data – Page 16 – The Living Library

My City Forecast: Urban planning communication tool for citizen with national open data

Curated on June 23, 2018August 3, 2018 by Stefaan Verhulst

Paper by Y. Hasegawa, Y. Sekimoto, T. Seto, Y. Fukushima et al in Computers, Environment and Urban Systems: “In urban management, the importance of citizen participation is being emphasized more than ever before. This is especially true in countries where depopulation has become a major concern for urban managers and many local authorities are working on revising city master plans, often incorporating the concept of the “compact city.” In Japan, for example, the implementation of compact city plans means that each local government decides on how to designate residential areas and promotes citizens moving to these areas in order to improve budget effectiveness and the vitality of the city. However, implementing a compact city is possible in various ways. Given that there can be some designated withdrawal areas for budget savings, compact city policies can include disadvantages for citizens. At this turning point for urban structures, citizen–government mutual understanding and cooperation is necessary for every step of urban management, including planning.

Concurrently, along with the recent rapid growth of big data utilization and computer technologies, a new conception of cooperation between citizens and government has emerged. With emerging technologies based on civic knowledge, citizens have started to obtain the power to engage directly in urban management by obtaining information, thinking about their city’s problems, and taking action to help shape the future of their city themselves (Knight Foundation, 2013). This development is also supported by the open government data movement, which promotes the availability of government information online (Kingston, Carver, Evans, & Turton, 2000). CityDashboard is one well-known example of real-time visualization and distribution of urban information. CityDashboard, a web tool launched in 2012 by University College London, aggregates spatial data for cities around the UK and displays the data on a dashboard and a map. These new technologies are expected to enable both citizens and government to see their urban situation in an interface presenting an overhead view based on statistical information.

However, usage of statistics and governmental data is as yet limited in the actual process of urban planning…

To help improve this situation and increase citizen participation in urban management, we have developed a web-based urban planning communication tool using open government data for enhanced citizen–government cooperation. The main aim of the present research is to evaluate the effect of our system on users’ awareness of and attitude toward the urban situation. We have designed and developed an urban simulation system, My City Forecast (http://mycityforecast.net,) that enables citizens to understand how their environment and region are likely to change by urban management in the future (up to 2040)….(More)”.

Can Smart Cities Be Equitable?

Curated on June 23, 2018May 29, 2019 by Stefaan Verhulst

Homi Kharas and Jaana Remes at Project Syndicate: “Around the world, governments are making cities “smarter” by using data and digital technology to build more efficient and livable urban environments. This makes sense: with urban populations growing and infrastructure under strain, smart cities will be better positioned to manage rapid change.

But as digital systems become more pervasive, there is a danger that inequality will deepen unless local governments recognize that tech-driven solutions are as important to the poor as they are to the affluent.

While offline populations can benefit from applications running in the background of daily life – such as intelligent signals that help with traffic flows – they will not have access to the full range of smart-city programs. With smartphones serving as the primary interface in the modern city, closing the digital divide, and extending access to networks and devices, is a critical first step.

City planners can also deploy technology in ways that make cities more inclusive for the poor, the disabled, the elderly, and other vulnerable people. Examples are already abundant.

In New York City, the Mayor’s Public Engagement Unit uses interagency data platforms to coordinate door-to-door outreachto residents in need of assistance. In California’s Santa Clara County, predictive analytics help prioritize shelter space for the homeless. On the London Underground, an app called Wayfindr uses Bluetooth to help visually impaired travelers navigate the Tube’s twisting pathways and escalators.

And in Kolkata, India, a Dublin-based startup called Addressing the Unaddressedhas used GPS to provide postal addresses for more than 120,000 slum dwellers in 14 informal communities. The goal is to give residents a legal means of obtaining biometric identification cards, essential documentation needed to access government services and register to vote.

But while these innovations are certainly significant, they are only a fraction of what is possible.

Public health is one area where small investments in technology can bring big benefits to marginalized groups. In the developing world, preventable illnesses comprise a disproportionate share of the disease burden. When data are used to identify demographic groups with elevated risk profiles, low-cost mobile-messaging campaigns can transmit vital prevention information. So-called “m-health” interventions on issues like vaccinations, safe sex, and pre- and post-natal care have been shown to improve health outcomes and lower health-care costs.

Another area ripe for innovation is the development of technologies that directly aid the elderly….(More)”.

