How Artificial Intelligence Will Usher in the Next Stage of E-Government


Daniel Castro at GovTech: “Since the earliest days of the Internet, most government agencies have eagerly explored how to use technology to better deliver services to citizens, businesses and other public-sector organizations. Early on, observers recognized that these efforts often varied widely in their implementation, and so researchers developed various frameworks to describe the different stages of growth and development of e-government. While each model is different, they all identify the same general progression from the informational, for example websites that make government facts available online, to the interactive, such as two-way communication between government officials and users, to the transactional, like applications that allow users to access government services completely online.

However, we will soon see a new stage of e-government: the perceptive.

The defining feature of the perceptive stage will be that the work involved in interacting with government will be significantly reduced and automated for all parties involved. This will come about principally from the integration of artificial intelligence (AI) — computer systems that can learn, reason and decide at levels similar to that of a human — into government services to make it more insightful and intelligent.

Consider the evolution of the Department of Motor Vehicles. The informational stage made it possible for users to find the hours for the local office; the interactive stage made it possible to ask the agency a question by email; and the transactional stage made it possible to renew a driver’s license online.

In the perceptive stage, the user will simply say, “Siri, I need a driver’s license,” and the individual’s virtual assistant will take over — collecting any additional information from the user, coordinating with the government’s system and scheduling any in-person meetings automatically. That’s right: AI might finally end your wait at the DMV.

In general, there are at least three ways that AI will impact government agencies. First, it will enable government workers to be more productive since the technology can be used to automate many tasks. …

Second, AI will create a faster, more responsive government. AI enables the creation of autonomous, intelligent agents — think online chatbots that answer citizens’ questions, real-time fraud detection systems that constantly monitor government expenditures and virtual legislative assistants that quickly synthesize feedback from citizens to lawmakers.

Third, AI will allow people to interact more naturally with digital government services…(More)”

Artificial Intelligence Could Help Colleges Better Plan What Courses They Should Offer


Jeffrey R. Young at EdSsurge: Big data could help community colleges better predict how industries are changing so they can tailor their IT courses and other programs. After all, if Amazon can forecast what consumers will buy and prestock items in their warehouses to meet the expected demand, why can’t colleges do the same thing when planning their curricula, using predictive analytics to make sure new degree or certificates programs are started just in time for expanding job opportunities?

That’s the argument made by Gordon Freedman, president of the nonprofit National Laboratory for Education Transformation. He’s part of a new center that will do just that, by building a data warehouse that brings together up-to-date information on what skills employers need and what colleges currently offer—and then applying artificial intelligence to attempt to predict when sectors or certain employment needs might be expanding.

He calls the approach “opportunity engineering,” and the center boasts some heavy-hitting players to assist in the efforts, including the University of Chicago, the San Diego Supercomputing Center and Argonne National Laboratory. It’s called the National Center for Opportunity Engineering & Analysis.

Ian Roark, vice president of workforce development at Pima Community College in Arizona, is among those eager for this kind of “opportunity engineering” to emerge.

He explains when colleges want to start new programs, they face a long haul—it takes time to develop a new curriculum, put it through an internal review, and then send it through an accreditor….

Other players are already trying to translate the job market into a giant data set to spot trends. LinkedIn sits on one of the biggest troves of data, with hundreds of millions of job profiles, and ambitions to create what it calls the “economic graph” of the economy. But not everyone is on LinkedIn, which attracts mainly those in white-collar jobs. And companies such as Burning Glass Technologies have scanned hundreds of thousands of job listings and attempt to provide real-time intelligence on what employers say they’re looking for. Those still don’t paint the full picture, Freedman argues, such as what jobs are forming at companies.

“We need better information from the employer, better information from the job seeker and better information from the college, and that’s what we’re going after,” Freedman says…(More)”.

Rethinking how we collect, share, and use development results data


Development Gateway: “The international development community spends a great deal of time, effort, and money gathering data on thousands of indicators embedded in various levels of Results Frameworks. These data comprise outputs (school enrollment, immunization figures), program outcomes (educational attainment, disease prevalence), and, in some cases, impacts (changes in key outcomes over time).

Ostensibly, we use results data to allocate resources to the places, partners, and programs most likely to achieve lasting success. But is this data good enough – and is it used well enough – to genuinely increase development impact in priority areas?

Experience suggests that decision-makers at all levels may often face inadequate, incorrect, late, or incomplete results data. At the same time, a figurative “Tower of Babel” of both project-level M&E and program-level outcome data can make it difficult for agencies and organizations to share and use data effectively. Further, potential users may not have the skills, resources, or enabling environment to meaningfully analyze and apply results data to decisions. With these challenges in mind, the development community needs to re-think its investments in results data, making sure that the right users are able to collect, share, and use this information to maximum effect.

