Beth Noveck at Governing: “With complex, seemingly intractable problems such as inequality, climate change and affordable access to health care plaguing contemporary society, traditional institutions such as government agencies and nonprofit organizations often lack strategies for tackling them effectively and legitimately. For this reason, this year the MacArthur Foundation launched its Research Network on Opening Governance.
The Network, which I chair and which also is supported by Google.org, is what MacArthur calls a “research institution without walls.” It brings together a dozen researchers across universities and disciplines, with an advisory network of academics, technologists, and current and former government officials, to study new ways of addressing public problems using advances in science and technology.
Through regular meetings and collaborative projects, the Network is exploring, for example, the latest techniques for more open and transparent decision-making, the uses of data to transform how we govern, and the identification of an individual’s skills and experiences to improve collaborative problem-solving between government and citizen.
One of the central questions we are grappling with is how to accelerate the pace of research so we can learn better and faster when an innovation in governance works — for whom, in which contexts and under which conditions. With better methods for doing fast-cycle research in collaboration with government — in the wild, not in the lab — our hope is to be able to predict with accuracy, not just know after the fact, whether innovations such as opening up an agency’s data or consulting with citizens using a crowdsourcing platform are likely to result in real improvements in people’s lives.
An example of such an experiment is the work that members of the Network are undertaking with the Food and Drug Administration. As one of its duties, the FDA manages the process of pre-market approval of medical devices to ensure that patients and providers have timely access to safe, effective and high-quality technology, as well as the post-market review of medical devices to ensure that unsafe ones are identified and recalled from the market. In both of these contexts, the FDA seeks to provide the medical-device industry with productive, consistent, transparent and efficient regulatory pathways.
With thousands of devices, many of them employing cutting-edge technology, to examine each year, the FDA is faced with the challenge of finding the right internal and external expertise to help it quickly study a device’s safety and efficacy. Done right, lives can be saved and companies can prosper from bringing innovations quickly to market. Done wrong, bad devices can kill…”
Off the map
The Economist: “Rich countries are deluged with data; developing ones are suffering from drought…
AFRICA is the continent of missing data. Fewer than half of births are recorded; some countries have not taken a census in several decades. On maps only big cities and main streets are identified; the rest looks as empty as the Sahara. Lack of data afflicts other developing regions, too. The self-built slums that ring many Latin American cities are poorly mapped, and even estimates of their population are vague. Afghanistan is still using census figures from 1979—and that count was cut short after census-takers were killed by mujahideen.
As rich countries collect and analyse data from as many objects and activities as possible—including thermostats, fitness trackers and location-based services such as Foursquare—a data divide has opened up. The lack of reliable data in poor countries thwarts both development and disaster-relief. When Médecins Sans Frontières (MSF), a charity, moved into Liberia to combat Ebola earlier this year, maps of the capital, Monrovia, fell far short of what was needed to provide aid or track the disease’s spread. Major roads were marked, but not minor ones or individual buildings.
Poor data afflict even the highest-profile international development effort: the Millennium Development Goals (MDGs). The targets, which include ending extreme poverty, cutting infant mortality and getting all children into primary school, were set by UN members in 2000, to be achieved by 2015. But, according to a report by an independent UN advisory group published on November 6th, as the deadline approaches, the figures used to track progress are shaky. The availability of data on 55 core indicators for 157 countries has never exceeded 70%, it found (see chart)….
Some of the data gaps are now starting to be filled from non-government sources. A volunteer effort called Humanitarian OpenStreetMap Team (HOT) improves maps with information from locals and hosts “mapathons” to identify objects shown in satellite images. Spurred by pleas from those fighting Ebola, the group has intensified its efforts in Monrovia since August; most of the city’s roads and many buildings have now been filled in (see maps). Identifying individual buildings is essential, since in dense slums without formal roads they are the landmarks by which outbreaks can be tracked and assistance targeted.
