Artificial Intelligence for Citizen Services and Government

Curated on Posted on by Stefaan Verhulst

Paper by Hila Mehr: “From online services like Netflix and Facebook, to chatbots on our phones and in our homes like Siri and Alexa, we are beginning to interact with artificial intelligence (AI) on a near daily basis. AI is the programming or training of a computer to do tasks typically reserved for human intelligence, whether it is recommending which movie to watch next or answering technical questions. Soon, AI will permeate the ways we interact with our government, too. From small cities in the US to countries like Japan, government agencies are looking to AI to improve citizen services.

While the potential future use cases of AI in government remain bounded by government resources and the limits of both human creativity and trust in government, the most obvious and immediately beneficial opportunities are those where AI can reduce administrative burdens, help resolve resource allocation problems, and take on significantly complex tasks. Many AI case studies in citizen services today fall into five categories: answering questions, filling out and searching documents, routing requests, translation, and drafting documents. These applications could make government work more efficient while freeing up time for employees to build better relationships with citizens. With citizen satisfaction with digital government offerings leaving much to be desired, AI may be one way to bridge the gap while improving citizen engagement and service delivery.

Despite the clear opportunities, AI will not solve systemic problems in government, and could potentially exacerbate issues around service delivery, privacy, and ethics if not implemented thoughtfully and strategically. Agencies interested in implementing AI can learn from previous government transformation efforts, as well as private-sector implementation of AI. Government offices should consider these six strategies for applying AI to their work: make AI a part of a goals-based, citizen-centric program; get citizen input; build upon existing resources; be data-prepared and tread carefully with privacy; mitigate ethical risks and avoid AI decision making; and, augment employees, do not replace them.

This paper explores the various types of AI applications, and current and future uses of AI in government delivery of citizen services, with a focus on citizen inquiries and information. It also offers strategies for governments as they consider implementing AI….(More)”

Journal tries crowdsourcing peer reviews, sees excellent results

Curated on Posted on by Stefaan Verhulst

Chris Lee at ArsTechnica: “Peer review is supposed to act as a sanity check on science. A few learned scientists take a look at your work, and if it withstands their objective and entirely neutral scrutiny, a journal will happily publish your work. As those links indicate, however, there are some issues with peer review as it is currently practiced. Recently, Benjamin List, a researcher and journal editor in Germany, and his graduate assistant, Denis Höfler, have come up with a genius idea for improving matters: something called selected crowd-sourced peer review….

My central point: peer review is burdensome and sometimes barely functional. So how do we improve it? The main way is to experiment with different approaches to the reviewing process, which many journals have tried, albeit with limited success. Post-publication peer review, when scientists look over papers after they’ve been published, is also an option but depends on community engagement.

But if your paper is uninteresting, no one will comment on it after it is published. Pre-publication peer review is the only moment where we can be certain that someone will read the paper.

So, List (an editor for Synlett) and Höfler recruited 100 referees. For their trial, a forum-style commenting system was set up that allowed referees to comment anonymously on submitted papers but also on each other’s comments as well. To provide a comparison, the papers that went through this process also went through the traditional peer review process. The authors and editors compared comments and (subjectively) evaluated the pros and cons. The 100-person crowd of researchers was deemed the more effective of the two.

The editors found that it took a bit more time to read and collate all the comments into a reviewers’ report. But it was still faster, which the authors loved. Typically, it took the crowd just a few days to complete their review, which compares very nicely to the usual four to six weeks of the traditional route (I’ve had papers languish for six months in peer review). And, perhaps most important, the responses were more substantive and useful compared to the typical two-to-four-person review.

So far, List has not published the trial results formally. Despite that, Synlett is moving to the new system for all its papers.

Why does crowdsourcing work?

Here we get back to something more editorial. I’d suggest that there is a physical analog to traditional peer review, called noise. Noise is not just a constant background that must be overcome. Noise is also generated by the very process that creates a signal. The difference is how the amplitude of noise grows compared to the amplitude of signal. For very low-amplitude signals, all you measure is noise, while for very high-intensity signals, the noise is vanishingly small compared to the signal, even though it’s huge compared to the noise of the low-amplitude signal.

