How cities can leverage citizen data while protecting privacy

Curated on Posted on by Stefaan Verhulst

MIT News: “India is on a path with dual — and potentially conflicting — goals related to the use of citizen data.

To improve the efficiency their municipal services, many Indian cities have started enabling government-service requests, which involves collecting and sharing citizen data with government officials and, potentially, the public. But there’s also a national push to protect citizen privacy, potentially restricting data usage. Cities are now beginning to question how much citizen data, if any, they can use to track government operations.

In a new study, MIT researchers find that there is, in fact, a way for Indian cities to preserve citizen privacy while using their data to improve efficiency.

The researchers obtained and analyzed data from more than 380,000 government service requests by citizens across 112 cities in one Indian state for an entire year. They used the dataset to measure each city government’s efficiency based on how quickly they completed each service request. Based on field research in three of these cities, they also identified the citizen data that’s necessary, useful (but not critical), or unnecessary for improving efficiency when delivering the requested service.

In doing so, they identified “model” cities that performed very well in both categories, meaning they maximized privacy and efficiency. Cities worldwide could use similar methodologies to evaluate their own government services, the researchers say. …(More)”.

Community Data Dialogues

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Sunlight foundation: “Community Data Dialogues are in-person events designed to share open data with community members in the most digestible way possible to start a conversation about a specific issue. The main goal of the event is to give residents who may not have technical expertise but have local experience a chance to participate in data-informed decision-making. Doing this work in-person can open doors and let facilitators ask a broader range of questions. To achieve this, the event must be designed to be inclusive of people without a background in data analysis and/or using statistics to understand local issues. Carrying out this event will let decision-makers in government use open data to talk with residents who can add to data’s value with their stories of lived experience relevant to local issues.

These events can take several forms, and groups both in and outside of government have designed creative and innovative events tailored to engage community members who are actively interested in helping solve local issues but are unfamiliar with using open data. This guide will help clarify how exactly to make Community Data Dialogues non-technical, interactive events that are inclusive to all participants….

A number of groups both in and outside of government have facilitated accessible open data events to great success. Here are just a few examples from the field of what data-focused events tailored for a nontechnical audience can look like:

Data Days Cleveland

Data Days Cleveland is an annual one-day event designed to make data accessible to all. Programs are designed with inclusivity and learning in mind, making it a more welcoming space for people new to data work. Data experts and practitioners direct novices on the fundamentals of using data: making maps, reading spreadsheets, creating data visualizations, etc….

The Urban Institute’s Data Walks

The Urban Institute’s Data Walks are an innovative example of presenting data in an interactive and accessible way to communities. Data Walks are events gathering community residents, policymakers, and others to jointly review and analyze data presentations on specific programs or issues and collaborate to offer feedback based on their individual experiences and expertise. This feedback can be used to improve current projects and inform future policies….(More)“.

GovChain

Curated on Posted on by Stefaan Verhulst

Introduction to Report by Tom Rodden: “This report addresses the most discussed digital technologies of the last few years. There has been considerable debate about the potential benefits and threats that arise from the use of Distributed Ledger Technologies. What is clear from these debates is that blockchain is an important technology that has the potential to transform a range of sectors. The importance of Distributed Ledger Technology was identified and discussed in a 2016 report produced by Sir Mark Walport, the UK Government’s Chief Scientific Adviser at the time.

The report provided recommendations for the use of blockchain to meet national needs, and to ensure the UK’s competitiveness in the global arena. The report outlined the need for a broad response that spanned the public and private sector, whilst also recognising the need for leadership in the development and deployment of blockchain technologies.

This report provides an update and reflection on the use of blockchain technologies by Governments and Public Sector bodies around the world. Much has happened since 2016 and this report provides a reminder of the importance of Distributed Ledger Technologies for the public sector, and the various orientations of blockchains adopted across the globe. The team have mapped the various regulatory and policy responses to blockchain, and cryptocurrencies more broadly. This mapping not only reveals a varying degree of friendliness towards blockchain, it also highlights the challenges involved in implementing Distributed Ledger Technology systems in the public sector.