On November 7th a group of charities including MSF, Red Cross and HOT unveiled MissingMaps.org, a joint initiative to produce free, detailed maps of cities across the developing world—before humanitarian crises erupt, not during them. The co-ordinated effort is needed, says Ivan Gayton of MSF: aid workers will not use a map with too little detail, and are unlikely, without a reason, to put work into improving a map they do not use. The hope is that the backing of large charities means the locals they work with will help.
In Kenya and Namibia mobile-phone operators have made call-data records available to researchers, who have used them to combat malaria. By comparing users’ movements with data on outbreaks, epidemiologists are better able to predict where the disease might spread. mTrac, a Ugandan programme that replaces paper reports from health workers with texts sent from their mobile phones, has made data on medical cases and supplies more complete and timely. The share of facilities that have run out of malaria treatments has fallen from 80% to 15% since it was introduced.
Private-sector data are also being used to spot trends before official sources become aware of them. Premise, a startup in Silicon Valley that compiles economics data in emerging markets, has found that as the number of cases of Ebola rose in Liberia, the price of staple foods soared: a health crisis risked becoming a hunger crisis. In recent weeks, as the number of new cases fell, prices did, too. The authorities already knew that travel restrictions and closed borders would push up food prices; they now have a way to measure and track price shifts as they happen….”
8 ideas for the future of cities
TED: “In 2012, the TED Prize was awarded to an idea: The City2.0, a place to celebrate actions taken by citizens around the world to make their cities more livable, beautiful and sustainable. This week, The City2.0 website evolves. On the relaunched TEDCity2.org, you’ll find great talks on topics like housing, education and food, and how they relate to life in the bustling metropolis. You’ll find video explorations of 10 award-winning local projects that received funding through this TED Prize wish, and resources for those hoping to spark change in their own cities. The site will also be the home of all future TEDCity2.0 projects. In other words, it’s an online haven for everyone who wants to create the city of the future.
Below, a sampling of the great ideas you’ll find on TEDCity2.org. Enjoy, as most of these have never been seen on TED.com before….”
Chicago uses big data to save itself from urban ills
Aviva Rutkin in the New Scientist: “THIS year in Chicago, some kids will get lead poisoning from the paint or pipes in their homes. Some restaurants will cook food in unsanitary conditions and, here and there, a street corner will be suddenly overrun with rats. These kinds of dangers are hard to avoid in a city of more than 2.5 million people. The problem is, no one knows for certain where or when they will pop up.
The Chicago city government is hoping to change that by knitting powerful predictive models into its everyday city inspections. Its latest project, currently in pilot tests, analyses factors such as home inspection records and census data, and uses the results to guess which buildings are likely to cause lead poisoning in children – a problem that affects around 500,000 children in the US each year. The idea is to identify trouble spots before kids are exposed to dangerous lead levels.
“We are able to prevent problems instead of just respond to them,” says Jay Bhatt, chief innovation officer at the Chicago Department of Public Health. “These models are just the beginning of the use of predictive analytics in public health and we are excited to be at the forefront of these efforts.”
Chicago’s projects are based on the thinking that cities already have what they need to raise their municipal IQ: piles and piles of data. In 2012, city officials built WindyGrid, a platform that collected data like historical facts about buildings and up-to-date streams such as bus locations, tweets and 911 calls. The project was designed as a proof of concept and was never released publicly but it led to another, called Plenario, that allowed the public to access the data via an online portal.
The experience of building those tools has led to more practical applications. For example, one tool matches calls to the city’s municipal hotline complaining about rats with conditions that draw rats to a particular area, such as excessive moisture from a leaking pipe, or with an increase in complaints about garbage. This allows officials to proactively deploy sanitation crews to potential hotspots. It seems to be working: last year, resident requests for rodent control dropped by 15 per cent.