Our esteemed peers, I would argue, are somewhat random in their response, but weighted toward objectivity. Using this inappropriate physics model, a review conducted by four reviewers can be expected (on average) to contain two responses that are, basically, noise. By contrast, a review by 100 reviewers may only have 10 responses that are noise. Overall, a substantial improvement. So, adding the responses of a large number of peers together should produce a better picture of a scientific paper’s strengths and weaknesses.

Didn’t I just say that reviewers are overloaded? Doesn’t it seem that this will make the problem worse?

Well, no, as it turns out. When this approach was tested (with consent) on papers submitted to Synlett, it was discovered that review times went way down—from weeks to days. And authors reported getting more useful comments from their reviewers….(More)”.

Community Digital Storytelling for Collective Intelligence: towards a Storytelling Cycle of Trust

Curated on Posted on by Stefaan Verhulst

Sarah Copeland and Aldo de Moor in AI & SOCIETY: “Digital storytelling has become a popular method for curating community, organisational, and individual narratives. Since its beginnings over 20 years ago, projects have sprung up across the globe, where authentic voice is found in the narration of lived experiences. Contributing to a Collective Intelligence for the Common Good, the authors of this paper ask how shared stories can bring impetus to community groups to help identify what they seek to change, and how digital storytelling can be effectively implemented in community partnership projects to enable authentic voices to be carried to other stakeholders in society. The Community Digital Storytelling (CDST) method is introduced as a means for addressing community-of-place issues. There are five stages to this method: preparation, story telling, story digitisation, digital story sense-making, and digital story sharing. Additionally, a Storytelling Cycle of Trust framework is proposed. We identify four trust dimensions as being imperative foundations in implementing community digital media interventions for the common good: legitimacy, authenticity, synergy, and commons. This framework is concerned with increasing the impact that everyday stories can have on society; it is an engine driving prolonged storytelling. From this perspective, we consider the ability to scale up the scope and benefit of stories in civic contexts. To illustrate this framework, we use experiences from the CDST workshop in northern Britain and compare this with a social innovation project in the southern Netherlands….(More)”.

The Tech Revolution That’s Changing How We Measure Poverty

Curated on Posted on by Stefaan Verhulst

Alvin Etang Ndip at the Worldbank: “The world has an ambitious goal to end extreme poverty by 2030. But, without good poverty data, it is impossible to know whether we are making progress, or whether programs and policies are reaching those who are the most in need.

Countries, often in partnership with the World Bank Group and other agencies, measure poverty and wellbeing using household surveys that help give policymakers a sense of who the poor are, where they live, and what is holding back their progress. Once a paper-and-pencil exercise, technology is beginning to revolutionize the field of household data collection, and the World Bank is tapping into this potential to produce more and better poverty data….

“Technology can be harnessed in three different ways,” says Utz Pape, an economist with the World Bank. “It can help improve data quality of existing surveys, it can help to increase the frequency of data collection to complement traditional household surveys, and can also open up new avenues of data collection methods to improve our understanding of people’s behaviors.”

As technology is changing the field of data collection, researchers are continuing to find new ways to build on the power of mobile phones and tablets.

The World Bank’s Pulse of South Sudan initiative, for example, takes tablet-based data collection a step further. In addition to conducting the household survey, the enumerators also record a short, personalized testimonial with the people they are interviewing, revealing a first-person account of the situation on the ground. Such testimonials allow users to put a human face on data and statistics, giving a fuller picture of the country’s experience.

Real-time data through mobile phones

At the same time, more and more countries are generating real-time data through high-frequency surveys, capitalizing on the proliferation of mobile phones around the world. The World Bank’s Listening to Africa (L2A) initiative has piloted the use of mobile phones to regularly collect information on living conditions. The approach combines face-to-face surveys with follow-up mobile phone interviews to collect data that allows to monitor well-being.

