Ana Maria Barral et al in FASEB Journal: “The Small World Initiative™ (SWI) is an innovative program that encourages students to pursue careers in science and sets forth a unique platform to crowdsource new antibiotics. It centers around an introductory biology course through which students perform original hands-on field and laboratory research in the hunt for new antibiotics. Through a series of student-driven experiments, students collect soil samples, isolate diverse bacteria, test their bacteria against clinically-relevant microorganisms, and characterize those showing inhibitory activity. This is particularly relevant since over two thirds of antibiotics originate from soil bacteria or fungi. SWI’s approach also provides a platform to crowdsource antibiotic discovery by tapping into the intellectual power of many people concurrently addressing a global challenge and advances promising candidates into the drug development pipeline. This unique class approach harnesses the power of active learning to achieve both educational and scientific goals…..We will discuss our preliminary student evaluation results, which show the compelling impact of the program in comparison to traditional introductory courses. Ultimately, the mission of the program is to provide an evidence-based approach to teaching introductory biology concepts in the context of a real-world problem. This approach has been shown to be particularly impactful on underrepresented STEM talent pools, including women and minorities….(More)”
Global sharing of HIV vaccine research
Springwise: “Noticing that a global, collaborative effort is missing in the world of HIV vaccine research, scientists came together to make it a reality. Populated by research from the Collaboration for AIDS Vaccine Discovery — an international network of laboratories — DataSpace is a partnership between the Statistical Center for HIV/AIDS Research and Prevention, data management and software development company LabKey, and technology product development company Artefact.
Through pooled research results, scientists hope to make data more accessible and comparable. Two aspects make the platform particularly powerful. The Artefact team hand-coded a number of research points to allow results from multiple studies to be compared like-for-like. And rather than discard the findings of failed or inconclusive studies, DataSpace includes them in analysis, vastly increasing the volume of available information.
Material is added as study results become available, creating a constantly developing resource. Being able to quickly test ideas online helps researchers make serendipitous connections and avoid duplicating efforts….(More)”
Insights On Collective Problem-Solving: Complexity, Categorization And Lessons From Academia
Part 3 of an interview series by Henry Farrell for the MacArthur Research Network on Opening Governance: “…Complexity theorists have devoted enormous energy and attention to thinking about how complex problems, in which different factors interact in ways that are hard to predict, can best be solved. One key challenge is categorizing problems, so as to understand which approaches are best suited to addressing them.
Scott Page is the Leonid Hurwicz Collegiate Professor of Complex Systems at the University of Michigan, Ann Arbor, and one of the world’s foremost experts on diversity and problem-solving. I asked him a series of questions about how we might use insights from academic research to think better about how problem solving works.
Henry: One of the key issues of collective problem-solving is what you call the ‘problem of problems’ – the question of identifying which problems we need to solve. This is often politically controversial – e.g., it may be hard to get agreement that global warming, or inequality, or long prison sentences are a problem. How do we best go about identifying problems, given that people may disagree?
Scott: In a recent big think paper on the potential of diversity for collective problem solving in Scientific American, Katherine Phillips writes that group members must feel validated, that they must share a commitment to the group, and they must have a common goal if they are going to contribute. This implies that you won’t succeed in getting people to collaborate by setting an agenda from on high and then seeking to attract diverse people to further that agenda.
One way of starting to tackle the problem of problems is to steal a rule of thumb from Getting to Yes, by getting to think people about their broad interests rather than the position that they’re starting from. People often agree on their fundamental desires but disagree on how they can be achieved. For example, nearly everyone wants less crime, but they may disagree over whether they think the solution to crime involves tackling poverty or imposing longer prison sentences. If you can get them to focus on their common interest in solving crime rather than their disagreements, you’re more likely to get them to collaborate usefully.
Segregation amplifies the problem of problems. We live in towns and neighborhoods segregated by race, income, ideology, and human capital. Democrats live near Democrats and Republicans near Republicans. Consensus requires integration. We must work across ideologies. Relatedly, opportunity requires more than access. Many people grow up not knowing any engineers, dentists, doctors, lawyers, and statisticians. This isolation narrows the set of careers they consider and it reduces the diversity of many professions. We cannot imagine lives we do not know.
