education

Website Seeks to Make Government Data Easier to Sift Through

Curated on April 5, 2016August 3, 2018 by Stefaan Verhulst

Steve Lohr at the New York Times: “For years, the federal government, states and some cities have enthusiastically made vast troves of data open to the public. Acres of paper records on demographics, public health, traffic patterns, energy consumption, family incomes and many other topics have been digitized and posted on the web.

This abundance of data can be a gold mine for discovery and insights, but finding the nuggets can be arduous, requiring special skills.

A project coming out of the M.I.T. Media Lab on Monday seeks to ease that challenge and to make the value of government data available to a wider audience. The project, called Data U S A, bills itself as “the most comprehensive visualization of U.S. public data.” It is free, and its software code is open source, meaning that developers can build custom applications by adding other data.

Cesar A. Hidalgo, an assistant professor of media arts and sciences at the M.I.T. Media Lab who led the development of Data USA, said the website was devised to “transform data into stories.” Those stories are typically presented as graphics, charts and written summaries….Type “New York” into the Data USA search box, and a drop-down menu presents choices — the city, the metropolitan area, the state and other options. Select the city, and the page displays an aerial shot of Manhattan with three basic statistics: population (8.49 million), median household income ($52,996) and median age (35.8).

Lower on the page are six icons for related subject categories, including economy, demographics and education. If you click on demographics, one of the so-called data stories appears, based largely on data from the American Community Survey of the United States Census Bureau.

Using colorful graphics and short sentences, it shows the median age of foreign-born residents of New York (44.7) and of residents born in the United States (28.6); the most common countries of origin for immigrants (the Dominican Republic, China and Mexico); and the percentage of residents who are American citizens (82.8 percent, compared with a national average of 93 percent).

Data USA features a selection of data results on its home page. They include the g ender w age g ap in Connecticut; the r acial b reakdown of po verty in Flint, Mich.; the wages of p hysicians and s urgeons across the United States; and the institutions that award the most c omputer s cience degrees….(More)

Accountable machines: bureaucratic cybernetics?

Curated on March 28, 2016November 14, 2018 by Stefaan Verhulst

Alison Powell at LSE Media Policy Project Blog: “Algorithms are everywhere, or so we are told, and the black boxes of algorithmic decision-making make oversight of processes that regulators and activists argue ought to be transparent more difficult than in the past. But when, and where, and which machines do we wish to make accountable, and for what purpose? In this post I discuss how algorithms discussed by scholars are most commonly those at work on media platforms whose main products are the social networks and attention of individuals. Algorithms, in this case, construct individual identities through patterns of behaviour, and provide the opportunity for finely targeted products and services. While there are serious concerns about, for instance, price discrimination, algorithmic systems for communicating and consuming are, in my view, less inherently problematic than processes that impact on our collective participation and belonging as citizenship. In this second sphere, algorithmic processes – especially machine learning – combine with processes of governance that focus on individual identity performance to profoundly transform how citizenship is understood and undertaken.

Communicating and consuming

In the communications sphere, algorithms are what makes it possible to make money from the web for example through advertising brokerage platforms that help companies bid for ads on major newspaper websites. IP address monitoring, which tracks clicks and web activity, creates detailed consumer profiles and transform the everyday experience of communication into a constantly-updated production of consumer information. This process of personal profiling is at the heart of many of the concerns about algorithmic accountability. The consequence of perpetual production of data by individuals and the increasing capacity to analyse it even when it doesn’t appear to relate has certainly revolutionalised advertising by allowing more precise targeting, but what has it done for areas of public interest?

John Cheney-Lippold identifies how the categories of identity are now developed algorithmically, since a category like gender is not based on self-discloure, but instead on patterns of behaviour that fit with expectations set by previous alignment to a norm. In assessing ‘algorithmic identities’, he notes that these produce identity profiles which are narrower and more behaviour-based than the identities that we perform. This is a result of the fact that many of the systems that inspired the design of algorithmic systems were based on using behaviour and other markers to optimise consumption. Algorithmic identity construction has spread from the world of marketing to the broader world of citizenship – as evidenced by the Citizen Ex experiment shown at the Web We Want Festival in 2015.

