The New York City Business Atlas: Leveling the Playing Field for Small Businesses with Open Data


Chapter by Stefaan Verhulst and Andrew Young in Smarter New York City:How City Agencies Innovate. Edited by André Corrêa d’Almeida: “While retail entrepreneurs, particularly those operating in the small-business space, are experts in their respective trades, they often lack access to high-quality information about social, environmental, and economic conditions in the neighborhoods where they operate or are considering operating.

The New York City Business Atlas, conceived by the Mayor’s Office of Data Analytics (MODA) and the Department of Small Business Services, is designed to alleviate that information gap by providing a public web-based tool that gives small businesses access to high-quality data to help them decide where to establish a new business or expand an existing one. e tool brings together a diversity of data, including business-fling data from the Department of Consumer Affairs, sales-tax data from the Department of Finance, demographic data from the census, and traffic data from Placemeter, a New York City startup focusing on real-time traffic information.

The initial iteration of the Business Atlas made useful and previously inaccessible data available to small-business owners and entrepreneurs in an innovative manner. After a few years, however, it became clear that the tool was not experiencing the level of use or creating the level of demonstrable impact anticipated. Rather than continuing down the same path or abandoning the effort entirely, MODA pivoted to a new approach, moving from the Business Atlas as a single information-providing tool to the Business Atlas as a suite of capabilities aimed at bolstering New York’s small-business community.

Through problem- and user-centered efforts, the Business Atlas is now making important insights available to stakeholders who can put it to meaningful use—from how long it takes to open a restaurant in the city to which areas are most in need of education and outreach to improve their code compliance. This chapter considers the open data environment from which the Business Atlas was launched, details the initial version of the Business Atlas and the lessons it generated and describes the pivot to this new approach….(More)”.

Ethics & Algorithms Toolkit


Toolkit: “Government leaders and staff who leverage algorithms are facing increasing pressure from the public, the media, and academic institutions to be more transparent and accountable about their use. Every day, stories come out describing the unintended or undesirable consequences of algorithms. Governments have not had the tools they need to understand and manage this new class of risk.

GovEx, the City and County of San Francisco, Harvard DataSmart, and Data Community DC have collaborated on a practical toolkit for cities to use to help them understand the implications of using an algorithm, clearly articulate the potential risks, and identify ways to mitigate them….We developed this because:

  • We saw a gap. There are many calls to arms and lots of policy papers, one of which was a DataSF research paper, but nothing practitioner-facing with a repeatable, manageable process.
  • We wanted an approach which governments are already familiar with: risk management. By identifing and quantifying levels of risk, we can recommend specific mitigations.. …(More)”.

United Nations accidentally exposed passwords and sensitive information to the whole internet


Micah Lee at The Intercept: “The United Nations accidentally published passwords, internal documents, and technical details about websites when it misconfigured popular project management service Trello, issue tracking app Jira, and office suite Google Docs.

The mistakes made sensitive material available online to anyone with the proper link, rather than only to specific users who should have access. Affected data included credentials for a U.N. file server, the video conferencing system at the U.N.’s language school, and a web development environment for the U.N.’s Office for the Coordination of Humanitarian Affairs. Security researcher Kushagra Pathak discovered the accidental leak and notified the U.N. about what he found a little over a month ago. As of today, much of the material appears to have been taken down.

In an online chat, Pathak said he found the sensitive information by running searches on Google. The searches, in turn, produced public Trello pages, some of which contained links to the public Google Docs and Jira pages.

Trello projects are organized into “boards” that contain lists of tasks called “cards.” Boards can be public or private. After finding one public Trello board run by the U.N., Pathak found additional public U.N. boards by using “tricks like by checking if the users of one Trello board are also active on some other boards and so on.” One U.N. Trello board contained links to an issue tracker hosted on Jira, which itself contained even more sensitive information. Pathak also discovered links to documents hosted on Google Docs and Google Drive that were configured to be accessible to anyone who knew their web addresses. Some of these documents contained passwords….Here is just some of the sensitive information that the U.N. accidentally made accessible to anyone who Googled for it:

  • A social media team promoting the U.N.’s “peace and security” efforts published credentials to access a U.N. remote file access, or FTP, server in a Trello card coordinating promotion of the International Day of United Nations Peacekeepers. It is not clear what information was on the server; Pathak said he did not connect to it.
  • The U.N.’s Language and Communication Programme, which offers language courses at U.N. Headquarters in New York City, published credentials for a Google account and a Vimeo account. The program also exposed, on a publicly visible Trello board, credentials for a test environment for a human resources web app. It also made public a Google Docs spreadsheet, linked from a public Trello board, that included a detailed meeting schedule for 2018, along with passwords to remotely access the program’s video conference system to join these meetings.
  • One public Trello board used by the developers of Humanitarian Response and ReliefWeb, both websites run by the U.N.’s Office for the Coordination of Humanitarian Affairs, included sensitive information like internal task lists and meeting notes. One public card from the board had a PDF, marked “for internal use only,” that contained a map of all U.N. buildings in New York City. …(More)”.

