Maury Blackman at Wired: “The public’s trust in government is at an all-time low. This is not breaking news.
But what if I told you that just this past May, President Obama signed into law a bill that passed Congress with unanimous support. A bill that could fundamentally transform the way citizens interact with their government. This legislation could also create an entirely new, trillion-dollar industry right here in the U.S. It could even save lives.
On May 9th, the Digital Accountability and Transparency Act of 2014 (DATA Act) became law. There were very few headlines, no Rose Garden press conference.
I imagine most of you have never heard of the DATA Act. The bill with the nerdy name has the potential to revolutionize government. It requires federal agencies to make their spending data available in standardized, publicly accessible formats. Supporters of the legislation included Tea Partiers and the most liberal Democrats. But the bill is only scratches the surface of what’s possible.
So What’s the Big Deal?
On his first day in Office, President Obama signed a memorandum calling for a more open and transparent government. The President wrote, “Openness will strengthen our democracy and promote efficiency and effectiveness in Government.” This was followed by the creation of Data.gov, a one-stop shop for all government data. The site does not just include financial data, but also a wealth of other information related to education, public safety, climate and much more—all available in open and machine-readable format. This has helped fuel an international movement.
Tech minded citizens are building civic apps to bring government into the digital age; reporters are now more able to connect the dots easier, not to mention the billions of taxpayer dollars saved. And last year the President took us a step further. He signed an Executive Order making open government data the default option.
Cities and states have followed Washington’s lead with similar open data efforts on the local level. In San Francisco, the city’s Human Services Agency has partnered with Promptly; a text message notification service that alerts food stamp recipients (CalFresh) when they are at risk of being disenrolled from the program. This service is incredibly beneficial, because most do not realize any change in status, until they are in the grocery store checkout line, trying to buy food for their family.
Other products and services created using open data do more than just provide an added convenience—they actually have the potential to save lives. The PulsePoint mobile app sends text messages to citizens trained in CPR when someone in walking distance is experiencing a medical emergency that may require CPR. The app is currently available in almost 600 cities in 18 states, which is great. But shouldn’t a product this valuable be available to every city and state in the country?…”
The Innovators
Kirkus Review of “The innovators. How a Group of Inventors, Hackers, Geniuses, and Geeks Created the Digital Revolution” by Walter Isaacson: “Innovation occurs when ripe seeds fall on fertile ground,” Aspen Institute CEO Isaacson (Steve Jobs, 2011, etc.) writes in this sweeping, thrilling tale of three radical innovations that gave rise to the digital age. First was the evolution of the computer, which Isaacson traces from its 19th-century beginnings in Ada Lovelace’s “poetical” mathematics and Charles Babbage’s dream of an “Analytical Engine” to the creation of silicon chips with circuits printed on them. The second was “the invention of a corporate culture and management style that was the antithesis of the hierarchical organization of East Coast companies.” In the rarefied neighborhood dubbed Silicon Valley, new businesses aimed for a cooperative, nonauthoritarian model that nurtured cross-fertilization of ideas. The third innovation was the creation of demand for personal devices: the pocket radio; the calculator, marketing brainchild of Texas Instruments; video games; and finally, the holy grail of inventions: the personal computer. Throughout his action-packed story, Isaacson reiterates one theme: Innovation results from both “creative inventors” and “an evolutionary process that occurs when ideas, concepts, technologies, and engineering methods ripen together.” Who invented the microchip? Or the Internet? Mostly, Isaacson writes, these emerged from “a loosely knit cohort of academics and hackers who worked as peers and freely shared their creative ideas….Innovation is not a loner’s endeavor.” Isaacson offers vivid portraits—many based on firsthand interviews—of mathematicians, scientists, technicians and hackers (a term that used to mean anyone who fooled around with computers), including the elegant, “intellectually intimidating,” Hungarian-born John von Neumann; impatient, egotistical William Shockley; Grace Hopper, who joined the Army to pursue a career in mathematics; “laconic yet oddly charming” J.C.R. Licklider, one father of the Internet; Bill Gates, Steve Jobs, and scores of others.
Isaacson weaves prodigious research and deftly crafted anecdotes into a vigorous, gripping narrative about the visionaries whose imaginations and zeal continue to transform our lives.”