Our Initiative

To this end, Development Gateway (DG), with the support of the Bill & Melinda Gates Foundation, aims to “diagnose” the results data ecosystem in three countries, identifying ways to improve data quality, sharing, and use in the health and agriculture sectors. Some of our important questions include:

  • Quality: Who collects data and how? Is data quality adequate? Does the data meet actual needs? How much time does data collection demand? How can data collection, quality, and reporting be improved?
  • Sharing: How can we compare results data from different donors, governments, and implementers? Is there demand for comparability? Should data be shared more freely? If so, how?
  • Use: How is results data analyzed and used to inform actual policies and plans? Does (or can) access to results data improve decision-making? Do the right people have the right data? How else can (or should) we promote data use?…(More)”

Tech is moving beyond cities to focus on civic engagement in every U.S. county


 at TechCrunch: “While gridlock has taken hold in a paralyzed Washington, D.C. mayors across the country are taking a pragmatic approach to solving local problems and its time for tech to reach out to them….

The United States has 3,0007 counties. And all of them have an appetite to shift the momentum from the federal government to the communities where people live and work. This can’t just involve coastal cities or urban areas within states. Rather, after Trump’s election, now is the moment to redouble policy efforts in communities across the country from states to rural counties.

Cities from Chicago, Los Angeles, Boston, to New York have been leading the way to think about how to provide better services and engagement opportunities.  They’ve been exciting places where rich networks of talent from academia to philanthropy have been helping foster ecosystems to catalyze new policy solutions….

There are a host of illustrative experiments occurring across communities that are leveraging policy innovation, data, and technology for more responsive and inclusive governance. The engagements that work focus on process to ensure that diverse stakeholders are a part of decision making….

Wisconsin:

In Eau Claire, Wisconsin a local organization called Clear Vision is teaming up with stakeholders on a poverty summit to reduce the number of people living poverty in income insecurity and build more resilient and inclusive communities. Citizen action groups will work on key issues they identify as part of the engagement process.

A key component of this poverty summit is to bring in traditionally marginalized communities into the process including low-income households, rural poor, youth and black and Hispanic communities. There is even a community-supported, nonprofit journalism site to support the local work in Eau Claire, Chippewa, and Dunn counties….

Oregon:

In Oregon, a “Kitchen Table” is enabling residents from across the state to contribute ideas, resources, and feedback to inform public policy. The Kitchen Table enables public officials to consult with representatives about key policy areas, crowdfund, and micro-lend for local startups and community businesses….

Another practice in Oregon is the Citizens Initiative Review, where a representative sampling of citizens convenes for deliberations over several days to discuss state ballot measures.  After being established by the state’s bipartisan legislature in 2009, there have been six random representative samples of citizens for multi-day deliberations to draft voting guides written for the people, by their neighbors….

 

This requires tapping into existing networks and civic organizations, leveraging data, technology and policy innovations, and re-shifting our focus from federal policy towards building an infrastructure of governance that is durable through collective development and buy-in from people…(More)”

Introducing the Agricultural Open Data Package: BETA Version


PressRelease: “GODAN, Open Data for Development (OD4D) Network, Open Data Charter, and the Open Data Institute are pleased to announce the release of the Agricultural Open Data Package: BETA version. …The Agriculture Open Data Package (http://AgPack.info) has been designed to help governments get to impact with open data in the agriculture sector. This practical resource provides key policy areas, key data categories, examples datasets, relevant interoperability initiatives, and use cases that policymakers and other stakeholders in the agriculture sector or open data should focus on, in order to address food security challenges.

The Package is meant as a source of inspiration and an invitation to start a national open data for agriculture initiative.

In the Package we identify fourteen key categories of data and discuss the effort it will take for a government to make this data available in a meaningful way. …

The Package also highlights more than ten use cases (the number is growing) demonstrating how open data is being harnessed to address sustainable agriculture and food security around the world. Examples include:

  • mapping water points to optimise scarce resource allocation in Burkina Faso

  • surfacing daily price information on multiple food commodities across India

  • benchmarking agricultural productivity in the Netherlands

Where relevant we also highlight applicable interoperability initiatives, such as open contracting, international aid transparency initiative (IATI), and global product classification (GPC) standards.