The initiative hands out mobile phones and solar chargers to all respondents. To minimize the risk of people dropping out, the respondents are given credit top-ups to stay in the program. From monitoring health care facilities in Tanzania to collecting data on frequency of power outages in Togo, the initiative has been rolled out in six countries and has been used to collect data on a wide range of areas. …

Technology-driven data collection efforts haven’t been restricted to the Africa region alone. In fact, the approach was piloted early in Peru and Honduras with the Listening 2 LAC program. In Europe and Central Asia, the World Bank has rolled out the Listening to Tajikistan program, which was designed to monitor the impact of the Russian economic slowdown in 2014 and 2015. Initially a six-month pilot, the initiative has now been in operation for 29 months, and a partnership with UNICEF and JICA has ensured that data collection can continue for the next 12 months. Given the volume of data, the team is currently working to create a multidimensional fragility index, where one can monitor a set of well-being indicators – ranging from food security to quality jobs and public services – on a monthly basis…

There are other initiatives, such as in Mexico where the World Bank and its partners are using satellite imagery and survey data to estimate how many people live below the poverty line down to the municipal level, or guiding data collectors using satellite images to pick a representative sample for the Somali High Frequency Survey. However, despite the innovation, these initiatives are not intended to replace traditional household surveys, which still form the backbone of measuring poverty. When better integrated, they can prove to be a formidable set of tools for data collection to provide the best evidence possible to policymakers….(More)”

E-residency and blockchain

Curated on Posted on by Stefaan Verhulst

Clare Sullivan and Eric Burger in Computer Law & Security Review: “In December 2014, Estonia became the first nation to open its digital borders to enable anyone, anywhere in the world to apply to become an e-Resident. Estonian e-Residency is essentially a commercial initiative. The e-ID issued to Estonian e-Residents enables commercial activities with the public and private sectors. It does not provide citizenship in its traditional sense, and the e-ID provided to e-Residents is not a travel document. However, in many ways it is an international ‘passport’ to the virtual world. E-Residency is a profound change and the recent announcement that the Estonian government is now partnering with Bitnation to offer a public notary service to Estonian e-Residents based on blockchain technology is of significance. The application of blockchain to e-Residency has the potential to fundamentally change the way identity information is controlled and authenticated. This paper examines the legal, policy, and technical implications of this development….(More)”.

 

Algorithmic Transparency for the Smart City

Curated on Posted on by Stefaan Verhulst

Paper by Robert Brauneis and Ellen P. Goodman: “Emerging across many disciplines are questions about algorithmic ethics – about the values embedded in artificial intelligence and big data analytics that increasingly replace human decisionmaking. Many are concerned that an algorithmic society is too opaque to be accountable for its behavior. An individual can be denied parole or denied credit, fired or not hired for reasons she will never know and cannot be articulated. In the public sector, the opacity of algorithmic decisionmaking is particularly problematic both because governmental decisions may be especially weighty, and because democratically-elected governments bear special duties of accountability. Investigative journalists have recently exposed the dangerous impenetrability of algorithmic processes used in the criminal justice field – dangerous because the predictions they make can be both erroneous and unfair, with none the wiser.

We set out to test the limits of transparency around governmental deployment of big data analytics, focusing our investigation on local and state government use of predictive algorithms. It is here, in local government, that algorithmically-determined decisions can be most directly impactful. And it is here that stretched agencies are most likely to hand over the analytics to private vendors, which may make design and policy choices out of the sight of the client agencies, the public, or both. To see just how impenetrable the resulting “black box” algorithms are, we filed 42 open records requests in 23 states seeking essential information about six predictive algorithm programs. We selected the most widely-used and well-reviewed programs, including those developed by for-profit companies, nonprofits, and academic/private sector partnerships. The goal was to see if, using the open records process, we could discover what policy judgments these algorithms embody, and could evaluate their utility and fairness.