Balancing Act: Innovation vs. Privacy in the Age of Data Portability

Curated on June 22, 2018November 15, 2018 by admin

Thursday, July 12, 2018 @ 2 MetroTech Center, Brooklyn, NY 11201

RSVP here.

The ability of people to move or copy data about themselves from one service to another — data portability — has been hailed as a way of increasing competition and driving innovation. In many areas, such as through the Open Banking initiative in the United Kingdom, the practice of data portability is fully underway and propagating. The launch of GDPR in Europe has also elevated the issue among companies and individuals alike. But recent online security breaches and other experiences of personal data being transferred surreptitiously from private companies, (e.g., Cambridge Analytica’s appropriation of Facebook data), highlight how data portability can also undermine people’s privacy.

The GovLab at the NYU Tandon School of Engineering is pleased to present Jeni Tennison, CEO of the Open Data Institute, for its next Ideas Lunch, where she will discuss how data portability has been regulated in the UK and Europe, and what governments, businesses and people need to do to strike the balance between its risks and benefits.

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Jeni Tennison is the CEO of the Open Data Institute. She gained her PhD from the University of Nottingham then worked as an independent consultant, specialising in open data publishing and consumption, before joining the ODI in 2012. Jeni was awarded an OBE for services to technology and open data in the 2014 New Year Honours.

Before joining the ODI, Jeni was the technical architect and lead developer for legislation.gov.uk. She worked on the early linked data work on data.gov.uk, including helping to engineer new standards for publishing statistics as linked data. She continues her work within the UK’s public sector as a member of the Open Standards Board.

Jeni also works on international web standards. She was appointed to serve on the W3C’s Technical Architecture Group from 2011 to 2015 and in 2014 she started to co-chair the W3C’s CSV on the Web Working Group. She also sits on the Advisory Boards for Open Contracting Partnership and the Data Transparency Lab.

Twitter handle: @JeniT

We Need to Save Ignorance From AI

Curated on June 22, 2018August 3, 2018 by Stefaan Verhulst

Christina Leuker and Wouter van den Bos in Nautilus: “After the fall of the Berlin Wall, East German citizens were offered the chance to read the files kept on them by the Stasi, the much-feared Communist-era secret police service. To date, it is estimated that only 10 percent have taken the opportunity.

In 2007, James Watson, the co-discoverer of the structure of DNA, asked that he not be given any information about his APOE gene, one allele of which is a known risk factor for Alzheimer’s disease.

Most people tell pollsters that, given the choice, they would prefer not to know the date of their own death—or even the future dates of happy events.

Each of these is an example of willful ignorance. Socrates may have made the case that the unexamined life is not worth living, and Hobbes may have argued that curiosity is mankind’s primary passion, but many of our oldest stories actually describe the dangers of knowing too much. From Adam and Eve and the tree of knowledge to Prometheus stealing the secret of fire, they teach us that real-life decisions need to strike a delicate balance between choosing to know, and choosing not to.

But what if a technology came along that shifted this balance unpredictably, complicating how we make decisions about when to remain ignorant? That technology is here: It’s called artificial intelligence.

AI can find patterns and make inferences using relatively little data. Only a handful of Facebook likes are necessary to predict your personality, race, and gender, for example. Another computer algorithm claims it can distinguish between homosexual and heterosexual men with 81 percent accuracy, and homosexual and heterosexual women with 71 percent accuracy, based on their picture alone. An algorithm named COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) can predict criminal recidivism from data like juvenile arrests, criminal records in the family, education, social isolation, and leisure activities with 65 percent accuracy….

Recently, though, the psychologist Ralph Hertwig and legal scholar Christoph Engel have published an extensive taxonomy of motives for deliberate ignorance. They identified two sets of motives, in particular, that have a particular relevance to the need for ignorance in the face of AI.

The first set of motives revolves around impartiality and fairness. Simply put, knowledge can sometimes corrupt judgment, and we often choose to remain deliberately ignorant in response. For example, peer reviews of academic papers are usually anonymous. Insurance companies in most countries are not permitted to know all the details of their client’s health before they enroll; they only know general risk factors. This type of consideration is particularly relevant to AI, because AI can produce highly prejudicial information….(More)”.