Henry: Once you get past the problem of problems, you still need to identify which kind of problem you are dealing with. You identify three standard types of problems: solution problems, selection problems and optimization problems. What – very briefly – are the key differences between these kinds of problems?
Scott: I’m constantly pondering the potential set of categories in which collective intelligence can emerge. I’m teaching a course on collective intelligence this semester and the undergraduates and I developed an acronym SCARCE PIGS to describe the different types of domains. Here’s the brief summary:
- Predict: when individuals combine information, models, or measurements to estimate a future event, guess an answer, or classify an event. Examples might involve betting markets, or combined efforts to guess a quantity, such as Francis Galton’s example of people at a fair trying to guess the weight of a steer.
- Identify: when individuals have local, partial, or possibly erroneous knowledge and collectively can find an object. Here, an example is DARPA’s Red Balloon project.
- Solve: when individuals apply and possibly combine higher order cognitive processes and analytic tools for the purpose of finding or improving a solution to a task. Innocentive and similar organizations provide examples of this.
- Generate: when individuals apply diverse representations, heuristics, and knowledge to produce something new. An everyday example is creating a new building.
- Coordinate: when individuals adopt similar actions, behaviors, beliefs, or mental frameworks by learning through local interactions. Ordinary social conventions such as people greeting each other are good examples.
- Cooperate: when individuals take actions, not necessarily in their self interest, that collectively produce a desirable outcome. Here, think of managing common pool resources (e.g. fishing boats not overfishing an area that they collectively control).
- Arrange: when individuals manipulate items in a physical or virtual environment for their own purposes resulting in an organization of that environment. As an example, imagine a student co-op which keeps twenty types of hot sauce in its pantry. If each student puts whichever hot sauce she uses in the front of the pantry, then on average, the hot sauces will be arranged according to popularity, with the most favored hot sauces in the front and the least favored lost in the back.
- Respond: when individuals react to external or internal stimuli creating collective responses that maintains system level functioning. For example, when yellow jackets attack a predator to maintain the colony, they are displaying this kind of problem solving.
- Emerge: when individual parts create a whole that has categorically distinct and new functionalities. The most obvious example of this is the human brain….(More)”
The Biggest Hope for Ending Corruption Is Open Public Contracting
Gavin Hayman at the Huffington Post: “This week the British Prime Minister David Cameron is hosting an international anti-corruption summit. The scourge of anonymous shell companies and hidden identities rightly seizes the public’s imagination. We can all picture the suitcases of cash and tropical islands involved. As well as acting on offshore and onshore money laundering havens, world leaders at the summit should also be asking themselves where all this money is being stolen from in the first place.
The answer is mostly from public contracting: government spending through private companies to deliver works, goods and services to citizens. It is technical, dull and universally obscure. But it is the single biggest item of spending by government – amounting to a staggering $9,500,000,000,000 each year. This concentration of money, government discretion, and secrecy makes public contracting so vulnerable to corruption. Data on prosecutions tracked by the OECD Anti-Bribery Convention shows that roughly 60% of bribes were paid to win public contracts.
Corruption in contracting deprives ordinary people of vital goods and services, and sometimes even kills: I was one of many Londoners moved by Ai Wei Wei’s installation that memorialised the names of thousands of children killed in China’s Sichuan earthquake in 2008. Their supposed earthquake-proof schools collapsed on them like tofu.
Beyond corruption, inefficiency and mismanagement of public contracts cost countries billions. Governments just don’t seem to know what they are buying, when, from whom, and whether they got a good price.
