Author: Stefaan Verhulst

Chicago police see less violent crime after using predictive code

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Jon Fingas at Engadget: “Law enforcement has been trying predictive policing software for a while now, but how well does it work when it’s put to a tough test? Potentially very well, according to Chicago police. The city’s 7th District police reportthat their use of predictive algorithms helped reduce the number of shootings 39 percent year-over-year in the first 7 months of 2017, with murders dropping by 33 percent. Three other districts didn’t witness as dramatic a change, but they still saw 15 to 29 percent reductions in shootings and a corresponding 9 to 18 percent drop in murders.

It mainly comes down to knowing where and when to deploy officers. One of the tools used in the 7th District, HunchLab, blends crime statistics with socioeconomic data, weather info and business locations to determine where crimes are likely to happen. Other tools (such as the Strategic Subject’s List and ShotSpotter) look at gang affiliation, drug arrest history and gunfire detection sensors.

If the performance holds, It’ll suggest that predictive policing can save lives when crime rates are particularly high, as they have been on Chicago’s South Side. However, both the Chicago Police Department and academics are quick to stress that algorithms are just one part of a larger solution. Officers still have be present, and this doesn’t tackle the underlying issues that cause crime, such as limited access to education and a lack of economic opportunity. Still, any successful reduction in violence is bound to be appreciated….(More)”.

Digital Decisions Tool

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Center for Democracy and Technology (CDT): “Two years ago, CDT embarked on a project to explore what we call “digital decisions” – the use of algorithms, machine learning, big data, and automation to make decisions that impact individuals and shape society. Industry and government are applying algorithms and automation to problems big and small, from reminding us to leave for the airport to determining eligibility for social services and even detecting deadly diseases. This new era of digital decision-making has created a new challenge: ensuring that decisions made by computers reflect values like equality, democracy, and justice. We want to ensure that big data and automation are used in ways that create better outcomes for everyone, and not in ways that disadvantage minority groups.

The engineers and product managers who design these systems are the first line of defense against unfair, discriminatory, and harmful outcomes. To help mitigate harm at the design level, we have launched the first public version of our digital decisions tool. We created the tool to help developers understand and mitigate unintended bias and ethical pitfalls as they design automated decision-making systems.

About the digital decisions tool

This interactive tool translates principles for fair and ethical automated decision-making into a series of questions that can be addressed during the process of designing and deploying an algorithm. The questions address developers’ choices, such as what data to use to train an algorithm, what factors or features in the data to consider, and how to test the algorithm. They also ask about the systems and checks in place to assess risk and ensure fairness. These questions should provoke thoughtful consideration of the subjective choices that go into building an automated decision-making system and how those choices could result in disparate outcomes and unintended harms.

The tool is informed by extensive research by CDT and others about how algorithms and machine learning work, how they’re used, the potential risks of using them to make important decisions, and the principles that civil society has developed to ensure that digital decisions are fair, ethical, and respect civil rights. Some of this research is summarized on CDT’s Digital Decisions webpage….(More)”.

Building Digital Government Strategies

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Book by Rodrigo Sandoval-Almazan et al: “This book provides key strategic principles and best practices to guide the design and implementation of digital government strategies. It provides a series of recommendations and findings to think about IT applications in government as a platform for information, services and collaboration, and strategies to avoid identified pitfalls. Digital government research suggests that information technologies have the potential to generate immense public value and transform the relationships between governments, citizens, businesses and other stakeholders. However, developing innovative and high impact solutions for citizens hinges on the development of strategic institutional, organizational and technical capabilities.

Thus far,  particular characteristics and problems of the public sector organization promote the development of poorly integrated and difficult to maintain applications. For example, governments maintain separate applications for open data, transparency, and public services, leading to duplication of efforts and a waste of resources. The costs associated with maintaining such sets of poorly integrated systems may limit the use of resources to future projects and innovation.