Some predictions are trickier to get right. Charlie Catlett, director of the Urban Center for Computation and Data in Chicago, is investigating an old axiom among city cops: that violent crime tends to spike when there’s a sudden jump in temperature. But he’s finding it difficult to test its validity in the absence of a plausible theory for why it might be the case. “For a lot of things about cities, we don’t have that underlying theory that tells us why cities work the way they do,” says Catlett.
Still, predictive modelling is maturing, as other cities succeed in using it to tackle urban ills….Such efforts can be a boon for cities, making them more productive, efficient and safe, says Rob Kitchin of Maynooth University in Ireland, who helped launched a real-time data site for Dublin last month called the Dublin Dashboard. But he cautions that there’s a limit to how far these systems can aid us. Knowing that a particular street corner is likely to be overrun with rats tomorrow doesn’t address what caused the infestation in the first place. “You might be able to create a sticking plaster or be able to manage it more efficiently, but you’re not going to be able to solve the deep structural problems….”
VouliWatch – Empowering Democracy in Greece
Proposal at IndieGogo: “In the wake of the economic crisis and in a country where politics has all too often been beset by scandals and corruption, Vouliwatch aims to help develop an open and accountable political system that uses new digital technology to promote citizen participation in the political process and to rebuild trust in parliamentary democracy. In the heyday of Ancient Greek democracy, citizens actively participated in political dialogue, and Vouliwatch aims to revive this essential aspect of a democratic society through the use of digital technology.
How it actually works!
Vouliwatch is a digital platform that offers Greek citizens the opportunity to publicly question MPs and MEPs on the topic of their choice, and to hold their elected representatives accountable for their parliamentary activity. It is loosely modelled on similar initiatives that are already running successfully in other countries (Ireland, Luxemburg, Tunisia, Germany, France and Austria)….
Crowdsourcing/bottom up approach
The platform also gives users the chance to influence political debate and to focus the attention of both the media and the politicians on issues that citizens believe are important and are not being discussed widely.Vouliwatch offers citizens the chance to share their ideas and experiences and to make proposals to parliament for political action. The community of users can then comment on and rate them. A Google map application depicts all submitted data with the option of filtering based on different criteria (location; subject categories such as e.g. education, tourism, etc.). Every 2 months all submitted data is summarized in a report and sent to all MPs by our team, as food for thought and action. Vouliwatch will then publish and promote any resulting parliamentary reaction….”
Data revolution: How the UN is visualizing the future
Kate Krukiel at Microsoft Government: “…world leaders met in New York for the 69th session of the United Nations (UN) General Assembly. Progress toward achieving the eight Millennium Development Goals (MDGs) by the December 2015 target date—just 454 days away—was top of mind. So was the post-2015 agenda, which will pick up where the MDGs leave off. Ahead of the meetings, the UN Millennium Campaign asked Microsoft to build real-time visualizations of the progress on each goal—based on data spanning 21 targets, 60 indicators, and about 190 member countries. With the data visualizations we created (see them at http://www.mdgleaders.org/), UN and global leaders can decide where to focus in the next 15 months and, more importantly, where change needs to happen post-2015. Their experience offers three lessons for governments:
1. Data has a shelf life.
Since the MDGs were launched in 2000, the UN has relied on annual reports to assess its progress. But in August, UN Secretary-General Ban Ki-moon called for a “data revolution for sustainable development”, which in effect makes real-time data visualization a requirement, not just for tracking the MDGs, but for everything from Ebola to climate change….
2.Governments need visualization tools.
Just as the UN is using data visualization to track its progress and plan for the future, you can use the technology to better understand the massive amounts of data you collect—on everything from water supply and food prices to child mortality and traffic jams. Data visualization technology makes it possible to pull insights from historical data, develop forecasts, and spot gaps in your data far easier than you can with raw data. As they say, a picture is worth a thousand words. To get a better idea of what’s possible, check out the MDG visualizations Microsoft created for the UN using our Power BI tool.
3.The private sector can help.
