Paper by Richard Rose: “Open data makes transparent whether public officials are conducting their activities in conformity with standards that can be bureaucratic, political or moral. Actions that violate these standards are colloquially lumped together under the heterogeneous heading of corruption. However, the payment of a large bribe for a multi-million contract differs in kind from a party saying one thing to win votes and doing another once in office or an individual public figure promoting high standards of personal morality while conducting himself in private very differently. This paper conceptually distinguishes different forms of corruption with concrete examples. It also shows how sanctions for different forms of corruption require different sanctions: punishment by the courts, by political leaders or the electorate, or by public morality and a sense of individual shame. Such sanctions are most effective when there is normative agreement that standards have been violated. There are partisan as well as normative disagreements about whether standards have been violated. The paper concludes by pointing out that differences in violating standards require different policy responses….(More)”
AI and the Law: Setting the Stage
Urs Gasser: “Lawmakers and regulators need to look at AI not as a homogenous technology, but a set of techniques and methods that will be deployed in specific and increasingly diversified applications. There is currently no generally agreed-upon definition of AI. What is important to understand from a technical perspective is that AI is not a single, homogenous technology, but a rich set of subdisciplines, methods, and tools that bring together areas such as speech recognition, computer vision, machine translation, reasoning, attention and memory, robotics and control, etc. ….
Given the breadth and scope of application, AI-based technologies are expected to trigger a myriad of legal and regulatory issues not only at the intersections of data and algorithms, but also of infrastructures and humans. …
When considering (or anticipating) possible responses by the law vis-à-vis AI innovation, it might be helpful to differentiate between application-specific and cross-cutting legal and regulatory issues. …
Information asymmetries and high degrees of uncertainty pose particular difficulty to the design of appropriate legal and regulatory responses to AI innovations — and require learning systems. AI-based applications — which are typically perceived as “black boxes” — affect a significant number of people, yet there are nonetheless relatively few people who develop and understand AI-based technologies. ….Approaches such as regulation 2.0, which relies on dynamic, real-time, and data-driven accountability models, might provide interesting starting points.
The responses to a variety of legal and regulatory issues across different areas of distributed applications will likely result in a complex set of sector-specific norms, which are likely to vary across jurisdictions….
Law and regulation may constrain behavior yet also act as enablers and levelers — and are powerful tools as we aim for the development of AI for social good. …
Law is one important approach to the governance of AI-based technologies. But lawmakers and regulators have to consider the full potential of available instruments in the governance toolbox. ….
In a world of advanced AI technologies and new governance approaches towards them, the law, the rule of law, and human rights remain critical bodies of norms. …
As AI applies to the legal system itself, however, the rule of law might have to be re-imagined and the law re-coded in the longer run….(More).
Shaping space for civic life: Can better design help engage citizens?
Patrick Sisson at Curbed: “…The Assembly Civic Engagement Survey, a new report released yesterday by the Center for Active Design, seeks to understand the connections between the design of public spaces and buildings on public life, and eventually create a toolbox for planners and politicians to make decisions that can help improve civic pride. There’s perhaps an obvious connection between what one might consider a better-designed neighborhood and public perception of government and community, but how to design that neighborhood to directly improve public engagement—especially during an era of low voter engagement and partisan divide—is an important, and unanswered, question….
One of the most striking findings was around park signage. Respondents were shown a series of three signs, ranging from a traditional display of park rules and prohibitions to a more proactive, engaging pictograph that tells parkgoers it’s okay to give high-fives. The survey found the simple switch to more eye-catching, positive, and entertaining signage improved neighborhood pride by 11 percent and boosted the feeling that “the city cares for people in this park” by 9 percent. Similar improvements were found in surveys looking at signage on community centers.
According to Frank, the biggest revelation from the research is how a minimum of effort can make a large impact. On one hand, she says, it doesn’t take a genius to realize that transforming a formerly graffiti-covered vacant lot into a community garden can impact community trust and cohesion.
What sticks out from the study’s findings is how little is really necessary to shift attitudes and improve people’s trust in their neighborhoods and attitudes toward city government and police. Litter turned out to be a huge issue: High levels of trash eroded community pride by 10 percent, trust in police by 5 percent, and trust in local government by 4 percent. When presented with a series of seven things they could improve about their city, including crime, traffic, and noise, 23 percent of respondents chose litter.
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In short, disorder erodes civic trust. The small things matter, especially when cities are formulating budgets and streetscaping plans and looking at the most effective ways of investing in community improvements….
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Giving cities direction as well as data
Beyond connecting the dots, Frank wants to give planners rationale for their actions. Telling designers that placing planters in the middle of a street can beautify a neighborhood is one thing; showing that this kind of beautification increases walkability, brings more shoppers to a commercial strip, and ultimately leads to higher sales and tax revenue spurs action and innovation.