Individual consumer-citizens

What’s really at stake is that the expansion of algorithmic assessment of commercially derived big data has extended the frame of the individual consumer into all kinds of other areas of experience. In a supposed ‘age of austerity’ when governments believe it’s important to cut costs, this connects with the view of citizens as primarily consumers of services, and furthermore, with the idea that a citizen is an individual subject whose relation to a state can be disintermediated given enough technology. So, with sensors on your garbage bins you don’t need to even remember to take them out. With pothole reporting platforms like FixMyStreet, a city government can be responsive to an aggregate of individual reports. But what aspects of our citizenship are collective? When, in the algorithmic state, can we expect to be together?

Put another way, is there any algorithmic process to value the long term education, inclusion, and sustenance of a whole community for example through library services?…

Seeing algorithms – machine learning in particular – as supporting decision-making for broad collective benefit rather than as part of ever more specific individual targeting and segmentation might make them more accountable. But more importantly, this would help algorithms support society – not just individual consumers….(More)”

Big data, meet behavioral science

Curated on March 14, 2016August 3, 2018 by Stefaan Verhulst

Ben Castleman at Brookings: “America’s community colleges offer the promise of a more affordable pathway to a bachelor’s degree. Students can pay substantially less for the first two years of college, transfer to a four-year college or university, and still earn their diploma in the same amount of time. At least in theory. Most community college students—80 percent of them—enter with the intention to transfer, but only 20 percent actually do so within five years of entering college. This divide represents a classic case of what behavioralists call an intention-action gap.

Why would so many students who enter community colleges intending to transfer fail to actually do so? Put yourself in the shoes of a 20-something community college student. You’ve worked hard for the past couple years, earning credits and paying a lot less in tuition than you would have if you had enrolled immediately in a four-year college or university. But now you want to transfer, so that you can complete your bachelor’s degree. How do you figure out where to go? Ideally you’d probably like to find a college that would take most of your credits, where you’re likely to graduate from, and where the degree is going to count for something in the labor market. A college advisor could probably help you figure this out,but at many community colleges there are at least 1,000 other students assigned to your advisor, so you might have a hard time getting a quality meeting. Some states have articulation agreements between two- and four-year institutions that guarantee admission for students who complete certain course sequences and perform at a high enough level. But these agreements are often dense and inaccessible.

The combination of big data and behavioral insights has the potential to help students navigate these complex decisions and successfully follow through on their intentions. Big data analytic techniques allow us to identify concrete transfer pathways where students are positioned to succeed; behavioral insights ensure we communicate these options in a way that maximizes students’ engagement and responsiveness…..A growing body of innovative research has demonstrated that, by applying behavioral science insights to the way we communicate with students and families about the opportunities and resources available to them, we can help people navigate these complex decisions and experience better outcomes as a result. A combination of simplified information, reminders, and access to assistance have improved achievement and attainment up and down the education pipeline, nudging parents to practice early-literacy activities with their kids or check in with their high schoolers about missed assignments, andencouraging students to renew their financial aid for college….

These types of big data techniques are already being used in some education sectors. For instance, a growing number of colleges use predictive analytics to identify struggling students who need additional assistance, so faculty and administrators can intervene before the student drops out. But frequently there is insufficient attention, once the results of these predictive analyses are in hand, about how to communicate the information in a way that is likely to lead to behavior change among students or educators. And much of the predictive analytics work has been on the side of plugging leaks in the pipeline (e.g. preventing drop-outs from higher education), rather than on the side of proactively sending students and families personalized information about educational and career pathways where they are likely to flourish…(More)”

Community Engagement Matters (Now More Than Ever)

Curated on March 7, 2016August 3, 2018 by Stefaan Verhulst

Melody Barnes & Paul Schmitz at Stanford Social Innovation Review: “…Data-driven and evidence-based practices present new opportunities for public and social sector leaders to increase impact while reducing inefficiency. But in adopting such approaches, leaders must avoid the temptation to act in a top-down manner. Instead, they should design and implement programs in ways that engage community members directly in the work of social change. …

Under the sponsorship of an organization called Results for America, we recently undertook a research project that focused on how leaders can and should pursue data-driven social change efforts. For the project, we interviewed roughly 30 city administrators, philanthropists, nonprofit leaders, researchers, and community builders from across the United States. We began this research with a simple premise: Social change leaders now have an unprecedented ability to draw on data-driven insight about which programs actually lead to better results.