To do this work, we identified what meaningful “algorithmic transparency” entails. We found that in almost every case, it wasn’t provided. Over-broad assertions of trade secrecy were a problem. But contrary to conventional wisdom, they were not the biggest obstacle. It will not usually be necessary to release the code used to execute predictive models in order to dramatically increase transparency. We conclude that publicly-deployed algorithms will be sufficiently transparent only if (1) governments generate appropriate records about their objectives for algorithmic processes and subsequent implementation and validation; (2) government contractors reveal to the public agency sufficient information about how they developed the algorithm; and (3) public agencies and courts treat trade secrecy claims as the limited exception to public disclosure that the law requires. Although it would require a multi-stakeholder process to develop best practices for record generation and disclosure, we present what we believe are eight principal types of information that such records should ideally contain….(More)”.

How data can heal our oceans

Curated on Posted on by Stefaan Verhulst

Nishan Degnarain and Steve Adler at WEF: “We have collected more data on our oceans in the past two years than in the history of the planet.

There has been a proliferation of remote and near sensors above, on, and beneath the oceans. New low-cost micro satellites ring the earth and can record what happens below daily. Thousands of tidal buoys follow currents transmitting ocean temperature, salinity, acidity and current speed every minute. Undersea autonomous drones photograph and map the continental shelf and seabed, explore deep sea volcanic vents, and can help discover mineral and rare earth deposits.

The volume, diversity and frequency of data is increasing as the cost of sensors fall, new low-cost satellites are launched, and an emerging drone sector begins to offer new insights into our oceans. In addition, new processing capabilities are enhancing the value we receive from such data on the biological, physical and chemical properties of our oceans.

Yet it is not enough.

We need much more data at higher frequency, quality, and variety to understand our oceans to the degree we already understand the land. Less than 5% of the oceans are comprehensively monitored. We need more data collection capacity to unlock the sustainable development potential of the oceans and protect critical ecosystems.

More data from satellites will help identify illegal fishing activity, track plastic pollution, and detect whales and prevent vessel collisions. More data will help speed the placement of offshore wind and tide farms, improve vessel telematics, develop smart aquaculture, protect urban coastal zones, and enhance coastal tourism.

Unlocking the ocean data market

But we’re not there yet.

This new wave of data innovation is constrained by inadequate data supply, demand, and governance. The supply of existing ocean data is locked by paper records, old formats, proprietary archives, inadequate infrastructure, and scarce ocean data skills and capacity.

The market for ocean observation is driven by science and science isn’t adequately funded.

To unlock future commercial potential, new financing mechanisms are needed to create market demand that will stimulate greater investments in new ocean data collection, innovation and capacity.

Efforts such as the Financial Stability Board’s Taskforce on Climate-related Financial Disclosure have gone some way to raise awareness and create demand for such ocean-related climate risk data.

Much data that is produced is collected by nations, universities and research organizations, NGO’s, and the private sector, but only a small percentage is Open Data and widely available.

Data creates more value when it is widely utilized and well governed. Helping organize to improve data infrastructure, quality, integrity, and availability is a requirement for achieving new ocean data-driven business models and markets. New Ocean Data Governance models, standards, platforms, and skills are urgently needed to stimulate new market demand for innovation and sustainable development….(More)”.

Opportunities and risks in emerging technologies

Curated on Posted on by Stefaan Verhulst

White Paper Series at the WebFoundation: “To achieve our vision of digital equality, we need to understand how new technologies are shaping society; where they present opportunities to make people’s lives better, and indeed where they threaten to create harm. To this end, we have commissioned a series of white papers examining three key digital trends: artificial intelligence, algorithms and control of personal data. The papers focus on low and middle-income countries, which are all too often overlooked in debates around the impacts of emerging technologies.

The series addresses each of these three digital issues, looking at how they are impacting people’s lives and identifying steps that governments, companies and civil society organisations can take to limit the harms, and maximise benefits, for citizens.

