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.

Now Hulick is partnering with two of those fans, a pair of Code for America fellows, to encourage the public to do the same for, say, the process of applying for food stamps.  It’s called CitizenOnboard.
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.”…”

Happy Birthday, We the People! Marking Three Years of Online Petitions


On September 22, 2011, we launched We the People to give Americans a new way to petition their government around issues they care about. It works like this: Start a petition, get enough signatures, and the Obama administration will work with policy experts to issue an official response.
It’s three years later, and We the People remains incredibly popular: More than 15 million users have participated, collecting more than 22 million signatures on more than 360,000 petitions. To date, we’ve issued nearly 250 responses to petitions on a wide range of topics, including maintaining an open and innovative internet, reducing student loan debt, improving our economy, and even building a “Death Star.”
The We the People platform has led directly to policy changes and provided new opportunities for dialogue between citizens and their government. That’s part of the reason why, over the course of 2014, an average of response surveys showed a majority of signers thought it was “helpful to hear the Administration’s response,” even if they didn’t agree. Nearly 80 percent said they would use We the People again.
To celebrate We the People’s third birthday, the White House will host the first-ever social meetup for We the People users and petition creators right here at 1600 Pennsylvania Avenue. It will be an exciting chance for users to meet with policy experts and connect with each other in person.
Meanwhile, we continue to work to make We the People even more accessible so that people — no matter where they are on the internet — can use the platform to reach the White House. Beginning in October, third-party websites can submit signatures to We the People on behalf of their own signers, using our soon-to-be-released Write API (which is currently in beta). It’s the result of months of hard work, and we can’t wait to share it with the public.
Check out the infographic below, and take a look at some of the platform’s highlights over the last three years…”

Mapping the Next Frontier of Open Data: Corporate Data Sharing


Stefaan Verhulst at the GovLab (cross-posted at the UN Global Pulse Blog): “When it comes to data, we are living in the Cambrian Age. About ninety percent of the data that exists today has been generated within the last two years. We create 2.5 quintillion bytes of data on a daily basis—equivalent to a “new Google every four days.”
All of this means that we are certain to witness a rapid intensification in the process of “datafication”– already well underway. Use of data will grow increasingly critical. Data will confer strategic advantages; it will become essential to addressing many of our most important social, economic and political challenges.
This explains–at least in large part–why the Open Data movement has grown so rapidly in recent years. More and more, it has become evident that questions surrounding data access and use are emerging as one of the transformational opportunities of our time.
Today, it is estimated that over one million datasets have been made open or public. The vast majority of this open data is government data—information collected by agencies and departments in countries as varied as India, Uganda and the United States. But what of the terabyte after terabyte of data that is collected and stored by corporations? This data is also quite valuable, but it has been harder to access.
The topic of private sector data sharing was the focus of a recent conference organized by the Responsible Data Forum, Data and Society Research Institute and Global Pulse (see event summary). Participants at the conference, which was hosted by The Rockefeller Foundation in New York City, included representatives from a variety of sectors who converged to discuss ways to improve access to private data; the data held by private entities and corporations. The purpose for that access was rooted in a broad recognition that private data has the potential to foster much public good. At the same time, a variety of constraints—notably privacy and security, but also proprietary interests and data protectionism on the part of some companies—hold back this potential.
The framing for issues surrounding sharing private data has been broadly referred to under the rubric of “corporate data philanthropy.” The term refers to an emerging trend whereby companies have started sharing anonymized and aggregated data with third-party users who can then look for patterns or otherwise analyze the data in ways that lead to policy insights and other public good. The term was coined at the World Economic Forum meeting in Davos, in 2011, and has gained wider currency through Global Pulse, a United Nations data project that has popularized the notion of a global “data commons.”
Although still far from prevalent, some examples of corporate data sharing exist….

Help us map the field

A more comprehensive mapping of the field of corporate data sharing would draw on a wide range of case studies and examples to identify opportunities and gaps, and to inspire more corporations to allow access to their data (consider, for instance, the GovLab Open Data 500 mapping for open government data) . From a research point of view, the following questions would be important to ask:

  • What types of data sharing have proven most successful, and which ones least?
  • Who are the users of corporate shared data, and for what purposes?
  • What conditions encourage companies to share, and what are the concerns that prevent sharing?
  • What incentives can be created (economic, regulatory, etc.) to encourage corporate data philanthropy?
  • What differences (if any) exist between shared government data and shared private sector data?
  • What steps need to be taken to minimize potential harms (e.g., to privacy and security) when sharing data?
  • What’s the value created from using shared private data?