Leaders today know that babies born to mothers enrolled in certain home visiting programs have healthier birth outcomes. (The Nurse-Family Partnership, which matches first-time mothers with registered nurses, is a prime example of this type of intervention.³) They know that students in certain reading programs reach higher literacy levels. (Reading Partners, for instance, has shown impressive results with a program that provides one-on-one reading instruction to struggling elementary school students.⁴) They know that criminal offenders who enter job-training and support programs when they leave prison are less likely to re-offend and more likely to succeed in gaining employment. (The Center for Employment Opportunities has achieved such outcomes by offering life-skills education, short-term paid transitional employment, full-time job placement, and post-placement services.⁵)

Results for America, which launched in 2012, seeks to enable governments at all levels to apply data-driven approaches to issues related to education, health, and economic opportunity. In 2014, the organization published a book called Moneyball for Government. (The title is a nod to Moneyball, a book by Michael Lewis that details how the Oakland A’s baseball club used data analytics to build championship teams despite having a limited budget for player salaries.) The book features contributions by a wide range of policymakers and thought leaders (including Melody Barnes, a co-author of this article). The editors of Moneyball for Government, Jim Nussle and Peter Orszag, outline three principles that public officials should follow as they pursue social change:

“Build evidence about the practices, policies, and programs that will achieve the most effective and efficient results so that policymakers can make better decisions.
“Invest limited taxpayer dollars in practices, policies, and programs that use data, evidence, and evaluation to demonstrate they work.
“Direct funds away from practices, policies, and programs that consistently fail to achieve measurable outcomes.”⁶

These concepts sound simple. Indeed, they have the ring of common sense. Yet they do not correspond to the current norms of practice in the public and nonprofit sectors. According to one estimate, less than 1 percent of federal nondefense discretionary spending goes toward programs that are backed by evidence. In a 2014 report, Lisbeth Schorr and Frank Farrow note that the influence of evidence on decision-making—“especially when compared to the influence of ideology, politics, history, and even anecdotes”—has been weak among policymakers and social service providers. (Schorr is a senior fellow at the Center for the Study of Social Policy, and Farrow is director of the center.)

That needs to change. There is both an economic and a moral imperative for adopting data-driven approaches. Given persistently limited budgets, public and nonprofit leaders must direct funds to programs and initiatives that use data to show that they are achieving impact. Even if unlimited funds were available, moreover, leaders would have a responsibility to design programs that will deliver the best results for beneficiaries….

The Need for “Patient Urgency”

The inclination to move fast in creating and implementing data-driven programs and practices is understandable. After all, the problems that communities face today are serious and immediate. People’s lives are at stake. If there is evidence that a particular intervention can (for example) help more children get a healthy start in life—or help them read at grade level, or help them develop marketable skills—then setting that intervention in motion is pressingly urgent.

But acting too quickly in this arena entails a significant risk. All too easily, the urge to initiate programs expeditiously translates into a preference for top-down forms of management. Leaders, not unreasonably, are apt to assume that bottom-up methods will only slow the implementation of programs that have a record of delivering positive results.

A former director of data and analytics for a US city offers a cautionary tale that illustrates this idea. “We thought if we got better results for people, they would demand more of it,” she explains. “Our mayor communicated in a paternal way: ‘I know better than you what you need. I will make things better for you. Trust me.’ The problem is that they didn’t trust us. Relationships matter. Not enough was done to ask people what they wanted, to honor what they see and experience. Many of our initiatives died—not because they didn’t work but because they didn’t have community support.”

To win such support, policymakers and other leaders must treat community members as active partners. “Doing to us, not with us, is a recipe for failure,” says Fuller, who has deep experience in building community-led coalitions. “If we engage communities, then we have a solution and we have the leadership necessary to demand that solution and hold people accountable for it.” Engaging a community is not an activity that leaders can check off on a list. It’s a continuous process that aims to generate the support necessary for long-term change. The goal is to encourage intended beneficiaries not just to participate in a social change initiative but also to champion it.