A Different Idea of Our Declaration
Gordon S. Wood reviews Our Declaration: A Reading of the Declaration of Independence in Defense of Equality
Allen, who is a professor of social science at the Institute for Advanced Study in Princeton, came to this extraordinary conclusion when she was teaching for a decade at the University of Chicago. But it was not the young bright-eyed undergraduates whom she taught by day who inspired her. Instead, it was the much older, life-tested adults whom she taught by night who created “the single most transformative experience” of her teaching career.
As she slowly worked her way through the 1,337 words of the Declaration of Independence with her night students, many of whom had no job or were working two jobs or were stuck in dead-end part-time jobs, Allen discovered that the document had meaning for them and that it was accessible to any reader or hearer of its words. By teaching the document to these adult students in the way that she did, she experienced “a personal metamorphosis.” For the first time in her life she came to realize that the Declaration makes a coherent philosophical argument about equality, an argument that could be made comprehensible to ordinary people who had no special training…”
How Thousands Of Dutch Civil Servants Built A Virtual 'Government Square' For Online Collaboration
Federico Guerrini at Forbes: “Democracy needs a reboot, or as the founders of Democracy Os, an open source platform for political debate say, “a serious upgrade”. They are not alone in trying to change the way citizens and governments communicate with each other. Not long ago, I covered on this blog a Greek platform, VouliWatch, which aims at boosting civic engagement following the model of other similar initiatives in countries like Germany, France and Austria, all running thanks to a software called Parliament Watch.
Other decision making tools, used by activists and organizations that try to reduce the distance between the people and their representatives include Liquid Feedback, and Airesis. But the quest for disintermediation doesn’t regard only the relationship between governments and citizens: it’s changing the way public organisations work internally as well. Civil servants are starting to develop and use their internal “social networks”, to exchange ideas, discussing issues and collaborate on projects.
One such thing is happening in the Netherlands: thousands of civil servants belonging to all government organizations have built their own “intranet” using Pleio (“government square”, in Dutch) a platform that runs on the open source networking engine Elgg.
It all started in 2010, thanks to the work of a group of four founders, Davied van Berlo, Harrie Custers, Wim Essers and Marcel Ziemerink. Growth has been steady and now Pleio can count on some 75.000 users spread in about 800 subsites. The nice thing about the platform, in fact, is that it is modular: subscribers can collaborate on a group and then start a sub group to get in more depth with a smaller team. To learn a little more about this unique experience, I reached out for van Berlo, who kindly answered a few questions. Check the interview below.
Where did the Pleio idea come from?Were you inspired by other experiences?
The idea came mainly from the developments around us: the whole web 2.0 movement at the time. This has shown us the power of platforms to connect people, bring them together and let them cooperate. I noticed that civil servants were looking for ways of collaborating across organisational borders and many were using the new online tools. That’s why I started the Civil Servant 2.0 network, so they could exchange ideas and experiences in this new way of working.
However, these tools are not always the ideal solution. They’re commercial for one, which can get in the way of the public goals we work for. They’re often American, where other laws and practices apply. You can’t change them or add to them. Usually you have to get another tool (and login) for different functionalities. And they were outright forbidden by some government agencies. I noticed there was a need for a platform where different tools were integrated, where people from different organisations and outside government could work together and where all information would remain in the Netherlands and in the hands of the original owner. Since there was no such platform we started one of our own….”
Demos for Democracy
The GovLab presents Demos for Democracy, an ongoing series of live, interactive online demos featuring designers and builders of the latest innovative governance platforms, tools or methods to foster greater openness and collaboration to how we govern.
Who: remesh, founded by PhD students Andrew Konya and Aaron Slodov, is an online public platform that offers a community, group, nation or planet of people the ability to speak with one voice that represents the collective thinking of all people within the group. remesh was prototyped at a HacKSU hackathon early in 2013 and has been under development over the past year.
What: Join us for a live demonstration of how remesh works before their official public launch. Participants will be given a link to test the platform during the live Google hangout. More information on what remesh does can be found here.
When: July 29, 2014, 2:00 – 2:30 PM EST
Where: Online via Google Hangouts on Air. To RSVP and join, go to the Hangout Link. This event will be live tweeted at #democracydemos.