This problem can be fixed. But it will require a set of innovations best described as open contracting: using accessible open data and better engagement so that citizens, government and business can follow the money in government contracts from planning to tendering to performance and closure. The coordination required can be hard work but it is achievable: any country can make substantial progress on open contracting with some political leadership. My organisation supports an open data standard and a free global helpdesk to assist governments, civil society, and business in this transition….(More)”
Global governance and ICTs: exploring online governance networks around gender and media
Claudia Padovani and Elena Pavan in the journal “Global Networks“: In this article, we address transformations in global governance brought about by information and communication technologies (ICTs). Focusing on the specific domain of ‘gender-oriented communication governance’, we investigate online interactions among different kinds of actors active in promoting gender equity in and through the media. By tracing and analysing online issue networks, we investigate which actors are capable of influencing the framing of issues and of structuring discursive practices. From the analysis, different forms of power emerge, reflecting diverse modes of engaging in online interactions, where actors can operate as network ‘programmers’, ‘mobilizers’, or ‘switchers’. Our case study suggests that, often, old ways of conceiving actors’ interactions accompany the implementation of new communication tools, while the availability of a pervasive networked infrastructure does not automatically translate into meaningful interactions among all relevant actors in a specific domain….(More)”
The New Power Politics: Networks and Transnational Security Governance
Book edited by Deborah Avant and Oliver Westerwinter: “Traditional analyses of global security cannot explain the degree to which there is “governance” of important security issues — from combatting piracy to curtailing nuclear proliferation to reducing the contributions of extractive industries to violence and conflict. They are even less able to explain why contemporary governance schemes involve the various actors and take the many forms they do.
Juxtaposing the insights of scholars writing about new modes of governance with the logic of network theory, The New Power Politics offers a framework for understanding contemporary security governance and its variation. The framework rests on a fresh view of power and how it works in global politics. Though power is integral to governance, it is something that emerges from, and depends on, relationships. Thus, power is dynamic; it is something that governors must continually cultivate with a wide range of consequential global players, and how a governor uses power in one situation can have consequences for her future relationships, and thus, future power.
Understanding this new power politics is crucial for explaining and shaping the future of global security politics. This stellar group of scholars analyzes both the networking strategies of would-be governors and their impacts on the effectiveness of governance and whether it reflects broad or narrow concerns on a wide range of contemporary governance issues….(More)”
‘Big data’ was supposed to fix education. It didn’t. It’s time for ‘small data’
Pasi Sahlberg and Jonathan Hasak in the Washington Post: “One thing that distinguishes schools in the United States from schools around the world is how data walls, which typically reflect standardized test results, decorate hallways and teacher lounges. Green, yellow, and red colors indicate levels of performance of students and classrooms. For serious reformers, this is the type of transparency that reveals more data about schools and is seen as part of the solution to how to conduct effective school improvement. These data sets, however, often don’t spark insight about teaching and learning in classrooms; they are based on analytics and statistics, not on emotions and relationships that drive learning in schools. They also report outputs and outcomes, not the impacts of learning on the lives and minds of learners….
If you are a leader of any modern education system, you probably care a lot about collecting, analyzing, storing, and communicating massive amounts of information about your schools, teachers, and students based on these data sets. This information is “big data,” a term that first appeared around 2000, which refers to data sets that are so large and complex that processing them by conventional data processing applications isn’t possible. Two decades ago, the type of data education management systems processed were input factors of education system, such as student enrollments, teacher characteristics, or education expenditures handled by education department’s statistical officer. Today, however, big data covers a range of indicators about teaching and learning processes, and increasingly reports on student achievement trends over time.
With the outpouring of data, international organizations continue to build regional and global data banks. Whether it’s the United Nations, the World Bank, the European Commission, or the Organization for Economic Cooperation and Development, today’s international reformers are collecting and handling more data about human development than before. Beyond government agencies, there are global education and consulting enterprises like Pearson and McKinsey that see business opportunities in big data markets.
Among the best known today is the OECD’s Program for International Student Assessment (PISA), which measures reading, mathematical, and scientific literacy of 15-year-olds around the world. OECD now also administers an Education GPS, or a global positioning system, that aims to tell policymakers where their education systems place in a global grid and how to move to desired destinations. OECD has clearly become a world leader in the big data movement in education.
Despite all this new information and benefits that come with it, there are clear handicaps in how big data has been used in education reforms. In fact, pundits and policymakers often forget that Big data, at best, only reveals correlations between variables in education, not causality. As any introduction to statistics course will tell you, correlation does not imply causation….