The UN called on the private sector to assist in determining the exact MDG progress and inspire ongoing global efforts. …
Follow the UN’s lead and join the #datarevolution now, if you haven’t already. It’s an opportunity to work across silos and political boundaries to address the world’s most pressing problems. It takes citizens’ points of view into account through What People Want. And it extends to the private sector, where expertise in using technology to create a sustainable future already exists. I encourage all government leaders to engage. To follow where the UN takes its revolution, watch for updates on the Data Revolution Group website or follow them on Twitter @data_rev….”
The View From Your Window Is Worth Cash to This Company
Eric Jaffe in Atlantic CityLab: “A city window overlooking the street has always been a score in its own right, what with so many apartments stuck opening onto back alleys and dumpsters and fire escapes. And now, a company wants to straight up monetize the view. New York startup Placemeter is paying city residents up to $50 a month for street views captured via old smartphones. The idea is to quantify sidewalk life in the service of making the city a more efficient place.
“Measuring data about how the city moves in real time, being able to make predictions on that, is definitely a good way to help cities work better,” says founder Alex Winter. “That’s the vision of Placemeter—to build a data platform where anyone at any time can know how busy the city is, and use that.”
Here’s how it works: City residents send Placemeter a little information about where they live and what they see from their window. In turn, Placemeter sends participants a kit (complete with window suction cup) to convert their unused smartphone into a street sensor, and agrees to pay cash so long as the device stays on and collects data. The more action outside—the more shops, pedestrians, traffic, and public space—the more the view is worth.
On the back end, Placemeter converts the smartphone images into statistical data using proprietary computer vision. The company first detects moving objects (the green splotches in the video below) and classifies them either as people or as 11 types of vehicles or other common urban elements, such as food carts. A second layer of analysis connects this movement with behavioral patterns based on the location—how many cars are speeding down a street, for instance, or how many people are going into a store….
Efforts to quantify city life with big data aren’t new, but where Placemeter’s clear advance is its ability to count pedestrians. Cities often track sidewalk traffic with little more than a hired hand and a manual clicker and spot locations. With its army of smartphone eyes, Placemeter promises a much wider net of real-time data dynamic enough to recognize not only that a person exists but also that person’s behavior, from walking speed to retail interest to general interaction with streets or public spaces…”
Forget GMOs. The Future of Food Is Data—Mountains of It
Cade Metz at Wired: “… Led by Dan Zigmond—who previously served as chief data scientist for YouTube, then Google Maps—this ambitious project aims to accelerate the work of all the biochemists, food scientists, and chefs on the first floor, providing a computer-generated shortcut to what Hampton Creek sees as the future of food. “We’re looking at the whole process,” Zigmond says of his data team, “trying to figure out what it all means and make better predictions about what is going to happen next.”
The project highlights a movement, spreading through many industries, that seeks to supercharge research and development using the kind of data analysis and manipulation pioneered in the world of computer science, particularly at places like Google and Facebook. Several projects already are using such techniques to feed the development of new industrial materials and medicines. Others hope the latest data analytics and machine learning techniques can help diagnosis disease. “This kind of approach is going to allow a whole new type of scientific experimentation,” says Jeremy Howard, who as the president of Kaggle once oversaw the leading online community of data scientists and is now applying tricks of the data trade to healthcare as the founder of Enlitic.
Zigmond’s project is the first major effort to apply “big data” to the development of food, and though it’s only just getting started—with some experts questioning how effective it will be—it could spur additional research in the field. The company may license its database to others, and Hampton Creek founder and CEO Josh Tetrick says it may even open source the data, so to speak, freely sharing it with everyone. “We’ll see,” says Tetrick, a former college football linebacker who founded Hampton Creek after working on economic and social campaigns in Liberia and Kenya. “That would be in line with who we are as a company.”…
Initially, Zigmond and his team will model protein interactions on individual machines, using tools like the R programming language (a common means of crunching data) and machine learning algorithms much like those that recommend products on Amazon.com. As the database expands, they plan to arrange for much larger and more complex models that run across enormous clusters of computer servers, using the sort of sweeping data-analysis software systems employed by the likes of Google. “Even as we start to get into the tens and hundreds of thousands and millions of proteins,” Zigmond says, “it starts to be more than you can handle with traditional database techniques.”