Bios:
Andrew Konya (CEO/Founder) is a PhD student in computational/theoretical physics at Kent State University. With extensive experience developing and implementing mathematical models for natural and man-made systems, Andrew brings a creative yet and versatile technical toolbox. This expertise, in concert with his passion for linguistics, led him to develop the first mathematical framework for collective speech. His goal is the completion of a conversation platform, built on this framework, which can make conversations between countries in conflict a viable alternative to war.
Aaron Slodov (COO/Founder) is a current power systems engineering PhD student at Case Western Reserve University. A previous engineer at both Google and Meetup.com, Aaron is experienced in the tech landscape, and understands many of the current problems in the space. By enabling remesh technology he hopes to bring significant paradigm-shifting change to the way we communicate and interact with our world.
RSVP and JOIN
We hope to see you on Tuesday! If you have any questions, email us at [email protected].
Business Models That Take Advantage of Open Data Opportunities
The OKFestival—hosted by the Open Knowledge Foundation—brought together more than 1,000 participants from around the globe working on various aspects of the open data agenda: the use of corporate data, open science research, government open data and crowdsourced data projects.
In a session held on the first day of the event, Borlongan facilitated an interactive workshop to help would-be entrepreneurs understand how startups are building business models that take advantage of open data opportunities to create sustainable, employment-generating businesses.
Citing research from the McKinsey Institute that calculates the value of open data to be worth $3 trillion globally, Borlongan said: “So the understanding of the open data process is usually: We throw open data over the wall, then we hold a hackathon, and then people will start making products off it, and then we make the $3 trillion.”
Borlongan argued that it is actually a “blurry identity to be an open data startup” and encouraged participants to unpack, with each of the startups presenting exactly how income can be generated and a viable business built in this space.
Jeni Tennison, from the U.K.’s Open Data Institute (which supports 15 businesses in its Startup Programme) categorizes two types of business models:
In a session held on the first day of the event, Borlongan facilitated an interactive workshop to help would-be entrepreneurs understand how startups are building business models that take advantage of open data opportunities to create sustainable, employment-generating businesses.
Citing research from the McKinsey Institute that calculates the value of open data to be worth $3 trillion globally, Borlongan said: “So the understanding of the open data process is usually: We throw open data over the wall, then we hold a hackathon, and then people will start making products off it, and then we make the $3 trillion.”
Borlongan argued that it is actually a “blurry identity to be an open data startup” and encouraged participants to unpack, with each of the startups presenting exactly how income can be generated and a viable business built in this space.
Jeni Tennison, from the U.K.’s Open Data Institute (which supports 15 businesses in its Startup Programme) categorizes two types of business models:
- Businesses that publish (but do not sell) open data.
- Businesses built on top of using open data.
Businesses That Publish but Do Not Sell Open Data
At the Open Data Institute, Tennison is investigating the possibility of an open address database that would provide street address data for every property in the U.K. She describes three types of business models that could be created by projects that generated and published such data:
Freemium: In this model, the bulk data of open addresses could be made available freely, “but if you want an API service, then you would pay for it.” Tennison pointed to lots of opportunities also to degrade the freemium-level data—for example, having it available in bulk but not at a particularly granular level (unless you pay for it), or by provisioning reuse on a share-only basis, but you would pay if you wanted the data for corporate use cases (similar to how OpenCorporates sells access to its data).
Cross-subsidy: In this approach, the data would be available, and the opportunities to generate income would come from providing extra services, like consultancy or white labeling data services alongside publishing the open data.
Network: In this business model, value is created by generating a network effect around the core business interest, which may not be the open data itself. As an example, Tennison suggested that if a post office or delivery company were to create the open address database, it might be interested in encouraging private citizens to collaboratively maintain or crowdsource the quality of the data. The revenue generated by this open data would then come from reductions in the cost of delivery services as the data improved accuracy.
Businesses Built on Top of Open Data
Six startups working in unique ways to make use of available open data also presented their business models to OKFestival attendees: Development Seed, Mapbox, OpenDataSoft, Enigma.io, Open Bank API, and Snips.
Startup: Development Seed
What it does: Builds solutions for development, public health and citizen democracy challenges by creating open source tools and utilizing open data.
Open data API focus: Regularly uses open data APIs in its projects. For example, it worked with the World Bank to create a data visualization website built on top of the World Bank API.
Type of business model: Consultancy, but it has also created new businesses out of the products developed as part of its work, most notably Mapbox (see below).
