Recent Developments in Open Data Policy

Curated on Posted on by Stefaan Verhulst

Presentation by Paul Uhlir:  “Several International organizations have issued policy statements on open data policies in the past two years. This presentation provides an overview of those statements and their relevance to developing countries.

International Statements on Open Data Policy

Open data policies have become much more supported internationally in recent years. Policy statements in just the most recent 2014-2016 period that endorse and promote openness to research data derived from public funding include: the African Data Consensus (UNECA 2014); the CODATA Nairobi Principles for Data Sharing for Science and Development in Developing Countries (PASTD 2014); the Hague Declaration on Knowledge Discovery in the Digital Age (LIBER 2014); Policy Guidelines for Open Access and Data Dissemination and Preservation (RECODE 2015); Accord on Open Data in a Big Data World (Science International 2015). This presentation will present the principal guidelines of these policy statements.

The Relevance of Open Data from Publicly Funded Research for Development

There are many reasons that publicly funded research data should be made as freely and openly available as possible. Some of these are noted here, although many other benefits are possible. For research, it is closing the gap with more economically developed countries, making researchers more visible on the web, enhancing their collaborative potential, and linking them globally. For educational benefits, open data assists greatly in helping students learn how to do data science and to manage data better. From a socioeconomic standpoint, open data policies have been shown to enhance economic opportunities and to enable citizens to improve their lives in myriad ways. Such policies are more ethical in allowing access to those that have no means to pay and not having to pay for the data twice—once through taxes to create the data in the first place and again at the user level . Finally, access to factual data can improve governance, leading to better decision making by policymakers, improved oversight by constituents, and digital repatriation of objects held by former colonial powers.

Some of these benefits are cited directly in the policy statements themselves, while others are developed more fully in other documents (Bailey Mathae and Uhlir 2012, Uhlir 2015). Of course, not all publicly funded data and information can be made available and there are appropriate reasons—such as the protection of national security, personal privacy, commercial concerns, and confidentiality of all kinds—that make the withholding of them legal and ethical. However, the default rule should be one of openness, balanced against a legitimate reason not to make the data public….(More)”

The Ethics of Influence: Government in the Age of Behavioral Science

Curated on Posted on by Stefaan Verhulst

New book by Cass R. Sunstein: “In recent years, ‘Nudge Units’ or ‘Behavioral Insights Teams’ have been created in the United States, the United Kingdom, Germany, and other nations. All over the world, public officials are using the behavioral sciences to protect the environment, promote employment and economic growth, reduce poverty, and increase national security. In this book, Cass R. Sunstein, the eminent legal scholar and best-selling co-author of Nudge (2008), breaks new ground with a deep yet highly readable investigation into the ethical issues surrounding nudges, choice architecture, and mandates, addressing such issues as welfare, autonomy, self-government, dignity, manipulation, and the constraints and responsibilities of an ethical state. Complementing the ethical discussion, The Ethics of Influence: Government in the Age of Behavioral Science contains a wealth of new data on people’s attitudes towards a broad range of nudges, choice architecture, and mandates…(More)”

Trust in Government

Curated on Posted on by Stefaan Verhulst

First issue of the Government Oxford Review focusing on trust (or lack of trust) in government:

“In 2016, governments are in the firing line. Their populations suspect them of accelerating globalisation for the benefit of the few, letting trade drive away jobs, and encouraging immigration so as to provide cheaper labour and to fill skills-gaps without having to invest in training. As a result the ‘anti-government’, ‘anti-expert’, ‘anti-immigration’ movements are rapidly gathering support. The Brexit campaign in the United Kingdom, the Presidential run of Donald Trump in the United States, and the Five Star movement in Italy are but three examples.” Dean Ngaire Woods

Our contributors have shed an interesting, and innovative, light on this issue. McKinsey’s Andrew Grant and Bjarne Corydon discuss the importance of transparency and accountability of government, while Elizabeth Linos, from the Behavioural Insights Team in North America, and Princeton’s Eldar Shafir discuss how behavioural science can be utilised to implement better policy, and Geoff Mulgan, CEO at Nesta, provides insights into how harnessing technology can bring about increased collective intelligence.

The Conference Addendum features panel summaries from the 2016 Challenges of Government Conference, written by our MPP and DPhil in Public Policy students.

Documents:
PDF icon Oxford Government Review 1 – The Trust Issue
PDF icon Oxford Government Review 1 – Conference addendum (More)”

Data for Policy: Data Science and Big Data in the Public Sector

Curated on Posted on by Stefaan Verhulst

Innar Liiv at OXPOL: “How can big data and data science help policy-making? This question has recently gained increasing attention. Both the European Commission and the White House have endorsed the use of data for evidence-based policy making.

Still, a gap remains between theory and practice. In this blog post, I make a number of recommendations for systematic development paths.