Computers Can Solve Your Problem. You May Not Like The Answer


David Scharfenberg at the Boston Globe: “Years of research have shown that teenagers need their sleep. Yet high schools often start very early in the morning. Starting them later in Boston would require tinkering with elementary and middle school schedules, too — a Gordian knot of logistics, pulled tight by the weight of inertia, that proved impossible to untangle.

Until the computers came along.

Last year, the Boston Public Schools asked MIT graduate students Sébastien Martin and Arthur Delarue to build an algorithm that could do the enormously complicated work of changing start times at dozens of schools — and rerouting the hundreds of buses that serve them….

The algorithm was poised to put Boston on the leading edge of a digital transformation of government. In New York, officials were using a regression analysis tool to focus fire inspections on the most vulnerable buildings. And in Allegheny County, Pa., computers were churning through thousands of health, welfare, and criminal justice records to help identify children at risk of abuse….

While elected officials tend to legislate by anecdote and oversimplify the choices that voters face, algorithms can chew through huge amounts of complicated information. The hope is that they’ll offer solutions we’ve never imagined ­— much as Google Maps, when you’re stuck in traffic, puts you on an alternate route, down streets you’ve never traveled.

Dataphiles say algorithms may even allow us to filter out the human biases that run through our criminal justice, social service, and education systems. And the MIT algorithm offered a small window into that possibility. The data showed that schools in whiter, better-off sections of Boston were more likely to have the school start times that parents prize most — between 8 and 9 a.m. The mere act of redistributing start times, if aimed at solving the sleep deprivation problem and saving money, could bring some racial equity to the system, too.

Or, the whole thing could turn into a political disaster.

District officials expected some pushback when they released the new school schedule on a Thursday night in December, with plans to implement in the fall of 2018. After all, they’d be messing with the schedules of families all over the city.

But no one anticipated the crush of opposition that followed. Angry parents signed an online petition and filled the school committee chamber, turning the plan into one of the biggest crises of Mayor Marty Walsh’s tenure. The city summarily dropped it. The failure would eventually play a role in the superintendent’s resignation.

It was a sobering moment for a public sector increasingly turning to computer scientists for help in solving nagging policy problems. What had gone wrong? Was it a problem with the machine? Or was it a problem with the people — both the bureaucrats charged with introducing the algorithm to the public, and the public itself?…(More)”

How Insurance Companies Used Bad Science to Discriminate


Jessie Wright-Mendoza at JStor: “After the Civil War, the United States searched for ways to redefine itself. But by the 1880’s, the hopes of Reconstruction had dimmed. Across the United States there was instead a push to formalize and legalize discrimination against African-Americans. The effort to marginalize the first generation of free black Americans infiltrated nearly every aspect of daily life, including the cost of insurance.

Initially, African-Americans could purchase life insurance policies on equal footing with whites. That all changed in 1881. In March of that year Prudential, one of the country’s largest insurers, announced that policies held by black adults would be worth one-third less than the same plans held by whites. Their weekly premiums would remain the same. Benefits for black children didn’t change, but weekly premiums for their policies would rise by five cents.

Prudential defended the decision by pointing out that the black mortality rate was higher than the white mortality rate. Therefore, they explained, claims paid out for black policyholders were a disproportionate amount of all payouts. Most of the major life insurance companies followed suit, making it nearly impossible for African-Americans to gain coverage. Across the industry, companies blocked agents from soliciting African-American customers and denied commission for any policies issued to blacks.

The public largely accepted the statistical explanation for unequal coverage. The insurer’s job was to calculate risk. Race was merely another variable like occupation or geographic location. As one trade publication put it in 1891: “Life insurance companies are not negro-maniacs, they are business institutions…there is no sentiment and there are no politics in it.”

Companies considered race-based risk the same for all African-Americans, whether they were strong or sickly, educated or uneducated, from the country or the city. The “science” behind the risk formula is credited to Prudential statistician Frederick L. Hoffman, whose efforts to prove the genetic inferiority of the black race were used to justify the company’s discriminatory policies….(More)”.

The Hacking of America


Jill Lepore at the New York Times: “Every government is a machine, and every machine has its tinkerers — and its jams. From the start, machines have driven American democracy and, just as often, crippled it. The printing press, the telegraph, the radio, the television, the mainframe, cable TV, the internet: Each had wild-eyed boosters who promised that a machine could hold the republic together, or make it more efficient, or repair the damage caused by the last machine. Each time, this assertion would be both right and terribly wrong. But lately, it’s mainly wrong, chiefly because the rules that prevail on the internet were devised by people who fundamentally don’t believe in government.