“This work takes patient urgency,” Fuller argues. “If you aren’t patient, you only get illusory change. Lasting change is not possible without community. You may be gone in 5 or 10 years, but the community will still be there. You need a sense of urgency to push the process forward and maintain momentum.” The tension between urgency and patience is a productive tension. Navigating that tension allows leaders and community members to achieve the right level of engagement.

Rich Harwood, president of the Harwood Institute for Public Innovation, makes this point in a post on his website: “Understanding and strengthening a community’s civic culture is as important to collective efforts as using data, metrics and measuring outcomes. … A weak civic culture undermines the best intentions and the most rigorous of analyses and plans. For change to happen, trust and community ownership must form, people need to engage with one another, and we need to create the right underlying conditions and capabilities for change to take root and spread.”…(More)

Value public information so we can trust it, rely on it and use it

Curated on March 3, 2016August 3, 2018 by Stefaan Verhulst

Speech by David Fricker, the director general of the National Archives of Australia: “No-one can deny that we are in an age of information abundance. More and more we rely on information from a variety of sources and channels. Digital information is seductive, because it’s immediate, available and easy to move around. But digital information can be used for nefarious purposes. Social issues can be at odds with processes of government in this digital age. There is a tension between what is the information, where it comes from and how it’s going to be used.

How do we know if the information has reached us without being changed, whether that’s intentional or not?

How do we know that government digital information will be the authoritative source when the pace of information exchange is so rapid? In short, how do we know what to trust?

“It’s everyone’s responsibly to contribute to a transparent government, and that means changes in our thinking and in our actions.”

These are big questions, because there is a complexity about digital information that we don’t have with paper. Information has never been more complicated, but also never more important. There’s no going back — nor would we want to — but it means that time is ticking, because valuable government information is being lost — as I speak. I want you to share my sense of urgency about digital information, and act on what I’m going to say today.

Consider the challenges and risks that come with the digital age: what does it really mean to have transparency and integrity of government in today’s digital environment?…

What does the digital age mean for government? Government should be delivering services online, which means thinking about location, timeliness and information accessibility. It’s about getting public-sector data out there, into the public, making it available to fuel the digital economy. And it’s about a process of change across government to make sure that we’re breaking down all of those silos, and the duplication and fragmentation which exist across government agencies in the application of information, communications, and technology…..

The digital age is about the digital economy, it’s about rethinking the economy of the nation through the lens of information that enables it. It’s understanding that a nation will be enriched, in terms of culture life, prosperity and rights, if we embrace the digital economy. And that’s a weighty responsibility. But the responsibility is not mine alone. It’s a responsibility of everyone in the government who makes records in their daily work. It’s everyone’s responsibly to contribute to a transparent government. And that means changes in our thinking and in our actions….

What has changed about democracy in the digital age? Once upon a time if you wanted to express your anger about something, you might write a letter to the editor of the paper, to the government department, or to your local member and then expect some sort of an argument or discussion as a response. Now, you can bypass all of that. You might post an inflammatory tweet or blog, your comment gathers momentum, you pick the right hashtag, and off we go. It’s all happening: you’re trending on Twitter…..

If I turn to transparency now, at the top of the list is the basic recognition that government information is public information. The information of the government belongs to the people who elected that government. It’s a fundamental of democratic values. It also means that there’s got to be more public participation in the development of public policy, which means if you’re going to have evidence-based, informed, policy development; government information has to be available, anywhere, anytime….

Good information governance is at the heart of managing digital information to provide access to that information into the future — ready access to government information is vital for transparency. Only when information is digital and managed well can government share it effectively with the Australian community, to the benefit of society and the economy.

There are many examples where poor information management, or poor information governance, has led to failures — both in the private and public sectors. Professor Peter Shergold’s recent report, Learning from Failure, why large government policy initiatives have gone so badly wrong in the past and how the chances of success in the future can be improved, highlights examples such as the Home Insulation Program, the NBN and Building the Education Revolution….(Full Speech)

Crowd2Map Tanzania

Curated on February 22, 2016August 3, 2018 by Stefaan Verhulst

“Crowd2Map Tanzania is a new crowdsourcing initiative aimed at creating a comprehensive map ofTanzania, including detailed depictions of all of its villages, roads and public resources (such as schools, shops, offices etc.) in OpenStreetMap and/or Google Maps, both of which are sadly rather poor at the moment. (For a convincing example, see our post about a not-so-blank-as-map-suggests Zeze village here.)