We believe that it is becoming evident that big data alone won’t be able to fix education systems. Decision-makers need to gain a better understanding of what good teaching is and how it leads to better learning in schools. This is where information about details, relationships and narratives in schools become important. These are what Martin Lindstrom calls “small data”: small clues that uncover huge trends. In education, these small clues are often hidden in the invisible fabric of schools. Understanding this fabric must become a priority for improving education.
To be sure, there is not one right way to gather small data in education. Perhaps the most important next step is to realize the limitations of current big data-driven policies and practices. Too strong reliance on externally collected data may be misleading in policy-making. This is an example of what small data look like in practice:
- It reduces census-based national student assessments to the necessary minimum and transfer saved resources to enhance the quality of formative assessments in schools and teacher education on other alternative assessment methods. Evidence shows that formative and other school-based assessments are much more likely to improve quality of education than conventional standardized tests.
- It strengthens collective autonomy of schools by giving teachers more independence from bureaucracy and investing in teamwork in schools. This would enhance social capital that is proved to be critical aspects of building trust within education and enhancing student learning.
- It empowers students by involving them in assessing and reflecting their own learning and then incorporating that information into collective human judgment about teaching and learning (supported by national big data). Because there are different ways students can be smart in schools, no one way of measuring student achievement will reveal success. Students’ voices about their own growth may be those tiny clues that can uncover important trends of improving learning.
Edwards Deming once said that “without data you are another person with an opinion.” But Deming couldn’t have imagined the size and speed of data systems we have today….(More)”
Can Crowdsourcing Help Make Life Easier For People With Disabilities?
Sean Captain at FastCompany: “These days GPS technology can get you as close as about 10 feet from your destination, close enough to see it—assuming you can see.
But those last few feet are a chasm for the blind (and GPS accuracy sometimes falls only within about 30 feet).
“Actually finding the bus stop, not the right street, but standing in the right place when the bus comes, is pretty hard,” says Dave Power, president and CEO of the Perkins School for the Blind near Boston. Helen Keller’s alma mater is developing a mobile app that will provide audio directions—contributed by volunteers—so that blind people can get close enough to the stop for the bus driver to notice them.
Perkins’s app is one of 29 projects that recently received a total of $20 million in funding from Google.org’s Google Impact Challenge: Disabilities awards. Several of the winning initiatives rely on crowdsourced information to help the disabled—be they blind, in a wheelchair, or cognitively impaired. It’s a commonsense approach to tackling big logistical projects in a world full of people who have snippets of downtime during which they might perform bite-size acts of kindness online. But moving these projects from being just clever concepts to extensive services, based on the goodwill of volunteers, is going to be quite a hurdle.
People with limited mobility may have trouble traversing the last few feet between them and a wheelchair ramp, automatic doors, or other accommodations that aren’t easy to find (or may not even exist in some places).Wheelmap, based in Berlin, is trying to help by building online maps of accessible locations. Its website incorporates crowdsourced data. The site lets users type in a city and search for accessible amenities such as restaurants, hotels, and public transit.
Paris-based J’accede (which received 500,000 euros from Google, which is the equivalent of about $565,000) provides similar capabilities in both a website and an app, with a slicker design somewhat resembling TripAdvisor.
Both services have a long way to go. J’accede lists 374 accessible bars/restaurants in its hometown and a modest selection in other French cities like Marseille. “We still have a lot of work to do to cover France,” says J’accede’s president Damien Birambeau in an email. The goal is to go global though, and the site is available in English, German, and Spanish, in addition to French. Likewise, Wheelmap (which got 825,000 euros, or $933,000) performs best in the German capital of Berlin and cities like Hamburg, but is less useful in other places.
These sites face the same challenge as many other volunteer-based, crowdsourced projects: getting a big enough crowd to contribute information to the service. J’accede hopes to make the process easier. In June, it will connect itself with Google Places, so contributors will only need to supply details about accommodations at a site; information like the location’s address and phone number will be pulled in automatically. But both J’accede and Wheelmap recognize that crowdsourcing has its limits. They are now going beyond voluntary contributions, setting up automated systems to scrape information from other databases of accessible locations, such as those maintained by governments.