This book provides best practices and recommendations based on extensive research in both Mexico and the United States on how governments can develop a digital government strategy for creating public value, how to finance digital innovation in the public sector, how to building successful collaboration networks and foster citizen engagement, and how to correctly implement open government projects and open data. It will be of interest to researchers, practitioners, students, and public sector IT professionals that work in the design and implementation of technology-based projects and programs….(More)”.

Rise of the Government Chatbot

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Zack Quaintance at Government Technology: “A robot uprising has begun, except instead of overthrowing mankind so as to usher in a bleak yet efficient age of cold judgment and colder steel, this uprising is one of friendly robots (so far).

Which is all an alarming way to say that many state, county and municipal governments across the country have begun to deploy relatively simple chatbots, aimed at helping users get more out of online public services such as a city’s website, pothole reporting and open data. These chatbots have been installed in recent months in a diverse range of places including Kansas City, Mo.; North Charleston, S.C.; and Los Angeles — and by many indications, there is an accompanying wave of civic tech companies that are offering this tech to the public sector.

They range from simple to complex in scope, and most of the jurisdictions currently using them say they are doing so on somewhat of a trial or experimental basis. That’s certainly the case in Kansas City, where the city now has a Facebook chatbot to help users get more out of its open data portal.

“The idea was never to create a final chatbot that was super intelligent and amazing,” said Eric Roche, Kansas City’s chief data officer. “The idea was let’s put together a good effort, and put it out there and see if people find it interesting. If they use it, get some lessons learned and then figure out — either in our city, or with developers, or with people like me in other cities, other chief data officers and such — and talk about the future of this platform.”

Roche developed Kansas City’s chatbot earlier this year by working after hours with Code for Kansas City, the local Code for America brigade — and he did so because since in the four-plus years the city’s open data program has been active, there have been regular concerns that the info available through it was hard to navigate, search and use for average citizens who aren’t data scientists and don’t work for the city (a common issue currently being addressed by many jurisdictions). The idea behind the Facebook chatbot is that Roche can program it with a host of answers to the most prevalent questions, enabling it to both help interested users and save him time for other work….

In North Charleston, S.C., the city has adopted a text-based chatbot, which goes above common 311-style interfaces by allowing users to report potholes or any other lapses in city services they may notice. It also allows them to ask questions, which it subsequently answers by crawling city websites and replying with relevant links, said Ryan Johnson, the city’s public relations coordinator.

North Charleston has done this by partnering with a local tech startup that has deep roots in the area’s local government. The company is called Citibot …

With Citibot, residents can report a pothole at 2 a.m., or they can get info about street signs or trash pickup sent right to their phones.

There are also more complex chatbot technologies taking hold at both the civic and state levels, in Los Angeles and Mississippi, to be exact.

Mississippi’s chatbot is called Missi, and its capabilities are vast and nuanced. Residents can even use it for help submitting online payments. It’s accessible by clicking a small chat icon on the side of the website.

Back in May, Los Angeles rolled out Chip, or City Hall Internet Personality, on the Los Angeles Business Assistance Virtual Network. The chatbot aims to assist visitors by operating as a 24/7 digital assistant for visitors to the site, helping them navigate it and better understand its services by answering their inquiries. It is capable of presenting info from anywhere on the site, and it can even go so far as helping users fill out forms or set up email alerts….(More)”

The Nudging Divide in the Digital Big Data Era

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Julia M. Puaschunder in the International Robotics & Automation Journal: “Since the end of the 1970ies a wide range of psychological, economic and sociological laboratory and field experiments proved human beings deviating from rational choices and standard neo-classical profit maximization axioms to fail to explain how human actually behave. Behavioral economists proposed to nudge and wink citizens to make better choices for them with many different applications. While the motivation behind nudging appears as a noble endeavor to foster peoples’ lives around the world in very many different applications, the nudging approach raises questions of social hierarchy and class division. The motivating force of the nudgital society may open a gate of exploitation of the populace and – based on privacy infringements – stripping them involuntarily from their own decision power in the shadow of legally-permitted libertarian paternalism and under the cloak of the noble goal of welfare-improving global governance. Nudging enables nudgers to plunder the simple uneducated citizen, who is neither aware of the nudging strategies nor able to oversee the tactics used by the nudgers.