Distributed Ledger Technologies are an important technology for the public sector, albeit there exists a number of policy implications. If we are to show leadership in the use of blockchain and its application it is imperative that we are aware of both its benefits and limitations; and the issues that need to be addressed to ensure we gain value from the use of Distributed Ledger Technologies. This report captures the public sector experiences of blockchain technologies across the globe, and also documents the issues raised and the various responses. This is a hugely informative and useful document for those who seek to make use of blockchains in the public sector….(More)”.

Counting on the World to Act

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Home report cover

Report by Trends: “Eradicating poverty and hunger, ensuring quality education, instituting affordable and clean energy, and more – the Sustainable Development Goals (SDGs) lay out a broad, ambitious vision for our world. But there is one common denominator that cuts across this agenda: data. Without timely, relevant, and disaggregated data, policymakers and their development partners will be unprepared to turn their promises into reality for communities worldwide. With only eleven years left to meet the goals, it is imperative that we focus on building robust, inclusive, and relevant national data systems to support the curation and promotion of better data for sustainable development. In Counting on the World to Act, TReNDS details an action plan for governments and their development partners that will enable them to help deliver the SDGs globally by 2030. Our recommendations specifically aim to empower government actors – whether they be national statisticians, chief data scientists, chief data officers, ministers of planning, or others concerned with evidence in support of sustainable development – to advocate for, build, and lead a new data ecosystem….(More)”.

The Algorithmic Divide and Equality in the Age of Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Paper by Peter Yu: “In the age of artificial intelligence, highly sophisticated algorithms have been deployed to detect patterns, optimize solutions, facilitate self-learning, and foster improvements in technological products and services. Notwithstanding these tremendous benefits, algorithms and intelligent machines do not provide equal benefits to all. Just as the digital divide has separated those with access to the Internet, information technology, and digital content from those without, an emerging and ever-widening algorithmic divide now threatens to take away the many political, social, economic, cultural, educational, and career opportunities provided by machine learning and artificial intelligence.

Although policymakers, commentators, and the mass media have paid growing attention to algorithmic bias and the shortcomings of machine learning and artificial intelligence, the algorithmic divide has yet to attract much policy and scholarly attention. To fill this lacuna, this article draws on the digital divide literature to systematically analyze this new inequitable gap between the technology haves and have-nots. Utilizing the analytical framework that the Author developed in the early 2000s, the article discusses the five attributes of the algorithmic divide: awareness, access, affordability, availability, and adaptability.

This article then turns to three major problems precipitated by an emerging and fast-expanding algorithmic divide: (1) algorithmic deprivation; (2) algorithmic discrimination; and (3) algorithmic distortion. While the first two problems affect primarily those on the unfortunate side of the algorithmic divide, the latter impacts individuals on both sides of the divide. This article concludes by proposing seven nonexhaustive clusters of remedial actions to help bridge this emerging and ever-widening algorithmic divide. Combining law, communications policy, ethical principles, institutional mechanisms, and business practices, the article fashions a holistic response to help foster equality in the age of artificial intelligence….(More)”.

The Extended Corporate Mind: When Corporations Use AI to Break the Law

Curated on Posted on by Stefaan Verhulst

Paper by Mihailis Diamantis: “Algorithms may soon replace employees as the leading cause of corporate harm. For centuries, the law has defined corporate misconduct — anything from civil discrimination to criminal insider trading — in terms of employee misconduct. Today, however, breakthroughs in artificial intelligence and big data allow automated systems to make many corporate decisions, e.g., who gets a loan or what stocks to buy. These technologies introduce valuable efficiencies, but they do not remove (or even always reduce) the incidence of corporate harm. Unless the law adapts, corporations will become increasingly immune to civil and criminal liability as they transfer responsibility from employees to algorithms.

This Article is the first to tackle the full extent of the growing doctrinal gap left by algorithmic corporate misconduct. To hold corporations accountable, the law must sometimes treat them as if they “know” information stored on their servers and “intend” decisions reached by their automated systems. Cognitive science and the philosophy of mind offer a path forward. The “extended mind thesis” complicates traditional views about the physical boundaries of the mind. The thesis states that the mind encompasses any system that sufficiently assists thought, e.g. by facilitating recall or enhancing decision-making. For natural people, the thesis implies that minds can extend beyond the brain to include external cognitive aids, like rolodexes and calculators. This Article adapts the thesis to corporate law. It motivates and proposes a doctrinal framework for extending the corporate mind to the algorithms that are increasingly integral to corporate thought. The law needs such an innovation if it is to hold future corporations to account for their most serious harms….(More)”.