We recognise that the agriculture sector is diverse, with many contextual differences affecting scope of activities, priorities and capacities. In the full version of the Agricultural Open Data Package we discuss important implementation considerations such as inter-agency coordination and resourcing to develop an appropriate data infrastructure and a healthy data ‘ecosystem’ for agriculture….(More)”

21st Century Enlightenment Revisited


Matthew Taylor at the RSA: “The French historian Tzvetan Todorov describes the three essential ideas of the Enlightenment as ‘autonomy’, ‘universalism’ and ‘humanism’. The ideal of autonomy speaks to every individual’s right to self-determination. Universalism asserts that all human beings equally deserve basic rights and dignity (although, of course, in the 18th and 19th century most thinkers restricted this ambition to educated white men). The idea of humanism is that it is up to the people – not Gods or monarchs – through the use of rational inquiry to determine the path to greater human fulfilment….

21st Century Enlightenment 

Take autonomy; too often today we think of freedom either as a shrill demand to be able to turn our backs on wider society or in the narrow possessive terms of consumerism. Yet, brain and behavioural science have confirmed the intuition of philosophers through the ages genuine autonomy is something we only attain when we become aware of our human frailties and understand our truly social nature. Of course, freedom from oppression is the base line, but true autonomy is not a right to be granted but a goal to be pursued through self-awareness and engagement in society.

What of universalism, or social justice as we now tend to think of it? In most parts of the world and certainly in the West there have been incredible advances in equal rights. Discrimination and injustice still exist, but through struggle and reform huge strides have been made in widening the Enlightenment brotherhood of rich white men to women, people of different ethnicity, homosexuals and people with disabilities. Indeed the progress in legal equality over recent decades stands in contrast to the stubborn persistence, and even worsening, of social inequality, particularly based on class.

But the rationalist universalism of human rights needs an emotional corollary. People may be careful not to use the wrong words, but they still harbour resentment and suspicion towards other groups. …

Finally, humanism or the call of progress. The utilitarian philosophy that arose from the Enlightenment spoke to the idea that, free from the religious or autocratic dogma, the best routes to human fulfilment could be identified and should be pursued. The great motors of human progress – markets, science and technology, the modern state – shifted into gear and started to accelerate. Aspects of all these phenomena, indeed of Enlightenment ideas themselves, could be found at earlier stages of human history – what was different was the way they fed off each other and became dominant. Yet, in the process, the idea that these forces could deliver progress often became elided with the assumption that their development was the same as human progress.

Today this danger of letting the engines of progress determine the direction of the human journey feels particularly acute in relation to markets and technology. There is, for example, more discussion of how humans should best adapt to AI and robots than about how technological inquiry might be aligned with human fulfilment. The hollowing out of democratic institutions has diminished the space for public debate about what progress should comprise at just the time when the pace and scale of change makes those debates particularly vital.

A twenty first century enlightenment reinstates true autonomy over narrow ideas of freedom, it asserts a universalism based not just on legal status but on empathy and social connection and reminds us that humanism should lie at the heart of progress.

Think like a system act like an entrepreneur

There is one new strand I want to add to the 2010 account. In the face of many defeats, we must care as much about how we achieve change as about the goals we pursue. At the RSA we talk about ‘thinking like a system and acting like an entrepreneur’, a method which seeks to avoid the narrowness and path dependency of so many unsuccessful models of change. To alter the course our society is now on we need more fully to understand the high barriers to change but then to act more creatively and adaptively when we spot opportunities to take a different path….(More)”

Solving some of the world’s toughest problems with the Global Open Policy Report


 at Creative Commons: “Open Policy is when governments, institutions, and non-profits enact policies and legislation that makes content, knowledge, or data they produce or fund available under a permissive license to allow reuse, revision, remix, retention, and redistribution. This promotes innovation, access, and equity in areas of education, data, software, heritage, cultural content, science, and academia.

For several years, Creative Commons has been tracking the spread of open policies around the world. And now, with the new Global Open Policy Report (PDF) by the Open Policy Network, we’re able to provide a systematic overview of open policy development.

screen-shot-2016-12-02-at-5-57-09-pmThe first-of-its-kind report gives an overview of open policies in 38 countries, across four sectors: education, science, data and heritage. The report includes an Open Policy Index and regional impact and local case studies from Africa, the Middle East, Asia, Australia, Latin America, Europe, and North America. The index measures open policy strength on two scales: policy strength and scope, and level of policy implementation. The index was developed by researchers from CommonSphere, a partner organization of CC Japan.