Startup: Enigma.io
What it does: Open data platform with advanced discovery and search functions.
Open data API focus: Provides the Enigma API to allow programmatic access to all data sets and some analytics from the Enigma platform.
Type of business model: SaaS including a freemium plan with no degradation of data and with access to API calls; some venture funding; some contracting services to particular enterprises; creating new products in Enigma Labs for potential later sale.
Startup: Mapbox
What it does: Enables users to design and publish maps based on crowdsourced OpenStreetMap data.
Open data API focus: Uses OpenStreetMap APIs to draw data into its map-creation interface; provides the Mapbox API to allow programmatic creation of maps using Mapbox web services.
Type of business model: SaaS including freemium plan; some tailored contracts for big map users such as Foursquare and Evernote.
Startup: Open Bank Project
What it does: Creates an open source API for use by banks.
Open data API focus: Its core product is to build an API so that banks can use a standard, open source API tool when creating applications and web services for their clients.
Type of business model: Contract license with tiered SLAs depending on the number of applications built using the API; IT consultancy projects.
Startup: OpenDataSoft
What it does: Provides an open data publishing platform so that cities, governments, utilities and companies can publish their own data portal for internal and public use.
Open data API focus: It’s able to route data sources into the portal from a publisher’s APIs; provides automatic API-creation tools so that any data set uploaded to the portal is then available as an API.
Type of business model: SaaS model with freemium plan, pricing by number of data sets published and number of API calls made against the data, with free access for academic and civic initiatives.
Startup: Snips
What it does: Predictive modeling for smart cities.
Open data API focus: Channels some open and client proprietary data into its modeling algorithm calculations via API; provides a predictive modeling API for clients’ use to programmatically generate solutions based on their data.
Type of business model: Creating one B2C app product for sale as a revenue-generation product; individual contracts with cities and companies to solve particular pain points, such as using predictive modeling to help a post office company better manage staff rosters (matched to sales needs) and a consultancy project to create a visualization mapping tool that can predict the risk of car accidents for a city….”
Indonesian techies crowdsource election results
The Indonesian techies, who work for multinational companies, were spurred into action after both presidential candidates claimed victory and accused each other of trying to rig the convoluted counting process, raising fears that the country’s young democracy was under threat.
Mr Najib and two friends took advantage of the decision by the national election commission (KPU) to upload the individual results from Indonesia’s 480,000 polling stations to its website for the first time, in an attempt to counter widespread fears about electoral fraud.
The three Indonesians scraped the voting data from the KPU website on to a database and then recruited 700 friends and acquaintances through Facebook to type in the results and check them. They uploaded the data to a website called kawalpemilu.org, which means “guard the election” in Indonesian.
Throughout the process, Mr Najib said he had to fend off hacking attacks, forcing him to shift data storage to a cloud-based service. The whole exercise cost $10 for a domain name and $0.10 for the data storage….”
Neuroeconomics, Judgment, and Decision Making
New edited book by Evan A. Wilhelms, and Valerie F. Reyna: “This volume explores how and why people make judgments and decisions that have economic consequences, and what the implications are for human well-being. It provides an integrated review of the latest research from many different disciplines, including social, cognitive, and developmental psychology; neuroscience and neurobiology; and economics and business.
The book has six areas of focus: historical foundations; cognitive consistency and inconsistency; heuristics and biases; neuroeconomics and neurobiology; developmental and individual differences; and improving decisions. Throughout, the contributors draw out implications from traditional behavioral research as well as evidence from neuroscience. In recent years, neuroscientific methods have matured, beyond being simply correlational and descriptive, into theoretical prediction and explanation, and this has opened up many new areas of discovery about economic behavior that are reviewed in the book. In the final part, there are applications of the research to cognitive development, individual differences, and the improving of decisions.
The book takes a broad perspective and is written in an accessible way so as to reach a wide audience of advanced students and researchers interested in behavioral economics and related areas. This includes neuroscientists, neuropsychologists, clinicians, psychologists (developmental, social, and cognitive), economists and other social scientists; legal scholars and criminologists; professionals in public health and medicine; educators; evidence-based practitioners; and policy-makers.”