RESEARCH TRENDS SHAPING DATA FOR POLICY

‘Data for policy’ as an academic field is still in its infancy. A typology of the field’s foci and research areas are summarised in the figure below.

 

diagram1

 

Besides the ‘data for policy’ community, there are two important research trends shaping the field: 1) computational social science; and 2) the emergence of politicised social bots.

Computational social science (CSS) is an new interdisciplinary research trend in social science, which tries to transform advances in big data and data science into research methodologies for understanding, explaining and predicting underlying social phenomena.

Social science has a long tradition of using computational and agent-based modelling approaches (e.g.Schelling’s Model of Segregation), but the new challenge is to feed real-life, and sometimes even real-time information into those systems to get gain rapid insights into the validity of research hypotheses.

For example, one could use mobile phone call records to assess the acculturation processes of different communities. Such a project would involve translating different acculturation theories into computational models, researching the ethical and legal issues inherent in using mobile phone data and developing a vision for generating policy recommendations and new research hypothesis from the analysis.

Politicised social bots are also beginning to make their mark. In 2011, DARPA solicited research proposals dealing with social media in strategic communication. The term ‘political bot’ was not used, but the expected results left no doubt about the goals…

The next wave of e-government innovation will be about analytics and predictive models.  Taking advantage of their potential for social impact will require a solid foundation of e-government infrastructure.

The most important questions going forward are as follows:

  • What are the relevant new data sources?
  • How can we use them?
  • What should we do with the information? Who cares? Which political decisions need faster information from novel sources? Do we need faster information? Does it come with unanticipated risks?

These questions barely scratch the surface, because the complex interplay between general advancements of computational social science and hovering satellite topics like political bots will have an enormous impact on research and using data for policy. But, it’s an important start….(More)”

Ideas to help civil servants understand the opportunities of data

Curated on Posted on by Stefaan Verhulst

, at Gov.UK: “Back in April we set out our plan for the discovery phase for what we are now calling “data science literacy”. We explained that we were going to undertake user research with civil servants to understand how they use data. The discovery phase has helped clarify the focus of this work, and we have now begun to develop options for a data science literacy service for government.

Discovery has helped us understand what we really mean when we say ‘data literacy’. For one person it can be a basic understanding of statistics, but to someone else it might mean knowledge of new data science approaches. But on the basis of our exploration, we have started to use the term “data science literacy” to mean the ability to understand how new data science techniques and approaches can be applied in real world contexts in the civil service, and to distinguish it from a broader definition of ‘data literacy’….

In the spirit of openness and transparency we are making this long list of ideas available here:

Data science driven apps

One way in which civil servants could come to understand the opportunities of data science would be to experience products and services which are driven by data science in their everyday roles. This could be something like having a recommendation engine for actions provided to them on the basis of information already held on the customer.

Sharing knowledge across government

A key user need from our user research was to understand how others had undertaken data science projects in government. This could be supported by something like a series of videos / podcasts created by civil servants, setting out case studies and approaches to data science in government. Alternatively, we could have a regularly organised speaker series where data science projects across government are presented alongside outside speakers.

Support for using data science in departments

Users in departments need to understand and experience data science projects in government so that they can undertake their own. Potentially this could be achieved through policy, analytical and data science colleagues working in multidisciplinary teams. Colleagues could also be supported by tools of differing levels of complexity ranging from a simple infographic showing at a high level the types of data available in a department to an online tool which diagnoses which approach people should take for a data science project on the basis of their aims and the data available to them.

In practice training

Users could learn more about how to use data science in their jobs by attending more formal training courses. These could take the form of something like an off-site, week-long training course where they experience the stages of undertaking a data science project (similar to the DWP Digital Academy). An alternative model could be to allocate one day a week to work on a project with departmental importance with a data scientist (similar to theData Science Accelerator Programme for analysts).

IMG_1603

Cross-government support for collaboration

For those users who have responsibility for leading on data science transformation in their departments there is also a need to collaborate with others in similar roles. This could be achieved through interventions such as a day-long unconference to discuss anything related to data science, and using online tools such as Google Groups, Slack, Yammer, Trello etc. We also tested the idea of a collaborative online resource where data science leads and others can contribute content and learning materials / approaches.

This is by no means an exhaustive list of potential ways to encourage data science thinking by policy and delivery colleagues across government. We hope this list is of interest to others in the field and we will update in the next six months about the transition of this project to Alpha….(More)”

Civil Solutions

Curated on Posted on by Stefaan Verhulst

Brian R. Calfano on “addressing social and political ills through the solutions journalism approach” in The Blue Review: “…To effectively work in the public interest as a member of the media covering politics in a national election year, I argue that stories evaluating and proposing solutions to our major societal problems must be an integral part of the media menu served to the public. Solutions are certainly not the only thing we need to cover in the media, but greater focus on problem solving is needed than what is provided at present.