Frank gives the example of redesigning the streetscape in front of a police station. The idea of placing planters and benches may seem like a poor use of limited funds, until data and research reveals it’s a cost-effective way to encourage interactions between cops and the community and helps change the image of the department….(More)”
Detecting riots with Twitter
Cardiff University News: “An analysis of data taken from the London riots in 2011 showed that computer systems could automatically scan through Twitter and detect serious incidents, such as shops being broken in to and cars being set alight, before they were reported to the Metropolitan Police Service.
The computer system could also discern information about where the riots were rumoured to take place and where groups of youths were gathering. The new research, published in the peer-review journal ACM Transactions on Internet Technology, showed that on average the computer systems could pick up on disruptive events several minutes before officials and over an hour in some cases.
“Antagonistic narratives and cyber hate”
The researchers believe that their work could enable police officers to better manage and prepare for both large and small scale disruptive events.
Co-author of the study Dr Pete Burnap, from Cardiff University’s School of Computer Science and Informatics, said: “We have previously used machine-learning and natural language processing on Twitter data to better understand online deviance, such as the spread of antagonistic narratives and cyber hate…”
“We will never replace traditional policing resource on the ground but we have demonstrated that this research could augment existing intelligence gathering and draw on new technologies to support more established policing methods.”
Scientists are continually looking to the swathes of data produced from Twitter, Facebook and YouTube to help them to detect events in real-time.
Estimates put social media membership at approximately 2.5 billion non-unique users, and the data produced by these users have been used to predict elections, movie revenues and even the epicentre of earthquakes.
In their study the research team analysed 1.6m tweets relating to the 2011 riots in England, which began as an isolated incident in Tottenham on August 6 but quickly spread across London and to other cities in England, giving rise to looting, destruction of property and levels of violence not seen in England for more than 30 years.
Machine-learning algorithms
The researchers used a series of machine-learning algorithms to analyse each of the tweets from the dataset, taking into account a number of key features such as the time they were posted, the location where they were posted and the content of the tweet itself.
Results showed that the machine-learning algorithms were quicker than police sources in all but two of the disruptive events reported…(More)”.
Index: Collective Intelligence
By Hannah Pierce and Audrie Pirkl
The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on collective intelligence and was originally published in 2017.
The Collective Intelligence Universe
- Amount of money that Reykjavik’s Better Neighbourhoods program has provided each year to crowdsourced citizen projects since 2012: € 2 million (Citizens Foundation)
- Number of U.S. government challenges that people are currently participating in to submit their community solutions: 778 (Challenge.gov).
- Percent of U.S. arts organizations used social media to crowdsource ideas in 2013, from programming decisions to seminar scheduling details: 52% (Pew Research)
- Number of Wikipedia members who have contributed to a page in the last 30 days: over 120,000 (Wikipedia Page Statistics)
- Number of languages that the multinational crowdsourced Letters for Black Lives has been translated into: 23 (Letters for Black Lives)
- Number of comments in a Reddit thread that established a more comprehensive timeline of the theater shooting in Aurora than the media: 1272 (Reddit)
- Number of physicians that are members of SERMO, a platform to crowdsource medical research: 800,000 (SERMO)
- Number of citizen scientist projects registered on SciStarter: over 1,500 (Collective Intelligence 2017 Plenary Talk: Darlene Cavalier)
- Entrants to NASA’s 2009 TopCoder Challenge: over 1,800 (NASA)
Infrastructure
- Number of submissions for Block Holm (a digital platform that allows citizens to build “Minecraft” ideas on vacant city lots) within the first six months: over 10,000 (OpenLearn)
- Number of people engaged to The Participatory Budgeting Project in the U.S.: over 300,000. (Participatory Budgeting Project)
- Amount of money allocated to community projects through this initiative: $238,000,000
Health
- Percentage of Internet-using adults with chronic health conditions that have gone online within the US to connect with others suffering from similar conditions: 23% (Pew Research)
- Number of posts to Patient Opinion, a UK based platform for patients to provide anonymous feedback to healthcare providers: over 120,000 (Nesta)
- Percent of NHS health trusts utilizing the posts to improve services in 2015: 90%
- Stories posted per month: nearly 1,000 (The Guardian)
- Number of tumors reported to the English National Cancer Registration each year: over 300,000 (Gov.UK)
- Number of users of an open source artificial pancreas system: 310 (Collective Intelligence 2017 Plenary Talk: Dana Lewis)
