easy it is to develop a system that can handle large quantities of data but which, through its own design, is still unlikely to have enough data to work as planned.

As we entrust more of our lives to big data analytics, automation problems like this could become increasingly common, with their errors difficult to spot after the fact. Systems that ‘feel like they work’ are where the trouble starts.

Harvard University professor Gary King, who is also founder of social media analytics company Crimson Hexagon, recalls a project that used social media to predict unemployment. The model was built by correlating US unemployment figures with the frequency that people used words like ‘jobs’, ‘unemployment’ and ‘classifieds’. A sudden spike convinced researchers they had predicted a big rise in joblessness, but it turned out Steve Jobs had died and their model was simply picking up posts with his name. “This was an example of really bad analytics and it’s even worse because it’s the kind of thing that feels like it should work and does work a little bit,” says King.

Big data can shed light on areas with historic information deficits, and systems that seem to automatically highlight the best course of action can be seductive for executives and officials. “In the vacuum of no decision any decision is attractive,” says Jim Adler, head of data at Toyota Research Institute in Palo Alto. “Policymakers will say, ‘there’s a decision here let’s take it’, without really looking at what led to it. Was the data trustworthy, clean?”…(More)”

The Internet for farmers without Internet

Curated on Posted on by Stefaan Verhulst

Project Breakthrough: “Mobile Internet is rapidly becoming a primary source of knowledge for rural populations in developing countries. But not every one of the world’s 500 million smallholder farmers is connected to the Internet – which means they can struggle to solve daily agricultural challenges. With no way to access to information on things like planting, growing and selling, farmers in Asia, Latin America and Africa simply cannot grow. Many live on less than a dollar a day and don’t have smartphones to ask Google what to do.

London-based startup WeFarm is the world’s first free peer-to-peer network that spreads crowdsourced knowledge via SMS messages, which only need simple mobile phones. Since launching in November 2015, its aim has been to give remote, offline farmers access to the vital innovative insight, such as crop diversification, tackling soil erosion or changing climatic conditions. Billing itself as ‘The internet for people without the internet’, WeFarm strongly believes in the power of grassroots information. That’s why it costs nothing.

“With WeFarm we want all farmers in the world to be able to search for and access the information they need to improve their livelihoods,” Kenny Ewan, CEO tells us. The seeds for his idea were planted after many years working with indigenous communities in Latin America, based in Peru. “To me it makes perfect sense to allow farmers to connect with other farmers in order to find solutions to their problems. These farmers are experts in agriculture, and they come up with low-cost, innovative solutions, that are easy to implement.”

Farmers send questions by SMS to a local WeFarm number. Then they are connected to a huge crowdsourcing platform. The network’s back-end uses machine-learning algorithms to match them to farmers with answers. This data creates a sort of Google for agriculture…(More)”

The Wisdom of the Crowd is what science really needs

Curated on Posted on by Stefaan Verhulst

Science/Disrupt: “In a world where technology allows for global collaboration, and in a time when we’re finally championing diversity of thought, there are few barriers to getting the right people together to work on some of our most pressing problems. Governments and research labs are attempting to apply this mentality to science through what is known as ‘Citizen Science’ – research conducted in part by the public (amateur scientists) in partnership with the professionals.

The concept of Citizen Science is brilliant: moving science forward, faster, by utilising the wisdom and volume of the crowd. …

But Citizen Science goes beyond working directly with people with specific data to share. Zooniverse – the home of Citizen Science online – lists hundreds of projects which anyone can get involved with to help advance science. From mapping the galaxy and looking for comets, to seeking outAustralian wildlife and helping computers understand animal faces, the projects span across many subjects.

But when you dig deeper into the tasks being asked of these CitizenScientists, you find that – really – it’s a simple data capture activity. There’s no skill involved other than engaging your eyes to see and fingers to click and type. It’s not the wisdom of the crowd which is being tapped into.

You could argue that people are interested purely in being a part of important research – which of course is true for many – but it misses the point that scientists are simply missing out on a great resource of intellect at their fingertips.

There has been a rise of crowdsourced solutions over the last few years. rLoopis an organisation formed over Reddit to propose a Hyperloop transportation capsule; Techfugees is a Global community of technologists who team up to propose and build solutions to problems facing the increasing numbers of refugees around the world;  and XPRIZE is an open competition offering winning teams large sums of money and support to solve the global problems they select each year.

The difference between crowdsourcing and Citizen Science is that in the former, a high value is placed on ideas. There’s a general understanding that‘two minds are better than one’ and that by empowering a larger, more diverse pool of people to engage with important and purposeful work, a better solution will be found faster.