A “solutions journalism” approach to covering political stories holds promise because it focuses attention on the evaluation of effectiveness in dealing with some of the most pressing problems we face as a society. Along the way, the solutions-based focus may even tamp down the incivility that plagues our politics.The author is a member of the Solutions Journalism Network.

So, how do we get started with a solutions journalism approach?

The Solutions Journalism Network has already done much of the legwork in setting up the scaffolding for journalists looking to sink their teeth into the consideration of “what works” in solving a social problem.

In their Solutions Journalism Toolkit (2015, pdf), the Solutions Journalism Network suggests focusing on the following questions when determining a topic to cover (pgs. 6-7):

  • Does the story explain the causes of social problem?
  • Does the story present an associated response to that problem?
  • Does the story get into the problem solving and how to details of implementation?
  • Does the story present evidence of results linked to the response?
  • Does the story explain limitations of the response?
  • Does the story convey an insight or teachable lesson?

…Most interesting about this approach is that it calls on my experience as a social science researcher. I’m tempted to go into full researcher mode and critique the all-too-frequent use of basic cross-tabulations and observational survey data as means for showing cause and effect. Generally speaking, audiences may not care about research methods, but my job is to make the story compelling enough — including the bits about methodology — to make them interested.

Importantly, I’m not alone in this effort. Sources like the website evidencebasedprograms.org feature a litany of randomized controlled trials that allow determination of direct impact from a policy intervention on issues like the “cliff effect.”

My work is made more difficult if the organizations I interview for the solutions journalism stories on the “cliff effect” are not using the randomized trial approach. At the least, I’ll have to point out to the viewer that the solutions an organization proposes are not being evaluated with the strongest possible assessment tools. This is not so much a problem, however, as an opportunity, as the organization might benefit from the critique of its own evaluation practices to find what works “better than average.”…(More)”.

Citizen Scientist

Curated on Posted on by Stefaan Verhulst

Book by Mary Ellen Hannibal: “…Here is a wide-ranging adventure in becoming a citizen scientist by an award-winning writer and environmental thought leader. As Mary Ellen Hannibal wades into tide pools, follows hawks, and scours mountains to collect data on threatened species, she discovers the power of a heroic cast of volunteers—and the makings of what may be our last, best hope in slowing an unprecedented mass extinction.

Digging deeply, Hannibal traces today’s tech-enabled citizen science movement to its roots: the centuries-long tradition of amateur observation by writers and naturalists. Prompted by her novelist father’s sudden death, she also examines her own past—and discovers a family legacy of looking closely at the world. With unbending zeal for protecting the planet, she then turns her gaze to the wealth of species left to fight for.

Combining original reporting, meticulous research, and memoir in impassioned prose, Citizen Scientist is a literary event, a blueprint for action, and the story of how one woman rescued herself from an odyssey of loss—with a new kind of science….(More)”

Situation vacant: technology triathletes wanted

Curated on Posted on by Stefaan Verhulst

Anne-Marie Slaughter in the Financial Times: “It is time to celebrate a new breed of triathletes, who work in technology. When I was dean in the public affairs school at Princeton, I would tell students to aim to work in the public, private and civic sectors over the course of their careers.

Solving public problems requires collaboration among government, business and civil society. Aspiring problem solvers need the culture and language of all three sectors and to develop a network of contacts in each.

The public problems we face, in the US and globally, require lawyers, economists and issue experts but also technologists. A lack of technologists capable of setting up HealthCare.gov, a website designed to implement the Affordable Care act, led President Barack Obama to create the US Digital Service, which deploys Swat tech teams to address specific problems in government agencies.

But functioning websites that deliver government services effectively are only the most obvious technological need for the public sector.

Government can reinvent how it engages with citizens entirely, for example by personalising public education with digital feedback or training jobseekers. But where to find the talent? The market for engineers, designers and project managers sees big tech companies competing for graduates from the world’s best universities.

Governments can offer only a fraction of those salaries, combined with a rigid work environment, ingrained resistance to innovation and none of the amenities and perks so dear to Silicon Valley .

Government’s comparative advantage, however, is mission and impact, which is precisely what Todd Park sells…Still, demand outstrips supply. ….The goal is to create an ecosystem for public interest technology comparable to that in public interest law. In the latter, a number of American philanthropists created role models, educational opportunities and career paths for aspiring lawyers who want to change the world.