Wheelmap and J’accede are dwarfed by general-interest crowdsourced sites like TripAdvisor and Yelp, which offer some information about accessibility, too. For instance, among the many filters they offer users searching for restaurants—such as price range and cuisine type—TripAdvisor and Yelp both offer a Wheelchair Accessible checkbox. Applying that filter to Parisian establishments brings up about 1,000 restaurants on TripAdvisor and 2,800 in Yelp.
So what can Wheelmap and J’accede provide that the big players can’t? Details. “A person in a wheelchair, for example, will face different obstacles than a partially blind person or a person with cognitive disabilities,” says Birambeau. “These different needs and profiles means that we need highly detailed information about the accessibility of public places.”…(More)”
Hail the maintainers
Andrew Russell & Lee Vinsel at AEON: “The trajectory of ‘innovation’ from core, valued practice to slogan of dystopian societies, is not entirely surprising, at a certain level. There is a formulaic feel: a term gains popularity because it resonates with the zeitgeist, reaches buzzword status, then suffers from overexposure and cooptation. Right now, the formula has brought society to a question: after ‘innovation’ has been exposed as hucksterism, is there a better way to characterise relationships between society and technology?
There are three basic ways to answer that question. First, it is crucial to understand that technology is not innovation. Innovation is only a small piece of what happens with technology. This preoccupation with novelty is unfortunate because it fails to account for technologies in widespread use, and it obscures how many of the things around us are quite old. In his book, Shock of the Old (2007), the historian David Edgerton examines technology-in-use. He finds that common objects, like the electric fan and many parts of the automobile, have been virtually unchanged for a century or more. When we take this broader perspective, we can tell different stories with drastically different geographical, chronological, and sociological emphases. The stalest innovation stories focus on well-to-do white guys sitting in garages in a small region of California, but human beings in the Global South live with technologies too. Which ones? Where do they come from? How are they produced, used, repaired? Yes, novel objects preoccupy the privileged, and can generate huge profits. But the most remarkable tales of cunning, effort, and care that people direct toward technologies exist far beyond the same old anecdotes about invention and innovation.
Second, by dropping innovation, we can recognise the essential role of basic infrastructures. ‘Infrastructure’ is a most unglamorous term, the type of word that would have vanished from our lexicon long ago if it didn’t point to something of immense social importance. Remarkably, in 2015 ‘infrastructure’ came to the fore of conversations in many walks of American life. In the wake of a fatal Amtrak crash near Philadelphia, President Obama wrestled with Congress to pass an infrastructure bill that Republicans had been blocking, but finally approved in December 2015. ‘Infrastructure’ also became the focus of scholarly communities in history and anthropology, even appearing 78 times on the programme of the annual meeting of the American Anthropological Association. Artists, journalists, and even comedians joined the fray, most memorably with John Oliver’s hilarious sketch starring Edward Norton and Steve Buscemi in a trailer for an imaginary blockbuster on the dullest of subjects. By early 2016, the New York Review of Books brought the ‘earnest and passive word’ to the attention of its readers, with a depressing essay titled ‘A Country Breaking Down’.
Despite recurring fantasies about the end of work, the central fact of our industrial civilisation is labour, most of which falls far outside the realm of innovation
The best of these conversations about infrastructure move away from narrow technical matters to engage deeper moral implications. Infrastructure failures – train crashes, bridge failures, urban flooding, and so on – are manifestations of and allegories for America’s dysfunctional political system, its frayed social safety net, and its enduring fascination with flashy, shiny, trivial things. But, especially in some corners of the academic world, a focus on the material structures of everyday life can take a bizarre turn, as exemplified in work that grants ‘agency’ to material things or wraps commodity fetishism in the language of high cultural theory, slick marketing, and design. For example, Bloomsbury’s ‘Object Lessons’ series features biographies of and philosophical reflections on human-built things, like the golf ball. What a shame it would be if American society matured to the point where the shallowness of the innovation concept became clear, but the most prominent response was an equally superficial fascination with golf balls, refrigerators, and remote controls.