The book takes a broad perspective and is written in an accessible way so as to reach a wide audience of advanced students and researchers interested in behavioral economics and related areas. This includes neuroscientists, neuropsychologists, clinicians, psychologists (developmental, social, and cognitive), economists and other social scientists; legal scholars and criminologists; professionals in public health and medicine; educators; evidence-based practitioners; and policy-makers.”
The Quiet Movement to Make Government Fail Less Often
in The New York Times: “If you wanted to bestow the grandiose title of “most successful organization in modern history,” you would struggle to find a more obviously worthy nominee than the federal government of the United States.
In its earliest stirrings, it established a lasting and influential democracy. Since then, it has helped defeat totalitarianism (more than once), established the world’s currency of choice, sent men to the moon, built the Internet, nurtured the world’s largest economy, financed medical research that saved millions of lives and welcomed eager immigrants from around the world.
Of course, most Americans don’t think of their government as particularly successful. Only 19 percent say they trust the government to do the right thing most of the time, according to Gallup. Some of this mistrust reflects a healthy skepticism that Americans have always had toward centralized authority. And the disappointing economic growth of recent decades has made Americans less enamored of nearly every national institution.
But much of the mistrust really does reflect the federal government’s frequent failures – and progressives in particular will need to grapple with these failures if they want to persuade Americans to support an active government.
When the federal government is good, it’s very, very good. When it’s bad (or at least deeply inefficient), it’s the norm.
The evidence is abundant. Of the 11 large programs for low- and moderate-income people that have been subject to rigorous, randomized evaluation, only one or two show strong evidence of improving most beneficiaries’ lives. “Less than 1 percent of government spending is backed by even the most basic evidence of cost-effectiveness,” writes Peter Schuck, a Yale law professor, in his new book, “Why Government Fails So Often,” a sweeping history of policy disappointments.
As Mr. Schuck puts it, “the government has largely ignored the ‘moneyball’ revolution in which private-sector decisions are increasingly based on hard data.”
And yet there is some good news in this area, too. The explosion of available data has made evaluating success – in the government and the private sector – easier and less expensive than it used to be. At the same time, a generation of data-savvy policy makers and researchers has entered government and begun pushing it to do better. They have built on earlier efforts by the Bush and Clinton administrations.
The result is a flowering of experiments to figure out what works and what doesn’t.
New York City, Salt Lake City, New York State and Massachusetts have all begun programs to link funding for programs to their success: The more effective they are, the more money they and their backers receive. The programs span child care, job training and juvenile recidivism.
The approach is known as “pay for success,” and it’s likely to spread to Cleveland, Denver and California soon. David Cameron’s conservative government in Britain is also using it. The Obama administration likes the idea, and two House members – Todd Young, an Indiana Republican, and John Delaney, a Maryland Democrat – have introduced a modest bill to pay for a version known as “social impact bonds.”
The White House is also pushing for an expansion of randomized controlled trials to evaluate government programs. Such trials, Mr. Schuck notes, are “the gold standard” for any kind of evaluation. Using science as a model, researchers randomly select some people to enroll in a government program and others not to enroll. The researchers then study the outcomes of the two groups….”
Do We Choose Our Friends Because They Share Our Genes?
Rob Stein at NPR: “People often talk about how their friends feel like family. Well, there’s some new research out that suggests there’s more to that than just a feeling. People appear to be more like their friends genetically than they are to strangers, the research found.
“The striking thing here is that friends are actually significantly more similar to one another than we were expecting,” says James Fowler, a professor of medical genetics at the University of California, San Diego, who conducted the study with Nicholas A. Christakis, a social scientist at Yale University.
In fact, the study in Monday’s issue of the Proceedings of the National Academy of Sciences found that friends are as genetically similar as fourth cousins.
“It’s as if they shared a great- great- great-grandparent in common,” Fowler told Shots.
Some of the genes that friends were most likely to have in common involve smell. “We tend to smell things the same way that our friends do,” Fowler says. The study involved nearly 2,000 adults.
This suggests that as humans evolved, the ability to tolerate and be drawn to certain smells may have influenced where people hung out. Today we might call this the Starbucks effect.
“You may really love the smell of coffee. And you’re drawn to a place where other people have been drawn to who also love the smell of coffee,” Fowler says. “And so that might be the opportunity space for you to make friends. You’re all there together because you love coffee and you make friends because you all love coffee.”…”