…In February 2016, Crowd2Map Tanzania was one of the 7 projects selected in the Open Seventeenchallenge, which rallies the public to use open data as a means of achieving the 17 SustainableDevelopment Goals as proposed but the UN in September 2015! We are now excited to carry on with the helpof O17 partners – Citizen Cyberlab, The GovLab, ONE and SciFabric! We’re tackling Goal 11: creatingsustainable cities & communities and Goal 4: education through technology….(More)

Sticky-note strategy: How federal innovation labs borrow from Silicon Valley

Curated on February 18, 2016August 3, 2018 by Stefaan Verhulst

Carten Cordell in the Federal Times: “The framework for an integrated security solution in the Philippines is built on a bedrock of sticky notes. So is the strategy for combating piracy in East Africa and a handful of other plans that Zvika Krieger is crafting in a cauldron of collaboration within the State Department.

More specifically, Krieger, a senior adviser for strategy within the department’s Bureau of Political-Military Affairs, is working in the bureau’s Strategy Lab, just one pocket of federal government where a Silicon Valley-playbook for innovation is being used to develop policy solutions….

Krieger and a host of other policy thinkers learned a new way to channel innovation for policy solutions called human-centered design, or design thinking. While arguably new in government, the framework has long been in use by the tech sector to design products that will serve the needs of their customers. The strategy of group thinking towards a policy — which is more what these innovation labs seek to achieve — has been used before as well….Where the government has started to use HCD is in developing new policy solutions within a multifaceted group of stakeholders that can contribute a well-rounded slate of expertise. The product is a strategy that is developed from the creative thoughts of a team of experts, rather than a single specialized source….

The core tenet of HCD is to establish a meritocracy of ideas that is both empathetic of thought and immune to hierarchy. In order to get innovative solutions for a complex problem, Krieger forms a team of experts and stakeholders. He then mixes in outside thought leaders he calls “wild cards” to give the group outside perspective.

The delicate balance opens discussion and the mix of ideas ultimately form a strategy for handling the problem. That strategy might involve a technology; but it could also be a new partnership, a new function within an office, or a new acquisition program. Because the team is comprised of multiple experts, it can navigate the complexity more thoroughly, and the wild cards can offer their expertise to provide solutions the stakeholders may not have considered….

Human-centered design has been working its way through pockets of the federal government for a few years now. The Office of Personnel Management opened its Innovation Lab in 2012 and was tasked with improving the USAJobs website. The Department of Health and Human Services opened the IDEA Lab in 2013 to address innovation in its mission. The Department of Veteran Affairs has a Center of Innovation to identify new approaches to meet the current and future needs of veterans, and the departments of Defense and State both have innovation labs tackling policy solutions.

The concept is gaining momentum. This fall, the Obama administration released a strategy report calling for a network of innovation labs throughout federal agencies to develop new policy solutions through HCD.

“I think the word is spreading. It’s kind of like a whisper campaign, in the most positive way,” said an administration official with knowledge of innovation labs and HCD strategies, who was not authorized to speak to the press. “I think, again, the only constraint here is that we don’t have enough of them to be able to imbue this knowledge across government. We need many more people.”

A March 2014 GAO report said that the OPM Innovation Lab had not developed consistent performance targets that would allow it to assess the success of its projects. The report recommended more consistent milestones to assess progress, which the agency addressed through a series of pilot programs….

In the State Department’s Bureau of Educational and Cultural Affairs, an innovation lab called the Collaboratory is in its second year of existence, using HCD strategies to improve projects like the Fulbright program and other educational diplomacy efforts.

The Education Diplomacy initiative, for example, used HCD to devise ways to increase education access abroad using State resources. Defining U.S. embassies as the end user, the Collaboratory then analyzed the areas of need at the installations and began crafting policies.

“We identified a couple of area where we thought we could make substantial gains quite quickly and in a budget neutral way,” Collaboratory Deputy Director Paul Kruchoski said. The process allowed multiple stakeholders like the U.S. Agency for International Development, Peace Corps and the Department of Education to help craft the policy and create what Kruchoski called “feedback loops” to refine throughout the embassies…(More)”

Our finances are a mess – could behavioral science help clean them up?