The nudgers are thereby legally protected by democratically assigned positions they hold or by outsourcing strategies used, in which social media plays a crucial rule. Social media forces are captured as unfolding a class dividing nudgital society, in which the provider of social communication tools can reap surplus value from the information shared of social media users. The social media provider thereby becomes a capitalist-industrialist, who benefits from the information shared by social media users, or so-called consumer-workers, who share private information in their wish to interact with friends and communicate to public. The social media capitalist-industrialist reaps surplus value from the social media consumer-workers’ information sharing, which stems from nudging social media users. For one, social media space can be sold to marketers who can constantly penetrate the consumer-worker in a subliminal way with advertisements. But also nudging occurs as the big data compiled about the social media consumer-worker can be resold to marketers and technocrats to draw inferences about consumer choices, contemporary market trends or individual personality cues used for governance control, such as, for instance, border protection and tax compliance purposes.

The law of motion of the nudging societies holds an unequal concentration of power of those who have access to compiled data and who abuse their position under the cloak of hidden persuasion and in the shadow of paternalism. In the nudgital society, information, education and differing social classes determine who the nudgers and who the nudged are. Humans end in different silos or bubbles that differ in who has power and control and who is deceived and being ruled. The owners of the means of governance are able to reap a surplus value in a hidden persuasion, protected by the legal vacuum to curb libertarian paternalism, in the moral shadow of the unnoticeable guidance and under the cloak of the presumption that some know what is more rational than others. All these features lead to an unprecedented contemporary class struggle between the nudgers (those who nudge) and the nudged (those who are nudged), who are divided by the implicit means of governance in the digital scenery. In this light, governing our common welfare through deceptive means and outsourced governance on social media appears critical. In combination with the underlying assumption of the nudgers knowing better what is right, just and fair within society, the digital age and social media tools hold potential unprecedented ethical challenges….(More)”

Algorithmic Transparency for the Smart City

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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)”.

Scientists Use Google Earth and Crowdsourcing to Map Uncharted Forests

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Katie Fletcher, Tesfay Woldemariam and Fred Stolle at EcoWatch: “No single person could ever hope to count the world’s trees. But a crowd of them just counted the world’s drylands forests—and, in the process, charted forests never before mapped, cumulatively adding up to an area equivalent in size to the Amazon rainforest.

Current technology enables computers to automatically detect forest area through satellite data in order to adequately map most of the world’s forests. But drylands, where trees are fewer and farther apart, stymied these modern methods. To measure the extent of forests in drylands, which make up more than 40 percent of land surface on Earth, researchers from UN Food and Agriculture Organization, World Resources Institute and several universities and organizations had to come up with unconventional techniques. Foremost among these was turning to residents, who contributed their expertise through local map-a-thons….

Google Earth collects satellite data from several satellites with a variety of resolutions and technical capacities. The dryland satellite imagery collection compiled by Google from various providers, including Digital Globe, is of particularly high quality, as desert areas have little cloud cover to obstruct the views. So while difficult for algorithms to detect non-dominant land cover, the human eye has no problem distinguishing trees in the landscapes. Using this advantage, the scientists decided to visually count trees in hundreds of thousands of high-resolution images to determine overall dryland tree cover….

Armed with the quality images from Google that allowed researchers to see objects as small as half a meter (about 20 inches) across, the team divided the global dryland images into 12 regions, each with a regional partner to lead the counting assessment. The regional partners in turn recruited local residents with practical knowledge of the landscape to identify content in the sample imagery. These volunteers would come together in participatory mapping workshops, known colloquially as “map-a-thons.”…

Utilizing local landscape knowledge not only improved the map quality but also created a sense of ownership within each region. The map-a-thon participants have access to the open source tools and can now use these data and results to better engage around land use changes in their communities. Local experts, including forestry offices, can also use this easily accessible application to continue monitoring in the future.