In particular, Zigmond is exploring the use of deep learning, a form of artificial intelligence that goes beyond ordinary machine learning. Google is using deep learning to drive the speech recognition system in Android phones. Microsoft is using it to translate Skype calls from one language to another. Zigmond believes it can help model the creation of new foods….”
Zigmond’s project is the first major effort to apply “big data” to the development of food, and though it’s only just getting started—with some experts questioning how effective it will be—it could spur additional research in the field. The company may license its database to others, and Hampton Creek founder and CEO Josh Tetrick says it may even open source the data, so to speak, freely sharing it with everyone. “We’ll see,” says Tetrick, a former college football linebacker who founded Hampton Creek after working on economic and social campaigns in Liberia and Kenya. “That would be in line with who we are as a company.”…
Initially, Zigmond and his team will model protein interactions on individual machines, using tools like the R programming language (a common means of crunching data) and machine learning algorithms much like those that recommend products on Amazon.com. As the database expands, they plan to arrange for much larger and more complex models that run across enormous clusters of computer servers, using the sort of sweeping data-analysis software systems employed by the likes of Google. “Even as we start to get into the tens and hundreds of thousands and millions of proteins,” Zigmond says, “it starts to be more than you can handle with traditional database techniques.”
In particular, Zigmond is exploring the use of deep learning, a form of artificial intelligence that goes beyond ordinary machine learning. Google is using deep learning to drive the speech recognition system in Android phones. Microsoft is using it to translate Skype calls from one language to another. Zigmond believes it can help model the creation of new foods….”
Redesigning that first encounter with online government
Nancy Scola in the Washington Post: “Teardowns,” Samuel Hulick calls them, and by that he means his step-by-step dissections of how some of world’s most popular digital services — Gmail, Evernote, Instragram — welcome new users. But the term might give an overly negative sense of what Hulick is up to. The Portland, Ore., user-experience designer highlights both the good and bad in his critiques, and his annotated slideshows, under the banner of UserOnboard, have gained a following among design aficionados.
Using the original UserOnboard is like taking a tour through some of the digital sites you know best — but with an especially design-savvy friend by your side pointing out the kinks. “The user experience,” or UX on these sites, “is often tacked on haphazardly,” says Hulick, who launched UserOnboard in December 2013 and who is also the author of the recent book “The Elements of User Onboarding.” What’s he looking for in a good UX, he says, is something non-designers can spot, too. “If you were the Web site, what tone would you take? How would you guide people through your process?”
Hulick reviews what’s working and what’s not, and adds a bit of sass: Gmail pre-populates its inbox with a few welcome messages: “Preloading some emails is a nice way to deal with the ‘cold start’ problem,” Hulick notes. Evernote nudges new users to check out its blog and other apps: “It’s like a restaurant rolling out the dessert cart while I’m still trying to decide if I even want to eat there.” Instagram’s first backdrop is a photo of someone taking a picture: “I’m learning how to Instagram by osmosis!”….
CitizenOnboard’s pitch is to get the public to do that same work. They suggest starting with state food stamp programs. Hulick tackled his. The onboarding for Oregon’s SNAP service is 118 slides long, but that’s because there is much to address. In one step, applications must, using a drop-down menu, identify how those in their family are related to one another. “It took a while to figure out who should be the relation ‘of’ the other,” Hulick notes in his teardown. “In fact, I’m still not 100% sure I got it right.”…”
Ants Are Cool but Teach Us Nothing
Edward O. Wilson in Bloomberg View: “…For nearly seven decades, starting in boyhood, I’ve studied hundreds of kinds of ants around the world, and this qualifies me, I believe, to offer some advice on ways their lives can be applied to ours. I’ll start with the question I’m most often asked: “What can I do about the ants in my kitchen?” My response comes from the heart: Watch your step, be careful of little lives. Ants especially like honey, tuna and cookie crumbs. So put down bits of those on the floor, and watch as the first scout finds the bait and reports back to her colony by laying an odor trail. Then, as a little column follows her out to the food, you will see social behavior so strange it might be on another planet. Think of kitchen ants not as pests or bugs, but as your personal guest superorganism.