The Constitution itself was understood by its framers as a machine, a precisely constructed instrument whose measures — its separation of powers, its checks and balances — were mechanical devices, as intricate as the gears of a clock, designed to thwart tyrants, mobs and demagogues, and to prevent the forming of factions. Once those factions began to appear, it became clear that other machines would be needed to establish stable parties. “The engine is the press,” Thomas Jefferson, an inveterate inventor, wrote in 1799.

The United States was founded as a political experiment; it seemed natural that it should advance and grow through technological experiment. Different technologies have offered different fixes. Equality was the promise of the penny press, newspapers so cheap that anyone could afford them. The New York Sun was first published in 1833. “It shines for all” was its common-man motto. Union was the promise of the telegraph. “The greatest revolution of modern times, and indeed of all time, for the amelioration of society, has been effected by the magnetic telegraph,” The Sun announced, proclaiming “the annihilation of space.”
Time was being annihilated too. As The New York Herald pointed out, the telegraph appeared to make it possible for “the whole nation” to have “the same idea at the same moment.” Frederick Douglass was convinced that the great machines of the age were ushering in an era of worldwide political revolution. “Thanks to steam navigation and electric wires,” he wrote, “a revolution cannot be confined to the place or the people where it may commence but flashes with lightning speed from heart to heart.” Henry David Thoreau raised an eyebrow: “We are in great haste to construct a magnetic telegraph from Maine to Texas; but Maine and Texas, it may be, have nothing important to communicate.”

Even that savage war didn’t diminish Americans’ faith that technology could solve the problem of political division. In the 1920s, Herbert Hoover, as secretary of commerce, rightly anticipated that radio, the nation’s next great mechanical experiment, would make it possible for political candidates and officeholders to speak to voters without the bother and expense of traveling to meet them. NBC began radio broadcasting in 1926, CBS in 1928. By the end of the decade, nearly every household would have a wireless. Hoover promised that radio would make Americans “literally one people.”

That radio fulfilled this promise for as long as it did is the result of decisions made by Mr. Hoover, a Republican who believed that the government had a role to play in overseeing the airwaves by issuing licenses for frequencies to broadcasting companies and regulating their use. “The ether is a public medium,” he insisted, “and its use must be for the public benefit.” He pressed for passage of the Radio Act of 1927, one of the most consequential and underappreciated acts of Progressive reform — insisting that programmers had to answer to the public interest. That commitment was extended to television in 1949 when the Federal Communications Commission, the successor to the Federal Radio Commission, established the Fairness Doctrine, a standard for television news that required a “reasonably balanced presentation” of different political views….

All of this history was forgotten or ignored by the people who wrote the rules of the internet and who peer out upon the world from their offices in Silicon Valley and boast of their disdain for the past. But the building of a new machinery of communications began even before the opening of the internet. In the 1980s, conservatives campaigned to end the Fairness Doctrine in favor of a public-interest-based rule for broadcasters, a market-based rule: If people liked it, broadcasters could broadcast it….(More)”

Satellite Images and Shadow Analysis: How The Times Verifies Eyewitness Videos


 Christoph Koettl at the New York Times: “Was a video of a chemical attack really filmed in Syria? What time of day did an airstrike happen? Which military unit was involved in a shooting in Afghanistan? Is this dramatic image of glowing clouds really showing wildfires in California?

These are some of the questions the video team at The New York Times has to answer when reviewing raw eyewitness videos, often posted to social media. It can be a highly challenging process, as misinformation shared through digital social networks is a serious problem for a modern-day newsroom. Visual information in the digital age is easy to manipulate, and even easier to spread.

What is thus required for conducting visual investigations based on social media content is a mix of traditional journalistic diligence and cutting-edge internet skills, as can be seen in our recent investigation into the chemical attack in Douma, Syria.

 The following provides some insight into our video verification process. It is not a comprehensive overview, but highlights some of our most trusted techniques and tools….(More)”.

Don’t forget people in the use of big data for development


Joshua Blumenstock at Nature: “Today, 95% of the global population has mobile-phone coverage, and the number of people who own a phone is rising fast (see ‘Dialling up’)1. Phones generate troves of personal data on billions of people, including those who live on a few dollars a day. So aid organizations, researchers and private companies are looking at ways in which this ‘data revolution’ could transform international development.

Some businesses are starting to make their data and tools available to those trying to solve humanitarian problems. The Earth-imaging company Planet in San Francisco, California, for example, makes its high-resolution satellite pictures freely available after natural disasters so that researchers and aid organizations can coordinate relief efforts. Meanwhile, organizations such as the World Bank and the United Nations are recruiting teams of data scientists to apply their skills in statistics and machine learning to challenges in international development.