That process began in the 1960s, and today every great law school has a public interest programme with scholarships for the most promising students. Many branches of government take on top law school graduates. Public interest lawyers coming out of government find jobs with think-tanks and advocacy organisations and take up research fellowships, often at the law schools that educated them. When they need to pay the mortgage or send their kids to college, they can work at large law firms with pro bono programmes….We need much more. Every public policy school at a university with a computer science, data science or technology design programme should follow suit. Every think-tank should also become a tech tank. Every non-governmental organisation should have at least one technologist on staff. Every tech company should have a pro bono scheme rewarding public interest work….(More)”

Encouraging and Sustaining Innovation in Government: Technology and Innovation in the Next Administration

Curated on Posted on by Stefaan Verhulst

New report by Beth Simone Noveck and Stefaan Verhulst: “…With rates of trust in government at an all-time low, technology and innovation will be essential to achieve the next administration’s goals and to deliver services more effectively and efficiently. The next administration must prioritize using technology to improve governing and must develop plans to do so in the transition… This paper provides analysis and a set of concrete recommendations, both for the period of transition before the inauguration, and for the start of the next presidency, to encourage and sustain innovation in government. Leveraging the insights from the experts who participated in a day-long discussion, we endeavor to explain how government can improve its use of using digital technologies to create more effective policies, solve problems faster and deliver services more effectively at the federal, state and local levels….

The broad recommendations are:

  • Scale Data Driven Governance: Platforms such as data.gov represent initial steps in the direction of enabling data-driven governance. Much more can be done, however, to open-up data and for the agencies to become better consumers of data, to improve decision-making and scale up evidence-based governance. This includes better use of predictive analytics, more public engagement; and greater use of cutting-edge methods like machine learning.
  • Scale Collaborative Innovation: Collaborative innovation takes place when government and the public work together, thus widening the pool of expertise and knowledge brought to bear on public problems. The next administration can reach out more effectively, not just to the public at large, but to conduct targeted outreach to public officials and citizens who possess the most relevant skills or expertise for the problems at hand.
  • Promote a Culture of Innovation: Institutionalizing a culture of technology-enabled innovation will require embedding and institutionalizing innovation and technology skills more widely across the federal enterprise. For example, contracting, grants and personnel officials need to have a deeper understanding of how technology can help them do their jobs more efficiently, and more people need to be trained in human-centered design, gamification, data science, data visualization, crowdsourcing and other new ways of working.
  • Utilize Evidence-Based Innovation: In order to better direct government investments, leaders need a much better sense of what works and what doesn’t. The government spends billions on research in the private and university sectors, but very little experimenting with, testing, and evaluating its own programs. The next administration should continue developing an evidence-based approach to governance, including a greater use of methods like A/B testing (a method of comparing two versions of a webpage or app against each other to determine which one performs the best); establishing a clearinghouse for success and failure stories and best practices; and encouraging overseers to be more open to innovation.
  • Make Innovation a Priority in the Transition: The transition period represents a unique opportunity to seed the foundations for long-lasting change. By explicitly incorporating innovation into the structure, goals and activities of the transition teams, the next administration can get a fast start in implementing policy goals and improving government operations through innovation approaches….(More)”

How the Federal Government is thinking about Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Mohana Ravindranath at NextGov: “Since May, the White House has been exploring the use of artificial intelligence and machine learning for the public: that is, how the federal government should be investing in the technology to improve its own operations. The technologies, often modeled after the way humans take in, store and use new information, could help researchers find patterns in genetic data or help judges decide sentences for criminals based on their likelihood to end up there again, among other applications. …

Here’s a look at how some federal groups are thinking about the technology:

  • Police data: At a recent White House workshop, Office of Science and Technology Policy Senior Adviser Lynn Overmann said artificial intelligence could help police departments comb through hundreds of thousands of hours of body-worn camera footage, potentially identifying the police officers who are good at de-escalating situations. It also could help cities determine which individuals are likely to end up in jail or prison and officials could rethink programs. For example, if there’s a large overlap between substance abuse and jail time, public health organizations might decide to focus their efforts on helping people reduce their substance abuse to keep them out of jail.
  • Explainable artificial intelligence: The Pentagon’s research and development agency is looking for technology that can explain to analysts how it makes decisions. If people can’t understand how a system works, they’re not likely to use it, according to a broad agency announcement from the Defense Advanced Research Projects Agency. Intelligence analysts who might rely on a computer for recommendations on investigative leads must “understand why the algorithm has recommended certain activity,” as do employees overseeing autonomous drone missions.
  • Weather detection: The Coast Guard recently posted its intent to sole-source a contract for technology that could autonomously gather information about traffic, crosswind, and aircraft emergencies. That technology contains built-in artificial intelligence technology so it can “provide only operational relevant information.”
  • Cybersecurity: The Air Force wants to make cyber defense operations as autonomous as possible, and is looking at artificial intelligence that could potentially identify or block attempts to compromise a system, among others.

While there are endless applications in government, computers won’t completely replace federal employees anytime soon….(More)”