Third, focusing on infrastructure or on old, existing things rather than novel ones reminds us of the absolute centrality of the work that goes into keeping the entire world going…..
We organised a conference to bring the work of the maintainers into clearer focus. More than 40 scholars answered a call for papers asking, ‘What is at stake if we move scholarship away from innovation and toward maintenance?’ Historians, social scientists, economists, business scholars, artists, and activists responded. They all want to talk about technology outside of innovation’s shadow.
One important topic of conversation is the danger of moving too triumphantly from innovation to maintenance. There is no point in keeping the practice of hero-worship that merely changes the cast of heroes without confronting some of the deeper problems underlying the innovation obsession. One of the most significant problems is the male-dominated culture of technology, manifest in recent embarrassments such as the flagrant misogyny in the ‘#GamerGate’ row a couple of years ago, as well as the persistent pay gap between men and women doing the same work.
There is an urgent need to reckon more squarely and honestly with our machines and ourselves. Ultimately, emphasising maintenance involves moving from buzzwords to values, and from means to ends. In formal economic terms, ‘innovation’ involves the diffusion of new things and practices. The term is completely agnostic about whether these things and practices are good. Crack cocaine, for example, was a highly innovative product in the 1980s, which involved a great deal of entrepreneurship (called ‘dealing’) and generated lots of revenue. Innovation! Entrepreneurship! Perhaps this point is cynical, but it draws our attention to a perverse reality: contemporary discourse treats innovation as a positive value in itself, when it is not.
Entire societies have come to talk about innovation as if it were an inherently desirable value, like love, fraternity, courage, beauty, dignity, or responsibility. Innovation-speak worships at the altar of change, but it rarely asks who benefits, to what end? A focus on maintenance provides opportunities to ask questions about what we really want out of technologies. What do we really care about? What kind of society do we want to live in? Will this help get us there? We must shift from means, including the technologies that underpin our everyday actions, to ends, including the many kinds of social beneficence and improvement that technology can offer. Our increasingly unequal and fearful world would be grateful….(More)”
Citizen scientists aid Ecuador earthquake relief
Mark Zastrow at Nature: “After a magnitude-7.8 earthquake struck Ecuador’s Pacific coast on 16 April, a new ally joined the international relief effort: a citizen-science network called Zooniverse.
On 25 April, Zooniverse launched a website that asks volunteers to analyse rapidly-snapped satellite imagery of the disaster, which led to more than 650 reported deaths and 16,000 injuries. The aim is to help relief workers on the ground to find the most heavily damaged regions and identify which roads are passable.
Several crisis-mapping programmes with thousands of volunteers already exist — but it can take days to train satellites on the damaged region and to transmit data to humanitarian organizations, and results have not always proven useful. The Ecuador quake marked the first live public test for an effort dubbed the Planetary Response Network (PRN), which promises to be both more nimble than previous efforts, and to use more rigorous machine-learning algorithms to evaluate the quality of crowd-sourced analyses.
The network relies on imagery from the satellite company Planet Labs in San Francisco, California, which uses an array of shoebox-sized satellites to map the planet. In order to speed up the crowd-sourced process, it uses the Zooniverse platform to distribute the tasks of spotting features in satellite images. Machine-learning algorithms employed by a team at the University of Oxford, UK, then classify the reliability of each volunteer’s analysis and weight their contributions accordingly.
Rapid-fire data
Within 2 hours of the Ecuador test project going live with a first set of 1,300 images, each photo had been checked at least 20 times. “It was one of the fastest responses I’ve seen,” says Brooke Simmons, an astronomer at the University of California, San Diego, who leads the image processing. Steven Reece, who heads the Oxford team’s machine-learning effort, says that results — a “heat map” of damage with possible road blockages — were ready in another two hours.
In all, more than 2,800 Zooniverse users contributed to analysing roughly 25,000 square kilometres of imagery centred around the coastal cities of Pedernales and Bahia de Caraquez. That is where the London-based relief organization Rescue Global — which requested the analysis the day after the earthquake — currently has relief teams on the ground, including search dogs and medical units….(More)”