Global Forest Watch uses medium resolution satellites (30 meters or about 89 feet) and sophisticated algorithms to detect near-real time deforestation in densely forested area. The dryland tree cover maps complement Global Forest Watch by providing the capability to monitor non-dominant tree cover and small-scale, slower-moving events like degradation and restoration. Mapping forest change at this level of detail is critical both for guiding land decisions and enabling government and business actors to demonstrate their pledges are being fulfilled, even over short periods of time.

The data documented by local participants will enable scientists to do many more analyses on both natural and man-made land changes including settlements, erosion features and roads. Mapping the tree cover in drylands is just the beginning….(More)”.

How data can heal our oceans

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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)”.

Getting on the map: How to fix the problem with addresses

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Joshua Howgego at New Scientist: “Kwandengezi is a beguiling neighbourhood on the outskirts of Durban. Its ramshackle dwellings are spread over rolling green hills, with dirt roads winding in between. Nothing much to put it on the map. Until last year, that is, when weird signs started sprouting, nailed to doors, stapled to fences or staked in front of houses. Each consisted of three seemingly random words. Cutaway.jazz.wording said one; tokens.painted.enacted read another.

In a neighbourhood where houses have no numbers and the dirt roads no names, these signs are the fastest way for ambulances to locate women going into labour and who need ferrying to the nearest hospital. The hope is that signs like this will save lives and be adopted elsewhere. For the residents of KwaNdengezi in South Africa aren’t alone – recent estimates suggest that only 80 or so countries worldwide have an up-to-date addressing system. And even where one exists, it isn’t always working as well as it could.

Poor addresses aren’t simply confusing: they frustrate businesses and can shave millions of dollars off economic output. That’s why there’s a growing feeling that we need to reinvent the address – and those makeshift three-word signs are just the beginning.

“Poor addresses frustrate businesses and can shave millions of dollars off economic output”

In itself, an address is a simple thing: its purpose is to unambiguously identify a point on Earth’s surface. But, it also forms a crucial part of the way societies are managed. Governments use lists of addresses to work out how many people they need to serve; without an address by your name, you can’t apply for a passport…(More)”.

Personal finance questions elicit slightly different answers in phone surveys than online

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 and   at Pew Research: “People polled by telephone are slightly less likely than those interviewed online to say their personal finances are in “poor shape” (14% versus 20%, respectively), a Pew Research Center survey experiment has found.

The experiment, conducted in February and March, is part of a line of research at the Center looking into “mode effects” – in this case, whether findings from self-administered web surveys differ from those of interviewer-administered phone surveys.

In particular, survey researchers have long known that Americans may be more likely to give a “socially desirable” response (and less likely to give a stigmatized or undesirable answer) in an interviewer-administered survey than in one that is self-administered. Mode effects can also result from other differences in survey design, such as seeing the answer choices visually on the web versus hearing them over the phone.

The Center’s experiment randomly assigned respondents to a survey method (online or telephone). Although it found that political questions, such as whether respondents approve of President Donald Trump, don’t elicit significant mode effects, some other, more personal items clearly do. When asked whether or not they had received financial assistance from a family member in the past year, for instance, just 15% of phone respondents say yes. That share is significantly higher (26%) among web respondents….

While the findings from this experiment suggest that self-administered surveys may be more accurate than interviewer-administered approaches as a way to measure financial stress (all else being equal), this does not mean that past telephone-based research arrived at erroneous conclusions regarding financial stress – for example, what predicts it or how the likelihood varies across subgroups. That said, researchers studying financial stress should consider that phone surveys have, at least to some degree, been understating the share of Americans experiencing economic hardship….(More)”.

Note: Survey methodology can be found here, and the topline is available here.

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