Personal Data v. Big Data: Challenges of Commodification of Personal Data

Curated on June 21, 2018August 3, 2018 by Stefaan Verhulst

Maria Bottis and George Bouchagiar in the Open Journal of Philosophy: “Any firm today may, at little or no cost, build its own infrastructure to process personal data for commercial, economic, political, technological or any other purposes. Society has, therefore, turned into a privacy-unfriendly environment. The processing of personal data is essential for multiple economically and socially useful purposes, such as health care, education or terrorism prevention. But firms view personal data as a commodity, as a valuable asset, and heavily invest in processing for private gains. This article studies the potential to subject personal data to trade secret rules, so as to ensure the users’ control over their data without limiting the data’s free movement, and examines some positive scenarios of attributing commercial value to personal data….(More)”.

Mapping Puerto Rico’s Hurricane Migration With Mobile Phone Data

Curated on June 21, 2018August 3, 2018 by Stefaan Verhulst

Martin Echenique and Luis Melgar at CityLab: “It is well known that the U.S. Census Bureau keeps track of state-to-state migration flows. But that’s not the case with Puerto Rico. Most of the publicly known numbers related to the post-Maria diaspora from the island to the continental U.S. were driven by estimates, and neither state nor federal institutions kept track of how many Puerto Ricans have left (or returned) after the storm ravaged the entire territory last September.

But Teralytics, a New York-based tech company with offices in Zurich and Singapore, has developed a map that reflects exactly how, when, and where Puerto Ricans have moved between August 2017 and February 2018. They did it by tracking data that was harvested from a sample of nearly 500,000 smartphones in partnership with one major undisclosed U.S. cell phone carrier….

The usefulness of this kind of geo-referenced data is clear in disaster relief efforts, especially when it comes to developing accurate emergency planning and determining when and where the affected population is moving.

“Generally speaking, people have their phones with them the entire time. This tells you where people are, where they’re going to, coming from, and movement patterns,” said Steven Bellovin, a computer science professor at Columbia University and former chief technologist for the U.S. Federal Trade Commission. “It could be very useful for disaster-relief efforts.”…(More)”.

Against the Dehumanisation of Decision-Making – Algorithmic Decisions at the Crossroads of Intellectual Property, Data Protection, and Freedom of Information

Curated on June 21, 2018August 3, 2018 by Stefaan Verhulst

Paper by Guido Noto La Diega: “Nowadays algorithms can decide if one can get a loan, is allowed to cross a border, or must go to prison. Artificial intelligence techniques (natural language processing and machine learning in the first place) enable private and public decision-makers to analyse big data in order to build profiles, which are used to make decisions in an automated way.

This work presents ten arguments against algorithmic decision-making. These revolve around the concepts of ubiquitous discretionary interpretation, holistic intuition, algorithmic bias, the three black boxes, psychology of conformity, power of sanctions, civilising force of hypocrisy, pluralism, empathy, and technocracy.

The lack of transparency of the algorithmic decision-making process does not stem merely from the characteristics of the relevant techniques used, which can make it impossible to access the rationale of the decision. It depends also on the abuse of and overlap between intellectual property rights (the “legal black box”). In the US, nearly half a million patented inventions concern algorithms; more than 67% of the algorithm-related patents were issued over the last ten years and the trend is increasing.

To counter the increased monopolisation of algorithms by means of intellectual property rights (with trade secrets leading the way), this paper presents three legal routes that enable citizens to ‘open’ the algorithms.

First, copyright and patent exceptions, as well as trade secrets are discussed.

Second, the GDPR is critically assessed. In principle, data controllers are not allowed to use algorithms to take decisions that have legal effects on the data subject’s life or similarly significantly affect them. However, when they are allowed to do so, the data subject still has the right to obtain human intervention, to express their point of view, as well as to contest the decision. Additionally, the data controller shall provide meaningful information about the logic involved in the algorithmic decision.

Third, this paper critically analyses the first known case of a court using the access right under the freedom of information regime to grant an injunction to release the source code of the computer program that implements an algorithm.

Only an integrated approach – which takes into account intellectual property, data protection, and freedom of information – may provide the citizen affected by an algorithmic decision of an effective remedy as required by the Charter of Fundamental Rights of the EU and the European Convention on Human Rights….(More)”.

Ghost Cities: Built but Never Inhabited

Curated on June 21, 2018August 3, 2018 by Stefaan Verhulst

Civic Data Design Lab at UrbanNext: “Ghost Cities are vacant neighborhoods and sometimes whole cities that were built but were never inhabited. Their existence is a physical manifestation of Chinese overdevelopment in real estate and the dependence on housing as an investment strategy. Little data exists which establishes the location and extent of these Ghost Cities in China. MIT’s Civic Data Design Lab developed a model using data scraped from Chinese social media sites and Baidu (Chinese Google Maps) to create one of the first maps identifying the locations of Chinese Ghost Cities….