Another question I hear a lot is, “What can we learn of moral value from the ants?” Here again I will answer definitively: nothing. Nothing at all can be learned from ants that our species should even consider imitating. For one thing, all working ants are female. Males are bred and appear in the nest only once a year, and then only briefly. They are pitiful creatures with wings, huge eyes, small brains and genitalia that make up a large portion of their rear body segment. They have only one function in life: to inseminate the virgin queens during the nuptial season. They are built to be robot flying sexual missiles. Upon mating or doing their best to mate, they are programmed to die within hours, usually as victims of predators.
Many kinds of ants eat their dead — and their injured, too. You may have seen ant workers retrieve nestmates that you have mangled or killed underfoot (accidentally, I hope), thinking it battlefield heroism. The purpose, alas, is more sinister.
As ants grow older, they spend more time in the outermost chambers and tunnels of the nest, and are more prone to undertake dangerous foraging trips. They also are the first to attack enemy ants and other intruders. Here indeed is a major difference between people and ants: While we send our young men to war, ants send their old ladies.
The most complex societies of all ant species, and arguably of all animals everywhere, are the leafcutters of the American tropics. In lowland forests and grasslands from Mexico to South America, you find conspicuous long files of reddish ants. Many carry freshly cut pieces of leaves, flowers and twigs. The ants don’t eat this vegetation. They carry it deep into their nests, where they convert it into complex, spongelike structures. On this substrate they grow a fungus, which they do eat. The entire process employs a sequence of specialists: The leafcutters in the field are medium in size. As they head home with their burdens, tiny sister ant workers ride on their backs to protect them from parasitic phorid flies. Inside the nest, workers somewhat smaller than the gatherers scissor the leaf fragments into pieces. Still smaller ants chew the fragments into lumps and add their own fecal material as fertilizer. Even smaller workers use the gooey lumps thus created to construct the gardens. And workers as small as the fly guards plant and tend the fungus.
The largest caste of leafcutter ants have razor-sharp mandibles and the adductor muscles to close them with enough force to slice mammalian skin. These soldiers defend the nest against the most dangerous predators, including anteaters.
Species that have been able to evolve superorganismic colonies — almost purely on the basis of instinct — have as a whole been enormously successful. The 20,000 or so known species of social insects make up only 2 percent of the million known species of insects but three-fourths of the insect biomass.
With complexity, however, comes vulnerability, and that brings me to one of the other superorganism superstars, the domestic honeybee. When disease strikes solitary animals that we have embraced in symbiosis, such as chickens, pigs and dogs, veterinarians can usually diagnose and fix the problem. Honeybees, on the other hand, have by far the most complex lives of all our domestic partners. There are a great many more twists and turns in their adaptation to their environment that, upon failing, can damage some part of the colony life cycle. The intractability thus far of the honeybee colony collapse disorder of Europe and North America, which threatens so much of crop pollination, may represent an intrinsic weakness of superorganisms.
You may occasionally hear human societies described as superorganisms. This is a bit of a stretch. It is true that we form societies dependent on cooperation, labor specialization and frequent acts of altruism. But where social insects are ruled almost entirely by instinct, we base labor division on transmission of culture. Also, unlike social insects, we are too selfish to behave like cells in an organism. Human beings seek their own destiny. They will always revolt against slavery, and refuse to be treated like worker ants.”