But in the rush to find technological solutions to complex global problems there’s a danger of researchers and others being distracted by the technology and losing track of the key hardships and constraints that are unique to each local context. Designing data-enabled applications that work in the real world will require a slower approach that pays much more attention to the people behind the numbers…(More)”.

Pick your poison: How a crowdsourcing app helped identify and reduce food poisoning


Alex Papas at LATimes: “At some point in life, almost everyone will have experienced the debilitating effects of a foodborne illness. Whether an under-cooked chicken kebab, an E. coli infested salad or some toxic fish, a good day can quickly become a loathsome frenzy of vomiting and diarrhoea caused by poorly prepared or poorly kept food.

Since 2009, the website iwaspoisoned.com has allowed victims of food-poisoning victims to help others avoid such an ordeal by crowd-sourcing food illnesses on one easy-to-use, consumer-led platform.

Whereas previously a consumer struck down by food poisoning may have been limited to complaining to the offending food outlet, IWasPosioned allows users to submit detailed reports of food-poisoning incidents – including symptoms, location and space to describe the exact effects and duration of the incident. The information is then transferred in real time to public health organisations and food industry groups, who  use the data to flag potentially dangerous foodborne illness before a serious outbreak occurs.

In the United States alone, where food safety standards are among the highest in the world, there are still 48 million cases of food poisoning per year. From those cases, 128,000 result in hospitalisation and 3,000 in death, according to data from the U.S. Food and Drug Association.

Back in 2008 the site’s founder, Patrick Quade, himself fell foul to food poisoning after eating a BLT from a New York deli which caused him to be violently ill. Concerned by the lack of options for reporting such incidents, he set up the novel crowdsourcing platform, which also aims at improving transparency in the food monitoring industry.

The emergence of IWasPoisoned is part of the wider trend of consumers taking revenge against companies via digital platforms, which spans various industries. In the case of IWasPoisoned, reports of foodborne illness have seriously tarnished the reputations of several major food retailers….(More)”.

How Smart Should a City Be? Toronto Is Finding Out


Laura Bliss at CityLab: “A data-driven “neighborhood of the future” masterminded by a Google corporate sibling, the Quayside project could be a milestone in digital-age city-building. But after a year of scandal in Silicon Valley, questions about privacy and security remain…

Quayside was billed as “the world’s first neighborhood built from the internet up,” according to Sidewalk Labs’ vision plan, which won the RFP to develop this waterfront parcel. The startup’s pitch married “digital infrastructure” with an utopian promise: to make life easier, cheaper, and happier for Torontonians.

Everything from pedestrian traffic and energy use to the fill-height of a public trash bin and the occupancy of an apartment building could be counted, geo-tagged, and put to use by a wifi-connected “digital layer” undergirding the neighborhood’s physical elements. It would sense movement, gather data, and send information back to a centralized map of the neighborhood. “With heightened ability to measure the neighborhood comes better ways to manage it,” stated the winning document. “Sidewalk expects Quayside to become the most measurable community in the world.”

“Smart cities are largely an invention of the private sector—an effort to create a market within government,” Wylie wrote in Canada’s Globe and Mail newspaper in December 2017. “The business opportunities are clear. The risks inherent to residents, less so.” A month later, at a Toronto City Council meeting, Wylie gave a deputation asking officials to “ensure that the data and data infrastructure of this project are the property of the city of Toronto and its residents.”

In this case, the unwary Trojans would be Waterfront Toronto, the nonprofit corporation appointed by three levels of Canadian government to own, manage, and build on the Port Lands, 800 largely undeveloped acres between downtown and Lake Ontario. When Waterfront Toronto gave Sidewalk Labs a green light for Quayside in October, the startup committed $50 million to a one-year consultation, which was recently extended by several months. The plan is to submit a final “Master Innovation and Development Plan” by the end of this year.

That somewhat Orwellian vision of city management had privacy advocates and academics concerned from the the start. Bianca Wylie, the co-founder of the technology advocacy group Tech Reset Canada, has been perhaps the most outspoken of the project’s local critics. For the last year, she’s spoken up at public fora, written pointed op-edsand Medium posts, and warned city officials of what she sees as the “Trojan horse” of smart city marketing: private companies that stride into town promising better urban governance, but are really there to sell software and monetize citizen data.

But there has been no guarantee about who would own the data at the core of its proposal—much of which would ostensibly be gathered in public space. Also unresolved is the question of whether this data could be sold. With little transparency about what that means from the company or its partner, some Torontonians are wondering what Waterfront Toronto—and by extension, the public—is giving away….(More)”.