Quantifying the extent and location of Ghost Cities is complicated by the fact that the Chinese government keeps a tight hold on data about sales and occupancy of buildings. Even local planners may have a hard time acquiring it. The Civic Data Design Lab developed a model to identify Ghost Cities based on the idea that amenities (grocery stores, hair salons, restaurants, schools, retail, etc.) are the mark of a healthy community and the lack of amenities might indicate locations where no one lives. Given the lack of openly available data in China, data was scraped from Chinese social media and websites, including Dianping (Chinese Yelp), Amap (Chinese Map Quest), Fang (Chinese Zillow), and Baidu (Chinese Google Maps) using openly accessible Application Programming Interfaces(APIs).

Using data scraped from social media sites in Chengdu and Shenyang, the model was tested using 300 m x 300 m grid cells marking residential locations. Each grid cell was given an amenity accessibility score based on the distance and clustering of amenities nearby. Residential areas that had a cluster of low scores were marked as Ghost Cities. The results were ground-truthed through site visits documenting the location using aerial photography from drones and interviews with local stakeholders.

The model worked well at documenting under-utilized residential locations in these Chinese cities, picking up everything from vacant housing and stalled construction to abandoned older residential locations, creating the first data set that marks risk in the Chinese real estate market. The research shows that data available through social media can help locate and estimate risk in the Chinese real estate market. Perhaps more importantly, however, identifying where these areas are concentrated can help city planners, developers and local citizens make better investment decisions and address the risk created by these under-utilized developments….(More)”.

When Technology Gets Ahead of Society

Curated on June 20, 2018August 3, 2018 by Stefaan Verhulst

Tarun Khanna at Harvard Business Review: “Drones, originally developed for military purposes, weren’t approved for commercial use in the United States until 2013. When that happened, it was immediately clear that they could be hugely useful to a whole host of industries—and almost as quickly, it became clear that regulation would be a problem. The new technology raised multiple safety and security issues, there was no consensus on who should write rules to mitigate those concerns, and the knowledge needed to develop the rules didn’t yet exist in many cases. In addition, the little flying robots made a lot of people nervous.

Such regulatory, logistical, and social barriers to adopting novel products and services are very common. In fact, technology routinely outstrips society’s ability to deal with it. That’s partly because tech entrepreneurs are often insouciant about the legal and social issues their innovations birth. Although electric cars are subsidized by the federal government, Tesla has run afoul of state and local regulations because it bypasses conventional dealers to sell directly to consumers. Facebook is only now facing up to major regulatory concerns about its use of data, despite being massively successful with users and advertisers.

It’s clear that even as innovations bring unprecedented comfort and convenience, they also threaten old ways of regulating industries, running a business, and making a living. This has always been true. Thus early cars weren’t allowed to go faster than horses, and some 19th-century textile workers used sledgehammers to attack the industrial machinery they feared would displace them. New technology can even upend social norms: Consider how dating apps have transformed the way people meet.

Entrepreneurs, of course, don’t really care that the problems they’re running into are part of a historical pattern. They want to know how they can manage—and shorten—the period between the advent of a technology and the emergence of the rules and new behaviors that allow society to embrace its possibilities.

Interestingly, the same institutional murkiness that pervades nascent industries such as drones and driverless cars is something I’ve also seen in developing countries. And strange though this may sound, I believe that tech entrepreneurs can learn a lot from businesspeople who have succeeded in the world’s emerging markets.

Entrepreneurs in Brazil or Nigeria know that it’s pointless to wait for the government to provide the institutional and market infrastructure their businesses need, because that will simply take too long. They themselves must build support structures to compensate for what Krishna Palepu and I have referred to in earlier writings as “institutional voids.” They must create the conditions that will allow them to create successful products or services.

Tech-forward entrepreneurs in developed economies may want to believe that it’s not their job to guide policy makers and the public—but the truth is that nobody else can play that role. They may favor hardball tactics, getting ahead by evading rules, co-opting regulators, or threatening to move overseas. But in the long term, they’d be wiser to use soft power, working with a range of partners to co-create the social and institutional fabric that will support their growth—as entrepreneurs in emerging markets have done.…(More)”.