Next generation disaster data infrastructure

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Report by the IRDR Working Group on DATA and the CODATA Task Group on Linked Open Data for Global Disaster Risk Research: “Based on the targets of the Sendai Framework, this white paper proposes the next generation of disaster data infrastructure, which includes both novel and the most essential information systems and services that a country or a region can depend on to successfully gather, process and display disaster data to reduce the impact of natural hazards.

Fundamental requirements of disaster data infrastructure include (1) effective multi-source big disaster data collection (2) efficient big disaster data fusion, exchange and query (3) strict big disaster data quality control and standard construction (4) real time big data analysis and decision making and (5) user-friendly big data visualization.

The rest of the paper is organized as follows: first, several future scenarios of disaster management are developed based on existing disaster management systems and communication technology. Second, fundamental requirements of next generation disaster data infrastructure inspired by the proposed scenarios are discussed. Following that, research questions and issues are highlighted. Finally, policy recommendations and conclusions are provided at the end of the paper….(More)”.

Insurance Discrimination and Fairness in Machine Learning: An Ethical Analysis

Curated on Posted on by Stefaan Verhulst

Paper by Michele Loi and Markus Christen: “Here we provide an ethical analysis of discrimination in private insurance to guide the application of non-discriminatory algorithms for risk prediction in the insurance context. This addresses the need for ethical guidance of data-science experts and business managers. The reference to private insurance as a business practice is essential in our approach, because the consequences of discrimination and predictive inaccuracy in underwriting are different from those of using predictive algorithms in other sectors (e.g. medical diagnosis, sentencing). Moreover, the computer science literature has demonstrated the existence of a trade-off in the extent to which one can pursue non- discrimination versus predictive accuracy. Again the moral assessment of this trade-off is related to the context of application…(More)”

How does a computer ‘see’ gender?

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Pew Research Center: “Machine vision tools like facial recognition are increasingly being used for law enforcement, advertising, and other purposes. Pew Research Center itself recently used a machine vision system to measure the prevalence of men and women in online image search results. This kind of system develops its own rules for identifying men and women after seeing thousands of example images, but these rules can be hard for to humans to discern. To better understand how this works, we showed images of the Center’s staff members to a trained machine vision system similar to the one we used to classify image searches. We then systematically obscured sections of each image to see which parts of the face caused the system to change its decision about the gender of the person pictured. Some of the results seemed intuitive, others baffling. In this interactive challenge, see if you can guess what makes the system change its decision.

Here’s how it works:…(More)”.

Traffic Data Is Good for More than Just Streets, Sidewalks

Curated on Posted on by Stefaan Verhulst

Skip Descant at Government Technology: “The availability of highly detailed daily traffic data is clearly an invaluable resource for traffic planners, but it can also help officials overseeing natural lands or public works understand how to better manage those facilities.

The Natural Communities Coalition, a conservation nonprofit in southern California, began working with the traffic analysis firm StreetLight Data in early 2018 to study the impacts from the thousands of annual visitors to 22 parks and natural lands. StreetLight Data’s use of de-identified cellphone data held promise for the project, which will continue into early 2020.

“You start to see these increases,” Milan Mitrovich, science director for the Natural Communities Coalition, said of the uptick in visitor activity the data showed. “So being able to have this information, and share it with our executive committee… these folks, they’re seeing it for the first time.”…

Officials with the Natural Communities Coalition were able to use the StreetLight data to gain insights into patterns of use not only per day, but at different times of the day. The data also told researchers where visitors were traveling from, a detail park officials found “jaw-dropping.”

“What we were able to see is, these resources, these natural areas, cast an incredible net across southern California,” said Mitrovich, noting visitors come from not only Orange County, but Los Angeles, San Bernardino and San Diego counties as well, a region of more than 20 million residents.

The data also allows officials to predict traffic levels during certain parts of the week, times of day or even holidays….(More)”.