With Citizen Science, the mood is that of the public only being capable of playing hide and seek with pictures and completing menial, time consuming work that the scientists are simply too busy to do. …(More)”

Crowdsourcing: It Matters Who the Crowd Are

Curated on Posted on by Stefaan Verhulst

Paper by Alexis Comber, Peter Mooney, Ross S. Purves, Duccio Rocchini, and Ariane Walz: “Volunteered geographical information (VGI) and citizen science have become important sources data for much scientific research. In the domain of land cover, crowdsourcing can provide a high temporal resolution data to support different analyses of landscape processes. However, the scientists may have little control over what gets recorded by the crowd, providing a potential source of error and uncertainty. This study compared analyses of crowdsourced land cover data that were contributed by different groups, based on nationality (labelled Gondor and Non-Gondor) and on domain experience (labelled Expert and Non-Expert). The analyses used a geographically weighted model to generate maps of land cover and compared the maps generated by the different groups. The results highlight the differences between the maps how specific land cover classes were under- and over-estimated. As crowdsourced data and citizen science are increasingly used to replace data collected under the designed experiment, this paper highlights the importance of considering between group variations and their impacts on the results of analyses. Critically, differences in the way that landscape features are conceptualised by different groups of contributors need to be considered when using crowdsourced data in formal scientific analyses. The discussion considers the potential for variation in crowdsourced data, the relativist nature of land cover and suggests a number of areas for future research. The key finding is that the veracity of citizen science data is not the critical issue per se. Rather, it is important to consider the impacts of differences in the semantics, affordances and functions associated with landscape features held by different groups of crowdsourced data contributors….(More)”

How Citizen Attachment to Neighborhoods Helps to Improve Municipal Services and Public Spaces

Curated on Posted on by Stefaan Verhulst

Paper by Daniel O’Brien, Dietmar Offenhuber, Jessica Baldwin-Philippi, Melissa Sands, and Eric Gordon: “What motivates people to contact their local governments with reports about street light outages, potholes, graffiti, and other deteriorations in public spaces? Current efforts to improve government interactions with constituents operate on the premise that citizens who make such reports are motivated by broad civic values. In contrast, our recent research demonstrates that such citizens are primarily motivated by territoriality – that is, attachments to the spaces where they live. Our research focuses on Boston’s “311 system,” which provides telephone hotlines and web channels through which constituents can request non-emergency government services.

Although our study focuses on 311 users in Boston, it holds broader implications for more than 400 U.S. municipalities that administer similar systems. And our results encourage a closer look at the drivers of citizen participation in many “coproduction programs” – programs that involve people in the design and implementation of government services. Currently, 311 is just one example of government efforts to use technology to involve constituents in joint efforts.

Territorial Ties and Civic Engagement

The concept of territoriality originated in studies of animal behavior – such as bears marking trees in the forest or lions and hyenas fighting over a kill. Human beings also need to manage the ownership of objects and spaces, but social psychologists have demonstrated that human territoriality, whether at home, the workplace, or a neighborhood, entails more than the defense of objects or spaces against others. It includes maintenance and caretaking, and even extends to items shared with others….(More)”

Encouraging and Sustaining Innovation in Government: Technology and Innovation in the Next Administration

Curated on Posted on by Stefaan Verhulst

New report by Beth Simone Noveck and Stefaan Verhulst: “…With rates of trust in government at an all-time low, technology and innovation will be essential to achieve the next administration’s goals and to deliver services more effectively and efficiently. The next administration must prioritize using technology to improve governing and must develop plans to do so in the transition… This paper provides analysis and a set of concrete recommendations, both for the period of transition before the inauguration, and for the start of the next presidency, to encourage and sustain innovation in government. Leveraging the insights from the experts who participated in a day-long discussion, we endeavor to explain how government can improve its use of using digital technologies to create more effective policies, solve problems faster and deliver services more effectively at the federal, state and local levels….