The Open Policy Index scores were used to classify countries as either Leading, Mid-Way, or Delayed in open policy development. The ten countries with the highest scores are Argentina, Bolivia, Chile, France, Kyrgyzstan, New Zealand, Poland, South Korea, Tanzania, and Uruguay…(More)

Towards a transparency ontology in the context of open government


 and  at Electronic Government: “Several open government initiatives have been launched to make available online data enhancing accountability of public officials towards ordinary citizens. However, these initiatives raise several questions, namely: Which data should be disclosed? How to bring together dispersed (fragmented) data? How to improve its understandability by ordinary citizens? Literature shows that, in general, the data selection process does not take into account ordinary citizens’ expectations and information needs. This paper presents the development process of a transparency ontology, which aims to provide an answer to the above questions, in what concerns public sector entities’ use of resources. The process started by creating a list of relevant expressions/terms discussed in national and local newspapers, considering the role of journalists as ‘information brokers’ acting on behalf of ordinary citizens. This list was externally validated for relevance, comprehensiveness and improvements by interviewing journalists, and the resulting transparency ontology was formalised using OWL and Protégé….(More)”.

Too Much Democracy in All the Wrong Places: Toward a Grammar of Participation


Christopher M. Kelty at Current Anthropology: “Participation is a concept and practice that governs many aspects of new media and new publics. There are a wide range of attempts to create more of it and a surprising lack of theorization. In this paper I attempt to present a “grammar” of participation by looking at three cases where participation has been central in the contemporary moment of new, social media and the Internet as well as in the past, stretching back to the 1930s: citizen participation in public administration, workplace participation, and participatory international development. Across these three cases I demonstrate that the grammar of participation shifts from a language of normative enthusiasm to one of critiques of co-optation and bureaucratization and back again. I suggest that this perpetually aspirational logic results in the problem of “too much democracy in all the wrong places.”…(More)”

Saving Science


Daniel Sarewitz at the New Atlantis: “Science, pride of modernity, our one source of objective knowledge, is in deep trouble. Stoked by fifty years of growing public investments, scientists are more productive than ever, pouring out millions of articles in thousands of journals covering an ever-expanding array of fields and phenomena. But much of this supposed knowledge is turning out to be contestable, unreliable, unusable, or flat-out wrong. From metastatic cancer to climate change to growth economics to dietary standards, science that is supposed to yield clarity and solutions is in many instances leading instead to contradiction, controversy, and confusion. Along the way it is also undermining the four-hundred-year-old idea that wise human action can be built on a foundation of independently verifiable truths. Science is trapped in a self-destructive vortex; to escape, it will have to abdicate its protected political status and embrace both its limits and its accountability to the rest of society.

The story of how things got to this state is difficult to unravel, in no small part because the scientific enterprise is so well-defended by walls of hype, myth, and denial. But much of the problem can be traced back to a bald-faced but beautiful lie upon which rests the political and cultural power of science. This lie received its most compelling articulation just as America was about to embark on an extended period of extraordinary scientific, technological, and economic growth. It goes like this:

Scientific progress on a broad front results from the free play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown.

 

….The fruits of curiosity-driven scientific exploration into the unknown have often been magnificent. The recent discovery of gravitational waves — an experimental confirmation of Einstein’s theoretical work from a century earlier — provided a high-publicity culmination of billions of dollars of public spending and decades of research by large teams of scientists. Multi-billion dollar investments in space exploration have yielded similarly startling knowledge about our solar system, such as the recent evidence of flowing water on Mars. And, speaking of startling, anthropologists and geneticists have used genome-sequencing technologies to offer evidence that early humans interbred with two other hominin species, Neanderthals and Denisovans. Such discoveries heighten our sense of wonder about the universe and about ourselves.

And somehow, it would seem, even as scientific curiosity stokes ever-deepening insight about the fundamental workings of our world, science managed simultaneously to deliver a cornucopia of miracles on the practical side of the equation, just as Bush predicted: digital computers, jet aircraft, cell phones, the Internet, lasers, satellites, GPS, digital imagery, nuclear and solar power. When Bush wrote his report, nothing made by humans was orbiting the earth; software didn’t exist; smallpox still did.

So one might be forgiven for believing that this amazing effusion of technological change truly was the product of “the free play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown.” But one would be mostly wrong.

Science has been important for technological development, of course. Scientists have discovered and probed phenomena that turned out to have enormously broad technological applications. But the miracles of modernity in the above list came not from “the free play of free intellects,” but from the leashing of scientific creativity to the technological needs of the U.S. Department of Defense (DOD).

The story of how DOD mobilized science to help create our world exposes the lie for what it is and provides three difficult lessons that have to be learned if science is to evade the calamity it now faces.

First, scientific knowledge advances most rapidly, and is of most value to society, not when its course is determined by the “free play of free intellects” but when it is steered to solve problems — especially those related to technological innovation.

Second, when science is not steered to solve such problems, it tends to go off half-cocked in ways that can be highly detrimental to science itself.

Third — and this is the hardest and scariest lesson — science will be made more reliable and more valuable for society today not by being protected from societal influences but instead by being brought, carefully and appropriately, into a direct, open, and intimate relationship with those influences….(More)”