Curated on February 17, 2016May 29, 2019 by Stefaan Verhulst

Katy Davis at the Conversation: “Typical approaches to solving problematic finances are either to “educate” people about the need to save more or to “incentivize” savings with monetary rewards.

But when we look at traditional financial education and counseling programs, they have had virtually no long-term impact on behavior. Similarly, matched savings programs are expensive and have shown mixed results on savings rates. Furthermore, these approaches often prioritize the need for savings while treating debt repayment as a secondary concern.

Education and incentives haven’t worked because they are based on problematic assumptions about lower-income consumers that turn out to be false….

The good news is that a range of simple, behaviorally informed solutions can easily be deployed to tackle these problems, from policy innovations to product redesign.

For instance, changing the “suggested payoff” in credit card statements for targeted segments (i.e., those who were already paying in full) could help consumers more effectively pay down debt, as could allowing tax refunds to be directly applied toward debt repayment. Well-designed budgeting tools that leverage financial technology could be integrated into government programs. The state of California, for example, is currently exploring ways to implement such technologies across a variety of platforms.

But the public and private sectors both need to play a role for these tools to be effective. Creating an integrated credit-and-saving product, for example, would require buy-in from regulators along with financial providers.

While these banking solutions may not close the economic inequality gap on their own, behaviorally informed design shifts can be the missing piece of the puzzle in these efforts to fix major problems.

Our research indicates that people already want to be doing a better job with their finances; we just need to make it a little less difficult for them….(More)”

How to Hold Governments Accountable for the Algorithms They Use

Curated on February 17, 2016November 14, 2018 by Stefaan Verhulst

Nicholas Diakopoulos in Slate: “In 2015 more than 59 million Americans received some form ofbenefit from the Social Security Administration, not just for retirement but also for disability or as a survivor of a deceased worker. It’s a behemoth of a government program, and keeping it solvent has preoccupied the Office of the Chief Actuary of theSocial Security Administration for years. That office makes yearly forecasts of key demographic (such as mortality rates) or economic (for instance, labor forceparticipation) factors that inform how policy can or should change to keep theprogram on sound financial footing. But a recent Harvard University study examinedseveral of these forecasts and found that they were systematically biased—underestimating life expectancy and implying that funds were on firmer financialground than warranted. The procedures and methods that the SSA uses aren’t openfor inspection either, posing challenges to replicating and debugging those predictivealgorithms.

Whether forecasting the solvency of social programs, waging a war, managingnational security, doling out justice and punishment, or educating the populace,government has a lot of decisions to make—and it’s increasingly using algorithms tosystematize and scale that bureaucratic work. In the ideal democratic state, theelectorate chooses a government that provides social goods and exercises itsauthority via regulation. The government is legitimate to the extent that it is heldaccountable to the citizenry. Though as the SSA example shows, tightly heldalgorithms pose issues of accountability that grind at the very legitimacy of thegovernment itself.

One of the immensely useful abilities of algorithms is to rank and prioritize hugeamounts of data, turning a messy pile of items into a neat and orderly list. In 2013 theObama administration announced that it would be getting into the business ofranking colleges, helping the citizens of the land identify and evaluate the “best”educational opportunities. But two years later, the idea of ranking colleges had beenneutered, traded in for what amounts to a data dump of educational statistics calledthe College Scorecard. The human influences, subjective factors, and methodologicalpitfalls involved in quantifying education into rankings would be numerous. Perhapsthe government sensed that any ranking would be dubious—that it would be riddledwith questions of what data was used and how various statistical factors wereweighted. How could the government make such a ranking legitimate in the eyes ofthe public and of the industry that it seeks to hold accountable?

That’s a complicated question that goes far beyond college rankings. But whatever theend goal, government needs to develop protocols for opening up algorithmic blackboxes to democratic processes.

Transparency offers one promising path forward. Let’s consider the new risk-assessment algorithm that the state of Pennsylvania is developing to help make criminal sentencing decisions. Unlike some other states that are pursuing algorithmiccriminal justice using proprietary systems, the level of transparency around thePennsylvania Risk Assessment Project is laudable, with several publicly available in-depth reports on the development of the system….(More)’