The broad recommendations are:

  • Scale Data Driven Governance: Platforms such as data.gov represent initial steps in the direction of enabling data-driven governance. Much more can be done, however, to open-up data and for the agencies to become better consumers of data, to improve decision-making and scale up evidence-based governance. This includes better use of predictive analytics, more public engagement; and greater use of cutting-edge methods like machine learning.
  • Scale Collaborative Innovation: Collaborative innovation takes place when government and the public work together, thus widening the pool of expertise and knowledge brought to bear on public problems. The next administration can reach out more effectively, not just to the public at large, but to conduct targeted outreach to public officials and citizens who possess the most relevant skills or expertise for the problems at hand.
  • Promote a Culture of Innovation: Institutionalizing a culture of technology-enabled innovation will require embedding and institutionalizing innovation and technology skills more widely across the federal enterprise. For example, contracting, grants and personnel officials need to have a deeper understanding of how technology can help them do their jobs more efficiently, and more people need to be trained in human-centered design, gamification, data science, data visualization, crowdsourcing and other new ways of working.
  • Utilize Evidence-Based Innovation: In order to better direct government investments, leaders need a much better sense of what works and what doesn’t. The government spends billions on research in the private and university sectors, but very little experimenting with, testing, and evaluating its own programs. The next administration should continue developing an evidence-based approach to governance, including a greater use of methods like A/B testing (a method of comparing two versions of a webpage or app against each other to determine which one performs the best); establishing a clearinghouse for success and failure stories and best practices; and encouraging overseers to be more open to innovation.
  • Make Innovation a Priority in the Transition: The transition period represents a unique opportunity to seed the foundations for long-lasting change. By explicitly incorporating innovation into the structure, goals and activities of the transition teams, the next administration can get a fast start in implementing policy goals and improving government operations through innovation approaches….(More)”

Questioning Big Data: Crowdsourcing crisis data towards an inclusive humanitarian response

Curated on Posted on by Stefaan Verhulst

Femke Mulder, Julie Ferguson, Peter Groenewegen, Kees Boersma, and Jeroen Wolbers in Big Data and Society: “The aim of this paper is to critically explore whether crowdsourced Big Data enables an inclusive humanitarian response at times of crisis. We argue that all data, including Big Data, are socially constructed artefacts that reflect the contexts and processes of their creation. To support our argument, we qualitatively analysed the process of ‘Big Data making’ that occurred by way of crowdsourcing through open data platforms, in the context of two specific humanitarian crises, namely the 2010 earthquake in Haiti and the 2015 earthquake in Nepal. We show that the process of creating Big Data from local and global sources of knowledge entails the transformation of information as it moves from one distinct group of contributors to the next. The implication of this transformation is that locally based, affected people and often the original ‘crowd’ are excluded from the information flow, and from the interpretation process of crowdsourced crisis knowledge, as used by formal responding organizations, and are marginalized in their ability to benefit from Big Data in support of their own means. Our paper contributes a critical perspective to the debate on participatory Big Data, by explaining the process of in and exclusion during data making, towards more responsive humanitarian relief….(More)”.

Counterterrorism and Counterintelligence: Crowdsourcing Approach

Curated on Posted on by Stefaan Verhulst

Literature review by Sanket Subhash Khanwalkar: “Despite heavy investment by the United States and several other national governments, terrorism related problems are rising at an alarming rate. Lone-wolf terrorism, in particular, in the last decade, has caused 70% of all terrorism related deaths in the US and the West. This literature survey describes lone-wolf terrorism in detail to analyse its structure, characteristics, strengths and weaknesses. It also investigates crowdsourcing intelligence, as an unorthodox approach to counter lone-wolf terrorism, by reviewing its current state-of-the-art and identifying the areas for improvement….(More)”

An investigation of unpaid crowdsourcing

Curated on Posted on by Stefaan Verhulst

Chapter by Ria Mae Borromeo and Motomichi Toyama in Human-centric Computing and Information Sciences: “The continual advancement of internet technologies has led to the evolution of how individuals and organizations operate. For example, through the internet, we can now tap a remote workforce to help us accomplish certain tasks, a phenomenon called crowdsourcing. Crowdsourcing is an approach that relies on people to perform activities that are costly or time-consuming using traditional methods. Depending on the incentive given to the crowd workers, crowdsourcing can be classified as paid or unpaid. In paid crowdsourcing, the workers are incentivized financially, enabling the formation of a robust workforce, which allows fast completion of tasks. Consequently, in unpaid crowdsourcing, the lack of financial incentive potentially leads to an unpredictable workforce and indeterminable task completion time. However, since payment to workers is not necessary, it can be an economical alternative for individuals and organizations who are more concerned about the budget than the task turnaround time. In this study, we explore unpaid crowdsourcing by reviewing crowdsourcing applications where the crowd comes from a pool of volunteers. We also evaluate its performance in sentiment analysis and data extraction projects. Our findings suggest that for such tasks, unpaid crowdsourcing completes slower but yields results of similar or higher quality compared to its paid counterpart…(More)”