Government
- Number of submissions from 40 countries to the 2017 Open (Government) Contracting Innovation Challenge: 88 (The Open Data Institute)
- Public-service complaints received each day via Indonesian digital platform Lapor!: over 500 (McKinsey & Company)
- Number of registered users of Unicef Uganda’s weekly, SMS poll U-Report: 356,468 (U-Report)
- Number of reports regarding government corruption in India submitted to IPaidaBribe since 2011: over 140,000 (IPaidaBribe)
Business
- Reviews posted since Yelp’s creation in 2009: 121 million reviews (Statista)
- Percent of Americans in 2016 who trust online customer reviews as much as personal recommendations: 84% (BrightLocal)
- Number of companies and their subsidiaries mapped through the OpenCorporates platform: 60 million (Omidyar Network)
Crisis Response
- Number of diverse stakeholders digitally connected to solve climate change problems through the Climate CoLab: over 75,000 (MIT ILP Institute Insider)
- Number of project submissions to USAID’s 2014 Fighting Ebola Grand Challenge: over 1,500 (Fighting Ebola: A Grand Challenge for Development)
- Reports submitted to open source flood mapping platform Peta Jakarta in 2016: 5,000 (The Open Data Institute)
Public Safety
- Number of sexual harassment reports submitted to from 50 cities in India and Nepal to SafeCity, a crowdsourcing site and mobile app: over 4,000 (SafeCity)
- Number of people that used Facebook’s Safety Check, a feature that is being used in a new disaster mapping project, in the first 24 hours after the terror attacks in Paris: 4.1 million (Facebook)
Big Data: A Twenty-First Century Arms Race
Report by Atlantic Council and Thomson Reuters: “We are living in a world awash in data. Accelerated interconnectivity, driven by the proliferation of internet-connected devices, has led to an explosion of data—big data. A race is now underway to develop new technologies and implement innovative methods that can handle the volume, variety, velocity, and veracity of big data and apply it smartly to provide decisive advantage and help solve major challenges facing companies and governments
For policy makers in government, big data and associated technologies like machine-learning and artificial Intelligence, have the potential to drastically improve their decision-making capabilities. How governments use big data may be a key factor in improved economic performance and national security. This publication looks at how big data can maximize the efficiency and effectiveness of government and business, while minimizing modern risks. Five authors explore big data across three cross-cutting issues: security, finance, and law.
Chapter 1, “The Conflict Between Protecting Privacy and Securing Nations,” Els de Busser
Chapter 2, “Big Data: Exposing the Risks from Within,” Erica Briscoe
Chapter 3, “Big Data: The Latest Tool in Fighting Crime,” Benjamin Dean, Fellow
Chapter 4, “Big Data: Tackling Illicit Financial Flows,” Tatiana Tropina
Chapter 5, “Big Data: Mitigating Financial Crime Risk,” Miren Aparicio….Read the Publication (PDF)“
What Bhutanese hazelnuts tell us about using data for good
Bruno Sánchez-Andrade Nuño at WEForum: “How are we going to close the $2.5 trillion/year finance gap to achieve the Sustainable Development Goals (SDGs)? Whose money? What business model? How to scale it that much? If you read the recent development economics scholar literature, or Jim Kim’s new financing approach of the World Bank, you might hear the benefits of “blended finance” or “triple bottom lines.” I want to tell you instead about a real case that makes a dent. I want to tell you about Sonam.
Sonam is a 60-year old farmer in rural Bhutan. His children left for the capital, Thimphu, like many are doing nowadays. Four years ago, he decided to plant 2 acres of hazelnuts on an unused rocky piece of his land. Hazelnut saplings, training, and regular supervision all come from “Mountain Hazelnuts”, Bhutan’s only 100% foreign invested company. They fund the costs of the trees and helps him manage his orchard. In return, when the nuts come, he will sell his harvest to them above the guaranteed floor price, which will double his income; in a time when he will be too old to work in his rice field.
You could find similar impact stories for the roughly 10,000 farmers participating in this operation across the country, where the farmers are carefully selected to ensure productivity, maximize social and environmental benefits, such as vulnerable households, or reducing land erosion.
But Sonam also gets a visit from Kinzang every month. This is Kinzang’s first job. Otherwise, he would have moved to the city in hopes of finding a low paying job, but more likely joining the many unemployed youth from the countryside. Kinzang carefully records data on his smart-phone, talks to Sonam and digitally transmits the data back to the company HQ. There, if a problem is recorded with irrigation, pests, or there is any data anomaly, a team of experts (locally trained agronomists) will visit his orchard to figure out a solution.
The whole system of support, monitoring, and optimization live on a carefully crafted data platform that feeds information to and from the farmers, the monitors, the agronomist experts, and local government authorities. It ensures that all 10 million trees are healthy and productive, minimizes extra costs, tests and tracks effectiveness of new treatments….