We (the GovLab; Global Pulse; and Data & Society) welcome your input to add to this list of questions, or to help us answer them by providing case studies and examples of corporate data philanthropy. Please add your examples below, use our Google Form or email them to us at corporatedata@thegovlab.org”

Welcoming the Third Class of Presidential Innovation Fellows


Garren Givens, and Ryan Panchadsaram at the White House Blog: “We recently welcomed the newest group of Presidential Innovation Fellows into the federal government. This diverse group represents some of the nation’s most talented and creative civic-minded innovators…
You can learn more about this inspiring group of Fellows here.
Over the next 12 months, these innovators will collaborate and work with change agents inside government on three high-impact initiatives aimed at saving lives, saving taxpayer money, and fueling our economy. These initiatives include:

  • Building a 21st Century Veterans Experience
  • Unleashing the Power of Data Resources to Improve Americans’ Lives
  • Crowdsourcing to Improve Government

Read more about the projects that make up these initiatives, and the previous successes the program has helped shape.
The fellows will be supported by 18F, an innovative group focused on the delivery of digital services across the federal government, and will work alongside the U.S. Digital Service and agency innovators in continuing to build a culture, and best practice within government….”

DrivenData


DrivenData Blog: “As we begin launching our first competitions, we thought it would be a good idea to lay out what exactly we’re trying to do and why….
At DrivenData, we want to bring cutting-edge practices in data science and crowdsourcing to some of the world’s biggest social challenges and the organizations taking them on. We host online challenges, usually lasting 2-3 months, where a global community of data scientists competes to come up with the best statistical model for difficult predictive problems that make a difference.
Just like every major corporation today, nonprofits and NGOs have more data than ever before. And just like those corporations, they are trying to figure out how to make the best use of their data. We work with mission-driven organizations to identify specific predictive questions that they care about answering and can use their data to tackle.
Then we host the online competitions, where experts from around the world vie to come up with the best solution. Some competitors are experienced data scientists in the private sector, analyzing corporate data by day, saving the world by night, and testing their mettle on complex questions of impact. Others are smart, sophisticated students and researchers looking to hone their skills on real-world datasets and real-world problems. Still more have extensive experience with social sector data and want to bring their expertise to bear on new, meaningful challenges – with immediate feedback on how well their solution performs.
Like any data competition platform, we want to harness the power of crowds combined with the increasing prevalence of large, relevant datasets. Unlike other data competition platforms, our primary goal is to create actual, measurable, lasting positive change in the world with our competitions. At the end of each challenge, we work with the sponsoring organization to integrate the winning solutions, giving them the tools to drive real improvements in their impact….
We are launching soon and we want you to join us!
If you want to get updates about our launch this fall with exciting, real competitions, please sign up for our mailing list here and follow us on Twitter: @drivendataorg.
If you are a data scientist, feel free to create an account and start playing with our first sandbox competitions.
If you are a nonprofit or public sector organization, and want to squeeze every drop of mission effectiveness out of your data, check out the info on our site and let us know! “

What Is Big Data?


datascience@berkeley Blog: ““Big Data.” It seems like the phrase is everywhere. The term was added to the Oxford English Dictionary in 2013 External link, appeared in Merriam-Webster’s Collegiate Dictionary by 2014 External link, and Gartner’s just-released 2014 Hype Cycle External link shows “Big Data” passing the “Peak of Inflated Expectations” and on its way down into the “Trough of Disillusionment.” Big Data is all the rage. But what does it actually mean?
A commonly repeated definition External link cites the three Vs: volume, velocity, and variety. But others argue that it’s not the size of data that counts, but the tools being used, or the insights that can be drawn from a dataset.
To settle the question once and for all, we asked 40+ thought leaders in publishing, fashion, food, automobiles, medicine, marketing and every industry in between how exactly they would define the phrase “Big Data.” Their answers might surprise you! Take a look below to find out what big data is:

  1. John Akred, Founder and CTO, Silicon Valley Data Science
  2. Philip Ashlock, Chief Architect of Data.gov
  3. Jon Bruner, Editor-at-Large, O’Reilly Media
  4. Reid Bryant, Data Scientist, Brooks Bell
  5. Mike Cavaretta, Data Scientist and Manager, Ford Motor Company
  6. Drew Conway, Head of Data, Project Florida
  7. Rohan Deuskar, CEO and Co-Founder, Stylitics
  8. Amy Escobar, Data Scientist, 2U
  9. Josh Ferguson, Chief Technology Officer, Mode Analytics
  10. John Foreman, Chief Data Scientist, MailChimp

FULL LIST at datascience@berkeley Blog”

Opportunities for strengthening open meetings with open data


at the Sunlight Foundation Blog: “Governments aren’t alone in thinking about how open data can help improve the open meetings process. There are an increasing number of tools governments can use to help bolster open meetings with open data. From making public records generated by meetings more easily accessible and reusable online to inviting the public to participate in the decision-making process from wherever they may be, these tools allow governments to upgrade open meetings for the opportunities and demands of the 21st Century.
Improving open meetings with open data may involve taking advantage of simple solutions already freely available online, developing new tools within government, using open-source tools, or investing in new software, but it can all help serve the same goal: bringing more information online where it’s easily accessible to the public….
It’s not just about making open meetings more accessible, either. More communities are thinking about how they can bring government to the people. Open meetings are typically held in government-designated buildings at specified times, but are those locations and times truly accessible for most of the public or for those who may be most directly impacted by what’s being discussed?
Technology presents opportunities for governments to engage with the public outside of regularly scheduled meetings. Tools like Speakup and Textizen, for example, are being used to increase public participation in the general decision-making process. A continually increasing array of toolsprovidenewways for government and the public to identify issues, share ideas, and work toward solutions, even outside of open meetings. Boston, for example, took an innovative approach to this issue with its City Hall To Go truck and other efforts, bringing government services to locations around the city rather than requiring people to come to a government building…”

Policy bubbles: What factors drive their birth, maturity and death?


Moshe Maor at LSE Blog: “A policy bubble is a real or perceived policy overreaction that is reinforced by positive feedback over a relatively long period of time. This type of policy imposes objective and/or perceived social costs without producing offsetting objective and/or perceived benefits over a considerable length of time. A case in point is when government spending over a policy problem increases due to public demand for more policy while the severity of the problem decreases over an extended period of time. Another case is when governments raise ‘green’ or other standards due to public demand while the severity of the problem does not justify this move…
Drawing on insights from a variety of fields – including behavioural economics, psychology, sociology, political science and public policy – three phases of the life-cycle of a policy bubble may be identified: birth, maturity and death. A policy bubble may emerge when certain individuals perceive opportunities to gain from public policy or to exploit it by rallying support for the policy, promoting word-of-mouth enthusiasm and widespread endorsement of the policy, heightening expectations for further policy, and increasing demand for this policy….
How can one identify a policy bubble? A policy bubble may be identified by measuring parliamentary concerns, media concerns, public opinion regarding the policy at hand, and the extent of a policy problem, against the budget allocation to said policy over the same period, preferably over 50 years or more. Measuring the operation of different transmission mechanisms in emotional contagion and human herding, particularly the spread of social influence and feeling, can also work to identify a policy bubble.
Here, computer-aided content analysis of verbal and non-verbal communication in social networks, especially instant messaging, may capture emotional and social contagion. A further way to identify a policy bubble revolves around studying bubble expectations and individuals’ confidence over time by distributing a questionnaire to a random sample of the population, experts in the relevant policy sub-field, as well as decision makers, and comparing the results across time and nations.
To sum up, my interpretation of the process that leads to the emergence of policy bubbles allows for the possibility that different modes of policy overreaction lead to different types of human herding, thereby resulting in different types of policy bubbles. This interpretation has the added benefit of contributing to the explanation of economic, financial, technological and social bubbles as well”

OkCupid reveals it’s been lying to some of its users. Just to see what’ll happen.