Download the white papers

We will use these white papers to refine our thinking and set our work agenda on digital equality in the years ahead. We are sharing them openly with the hope they benefit others working towards our goals and to amplify the limited research currently available on digital issues in low and middle-income countries. We intend the papers to foster discussion about the steps we can take together to ensure emerging digital technologies are used in ways that benefit people’s lives, whether they are in Los Angeles or Lagos….(More)”.

Let the People Know the Facts: Can Government Information Removed from the Internet Be Reclaimed?

Curated on Posted on by Stefaan Verhulst

Paper by Susan Nevelow Mart: “…examines the legal bases of the public’s right to access government information, reviews the types of information that have recently been removed from the Internet, and analyzes the rationales given for the removals. She suggests that the concerted use of the Freedom of Information Act by public interest groups and their constituents is a possible method of returning the information to the Internet….(More)”.

How Can Blockchain Technology Help Government Drive Economic Activity?

Curated on Posted on by Stefaan Verhulst

Thomas Hardjono and Pete Teigen providing “A Blueprint Discussion on Identity“: Data breaches, identity theft, and trust erosion are all identity-related issues that citizens and government organizations face with increased frequency and magnitude. The rise of blockchain technology, and related distributed ledger technology, is generating significant interest in how a blockchain infrastructure can enable better identity management across a variety of industries.  Historically, governments have taken the primary role in issuing certain types of identities (e.g. social security numbers, driver licenses, and passports) based on strong authentication proofing of individuals using government-vetted documentation – a process often referred to as on-boarding. This identity proofing and on-boarding process presents a challenge to government because it is still heavily paper-based, making it cumbersome, time consuming and dependent on siloed, decades old, and inefficient systems.

Another aspect of the identity challenge is the risk of compromising an individual’s digital identifiers and government-issued credentials through identity theft. With so many vital services (e.g. banking, health services, transport, residency) dependent on trusted, government-vetted credentials, any compromise of that identity can result in a significant negative impact to the individual and be difficult to repair. Compounding the problem, many instances of identity theft go undetected and only discovered after damage is done.

Increasing the efficiency of the identity vetting process while also enhancing transparency would help mitigate those identity challenges.  Blockchain technology promises to do just that. Through the use of multiple computer systems (nodes) that are interconnected in a peer-to-peer (P2P) network, a shared common view of the information in the network ensures synchronicity of agreed data. A trusted ledger then exists in a distributed manner across the network that inherently is accountable to all network participants, thereby providing transparency and trustworthiness.

Using that trusted distributed ledger, identity-related data vetted by one Government entity and including that data’s location (producing a link in the chain) can be shared with other members of the network as needed — allowing members to instantaneously accept an identity without the need to duplicate the identity vetting process.  The more sophisticated blockchain systems possess this “record-link-fetch” feature that  is inherent in  the blockchain system’s building blocks.  Additional efficiency enhancing features allow downstream processes using that identity assertion as automated input to enable “smart contracts”, discussed below.

Thus, the combination of Government vetting of individual data, together with the embedded transparency and accountability capabilities of blockchain systems, allow relying parties (e.g. businesses, online merchants, individuals, etc.) to obtain higher degrees of assurance regarding the identity of other parties with whom they are conducting transactions…..

Identity and membership management solutions already exist and can be applied to private (permissioned) blockchain systems. Features within these solutions should be evaluated for their suitability for blockchain systems.  Specifically, these four steps can enable government to start in suing blockchain to address identity challenges:

  1. Evaluate existing identity and membership management solutions in order to identify features that apply to permissioned blockchain systems in the short term.
  2. Experiment with integrating these existing solutions with open source blockchain implementations.
  3. Create a roadmap (with a 2-3 year horizon) for identity and membership management for smart contracts within permissioned blockchains.
  4. Develop a long term plan (a 5 year horizon) for addressing identity and membership management for permissionless (public) blockchain systems. Here again, use open source blockchain implementations as the basis to understand the challenges in the identity space for permissionless blockchains….(More)”.