This is also a story which demonstrates how “Data is the new oil” is not the right approach. If Data is the new oil, you extract value from the data, without much regard to feeding back value to the source of the data. However, in this system, “Data is the new soil.” Data creates a higher ground in which value flows back and forth. It lifts the source of the data -the farmers- into new income generation, it enables optimized operations; and it also helps the whole country: Much of the data (such as road quality used by the monitors) is made open for the benefit of the Bhutanese people, without contradiction or friction with the business model….(More)”.
A Road-Map To Transform The Secure And Accessible Use Of Data For High Impact Program Management, Policy Development, And Scholarship
Preface and Roadmap by Andrew Reamer and Julia Lane: “Throughout the United States, there is broadly emerging support to significantly enhance the nation’s capacity for evidence-based policymaking. This support is shared across the public and private sectors and all levels of geography. In recent years, efforts to enable evidence-based analysis have been authorized by the U.S. Congress, and funded by state and local governments, philanthropic foundations.
The potential exists for substantial change. There has been dramatic growth in technological capabilities to organize, link, and analyze massive volumes of data from multiple, disparate sources. A major resource is administrative data, which offer both advantages and challenges in comparison to data gathered through the surveys that have been the basis for much policymaking to date. To date, however, capability-building efforts have been largely “artisanal” in nature. As a result, the ecosystem of evidence-based policymaking capacity-building efforts is thin and weakly connected.
Each attempt to add a node to the system faces multiple barriers that require substantial time, effort, and luck to address. Those barriers are systemic. Too much attention is paid to the interests of researchers, rather than in the engagement of data producers. Individual projects serve focused needs and operate at a relative distance from one another Researchers, policymakers and funding agencies thus need exists to move from these artisanal efforts to new, generalized solutions that will catalyze the creation of a robust, large-scale data infrastructure for evidence-based policymaking.
This infrastructure will have be a “complex, adaptive ecosystem” that expands, regenerates, and replicates as needed while allowing customization and local control. To create a path for achieving this goal, the U.S. Partnership on Mobility from Poverty commissioned 12 papers and then hosted a day-long gathering (January 23, 2017) of over 60 experts to discuss findings and implications for action. Funded by the Gates Foundation, the papers and workshop panels were organized around three topics: privacy and confidentiality, data providers, and comprehensive strategies.
This issue of the Annals showcases those 12 papers which jointly propose solutions for catalyzing the development of a data infrastructure for evidence-based policymaking.
This preface:
- places current evidence-based policymaking efforts in historical context
- briefly describes the nature of multiple current efforts,
- provides a conceptual framework for catalyzing the growth of any large institutional ecosystem,
- identifies the major dimensions of the data infrastructure ecosystem,
- describes key barriers to the expansion of that ecosystem, and
- suggests a roadmap for catalyzing that expansion….(More)
(All 12 papers can be accessed here).
Rawification and the careful generation of open government data
Jérôme Denis and Samuel Goëta in Social Studies of Science: “Drawing on a two-year ethnographic study within several French administrations involved in open data programs, this article aims to investigate the conditions of the release of government data – the rawness of which open data policies require. This article describes two sets of phenomena. First, far from being taken for granted, open data emerge in administrations through a progressive process that entails uncertain collective inquiries and extraction work. Second, the opening process draws on a series of transformations, as data are modified to satisfy an important criterion of open data policies: the need for both human and technical intelligibility. There are organizational consequences of these two points, which can notably lead to the visibilization or the invisibilization of data labour. Finally, the article invites us to reconsider the apparent contradiction between the process of data release and the existence of raw data. Echoing the vocabulary of one of the interviewees, the multiple operations can be seen as a ‘rawification’ process by which open government data are carefully generated. Such a notion notably helps to build a relational model of what counts as data and what counts as work….(More)”.
Is Crowdsourcing Patient-Reported Outcomes the Future of Evidence-Based Medicine?
Evidence is lacking for patient-reported effectiveness of treatments for most medical conditions and specifically for lower back pain. In this paper, we examined a consumer-based social network that collects patients’ treatment ratings as a potential source of evidence. Acknowledging the potential biases of this data set, we used propensity score matching and generalized linear regression to account for confounding variables. To evaluate validity, we compared results obtained by analyzing the patient reported data to results of evidence-based studies. Overall, there was agreement on the relationship between back pain and being obese. In addition, there was agreement about which treatments were effective or had no benefit. The patients’ ratings also point to new evidence that postural modification treatment is effective and that surgery is harmful to a large proportion of patients….(More)”.