Brian Fung in the Washington Post: “It turns out that OkCupid has been performing some of the same psychological experiments on its users that landed Facebook in hot water recently.
In a lengthy blog post, OkCupid cofounder Christian Rudder explains that OkCupid has on occasion played around with removing text from people’s profiles, removing photos, and even telling some users they were an excellent match when in fact they were only a 30 percent match according to the company’s systems. Just to see what would happen.
OkCupid defends this behavior as something that any self-respecting Web site would do.
“OkCupid doesn’t really know what it’s doing. Neither does any other Web site,” Rudder wrote. “But guess what, everybody: if you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work.”…
we have a bigger problem on our hands: A problem about how to reconcile the sometimes valuable lessons of data science with the creep factor — particularly when you aren’t notified about being studied. But as I’ve written before, these kinds of studies happen all the time; it’s just rare that the public is presented with the results.
Short of banning the practice altogether, which seems totally unrealistic, corporate data science seems like an opportunity on a number of levels, particularly if it’s disclosed to the public. First, it helps us understand how human beings tend to behave at Internet scale. Second, it tells us more about how Internet companies work. And third, it helps consumers make better decisions about which services they’re comfortable using.
I suspect that what bothers us most of all is not that the research took place, but that we’re slowly coming to grips with how easily we ceded control over our own information — and how the machines that collect all this data may all know more about us than we do ourselves. We had no idea we were even in a rabbit hole, and now we’ve discovered we’re 10 feet deep. As many as 62.5 percent of Facebook users don’t know the news feed is generated by a company algorithm, according to a recent study conducted by Christian Sandvig, an associate professor at the University of Michigan, and Karrie Karahalios, an associate professor at the University of Illinois.
OkCupid’s blog post is distinct in several ways from Facebook’s psychological experiment. OkCupid didn’t try to publish its findings in a scientific journal. It isn’t even claiming that what it did was science. Moreover, OkCupid’s research is legitimately useful to users of the service — in ways that Facebook’s research is arguably not….
But in any case, there’s no such motivating factor when it comes to Facebook. Unless you’re a page administrator or news organization, understanding how the newsfeed works doesn’t really help the average user in the way that understanding how OkCupid works does. That’s because people use Facebook for all kinds of reasons that have nothing to do with Facebook’s commercial motives. But people would stop using OkCupid if they discovered it didn’t “work.”
If you’re lying to your users in an attempt to improve your service, what’s the line between A/B testing and fraud?”

The Social Laboratory


Shane Harris in Foreign Policy: “…, Singapore has become a laboratory not only for testing how mass surveillance and big-data analysis might prevent terrorism, but for determining whether technology can be used to engineer a more harmonious society….Months after the virus abated, Ho and his colleagues ran a simulation using Poindexter’s TIA ideas to see whether they could have detected the outbreak. Ho will not reveal what forms of information he and his colleagues used — by U.S. standards, Singapore’s privacy laws are virtually nonexistent, and it’s possible that the government collected private communications, financial data, public transportation records, and medical information without any court approval or private consent — but Ho claims that the experiment was very encouraging. It showed that if Singapore had previously installed a big-data analysis system, it could have spotted the signs of a potential outbreak two months before the virus hit the country’s shores. Prior to the SARS outbreak, for example, there were reports of strange, unexplained lung infections in China. Threads of information like that, if woven together, could in theory warn analysts of pending crises.
The RAHS system was operational a year later, and it immediately began “canvassing a range of sources for weak signals of potential future shocks,” one senior Singaporean security official involved in the launch later recalled.
The system uses a mixture of proprietary and commercial technology and is based on a “cognitive model” designed to mimic the human thought process — a key design feature influenced by Poindexter’s TIA system. RAHS, itself, doesn’t think. It’s a tool that helps human beings sift huge stores of data for clues on just about everything. It is designed to analyze information from practically any source — the input is almost incidental — and to create models that can be used to forecast potential events. Those scenarios can then be shared across the Singaporean government and be picked up by whatever ministry or department might find them useful. Using a repository of information called an ideas database, RAHS and its teams of analysts create “narratives” about how various threats or strategic opportunities might play out. The point is not so much to predict the future as to envision a number of potential futures that can tell the government what to watch and when to dig further.
The officials running RAHS today are tight-lipped about exactly what data they monitor, though they acknowledge that a significant portion of “articles” in their databases come from publicly available information, including news reports, blog posts, Facebook updates, and Twitter messages. (“These articles have been trawled in by robots or uploaded manually” by analysts, says one program document.) But RAHS doesn’t need to rely only on open-source material or even the sorts of intelligence that most governments routinely collect: In Singapore, electronic surveillance of residents and visitors is pervasive and widely accepted…”