Marian.panganiban

Ever planned to take the bus, but wound up calling an Uber? That’s what the Pinellas Suncoast Transit Authority did in 2016.

That year, ridership across St. Petersburg, Florida’s fixed route bus lines plummeted by 11 percent—twice the drop PSTA experienced in the first year of the recession, and one of the deepest declines of any major U.S. system. Pinellas County constituents had recently rejected the concept of transit even more directly: PSTA’s one-cent “Greenlight Pinellas” sales tax proposal to spread bus service and build a light rail system bombed at the ballots in 2014.

That forced the agency to eliminate some of its existing routes, and to rethink how it was doing business. So it called in the apps. To cover the areas it had left transit-bare, PSTA became the first agency in the country to subsidize Uber trips. Since its “Direct Connect” program launched in February 2016, PSTA has given $5 discounts on rides provided by Uber and a local taxi company (and as of more recently, Lyft) to and from 24 popular bus stops in its service area to as many as 1,000 riders per month. “This is the future,” PSTA CEO Brad Miller told reporters on the day of the launch of the program, which was widely hailed as an example of what an amicable partnership between mass-transit and ride-hailing would look like.

By and large, much of the North American transit industry would seem to agree. According to a report released this week by DePaul University’s Chaddick Institute for Metropolitan Development, since 2016 at least 27 more communities across the United States have joined arms with Uber, Lyft, and other transportation network companies (TNCs) to supplement or substitute traditional service—even as questions linger about the wisdom of undertaking these kinds of programs.

Municipalities of virtually every size nationwide are dipping their toes into contracting with ride-hailing services. Washington, D.C., proposed a partnership with Uber as a transportation response to non-emergency 911 calls. Centennial, Colorado, offers free Lyft trips to light rail stations; Dublin, California, has across-the-board half-price Uber and Lyft fares. The partnerships range in focus and in scope: The most robust program in the country might be in Monrovia, California, where visitors and residents have reportedly taken more than 53,000 subsidized rides since its transit agency began offering $.50 rides on all Lyft trips within the city’s boundaries in March 2018. Others, like those in Boston and Las Vegas, are more limited, drawing on Uber and Lyft as platforms for paratransit that are easier to use for passengers and substantially cheaper for agencies to subsidize.

In many ways, the same factors that pushed Pinellas County to the world of ride-hailing have pushed the rest of these cities: a desire to provide higher-quality mobility in areas where transit options fall short or where there’s not enough parking. There’s also a degree of brand-consciousness at play, said Joseph Schwieterman, the director of DePaul’s Chaddick Institute, who co-authored the report with Mallory Livingston, a DePaul graduate researcher. “Transit agencies can’t afford to become like the taxi industry and let the world pass them by," Schwieterman said.

Working in tandem with Uber, Lyft, and other similar offerings is a way for transit agencies to insert themselves on the primary communication channel riders are already using—their smartphones—and could be a step towards reimagining the on- and off-board customer experience.

The question of whether ride-hailing apps are pulling riders on or off public transit—complementing it, or cannibalizing it—has been a cloud over the transportation industry for years. Transit ridership is declining on systems across the country, particularly on buses, and especially in smaller and mid-sized cities. While Uber, Lyft, and others TNCs have frequently taken the blame, the more significant drivers in ridership declines are likely service cuts and lower gas prices. “The writing is on the wall for many lightly used bus routes,” Schwieterman said. “Everybody is scratching their heads about how to better deliver their product, given how fast-paced society is becoming.” Establishing a link to on-demand transportation could be one way to do it.

But as the transportation analyst Bruce Schaller has recently written, surveys in several major U.S. cities show in aggregate that a majority of TNC users in those cities would have taken public transit, walked, biked, or forgone their trip if the ride-hailing apps hadn’t been available. These services are siphoning off some transit passengers who can afford it, in some areas.

On the other hand, Uber and Lyft also appear to be penetrating neighborhoods with poor transit coverage and low car ownership rates, places traditional taxi services would not go. And in some cases, when it’s late at night and transit options are scant, calling a car is a far more time- and cost-effective option.

In most cities, rider demand for Uber and Lyft trips through these transit agency partnerships has not been overwhelming. That much-ballyhooed pilot program in Centennial, for example, was not extended due to insufficient demand. PSTA has seen consistent ridership increases with its Direct Connect program, growing 210 trips per month in March 2017 to 994 trips per month by August of that year, according to PSTA data provided to CityLab. That’s still not much: A mixed-traffic lane with frequent buses can move at least 1,000 people per hour.

These TNC partnerships have hardly boosted transit demand. And plenty of transportation advocates fear they could be counterproductive, by unwittingly contributing to the perception that Uber and Lyft can meaningfully replace mass transit. “I’m sure we’ll get some criticism with this report for creating a risk that funding for transit will fall as these partnerships come to the table,” Schwieterman said. “It’s a fine line between maintaining the system and outsourcing parts of the system.”

There are other risks tied to partnering with TNCs. These companies are notoriously protective of ridership data, which is a limitation for transit agencies trying to judge the success of these subsidy and tie-in programs. When PSTA signed its original contract with Uber, for example, “there was nothing in it about data,” said Bonnie Epstein, a senior planner at PSTA. The agency did eventually get some ridership totals from Uber (as noted), but nothing about the origin or destination of the trips, for example.

Similarly, there’s nothing stopping Uber, Lyft, or any other private transportation company (including taxis) from raising minimum fares without notifying public agencies first. Uber has done this repeatedly in Pinellas County since the Direct Connect program launched in 2016. According to Epstein, some riders have complained that the $5 public subsidy is no longer as useful as the cost of the Uber becomes equal to (or greater than) the cost of a second bus ticket in addition to the one they’re already buying at their connecting station. This story will be updated with responses by Uber and Lyft to requests for comment.

Partnerships between ride-hailing companies and transit agencies are still in a delicate courting stage, said Jon McBride, a business strategist with a focus on emerging transportation modes. As far as agreements go, “I expect public agencies to become more specific about their data sharing requests, ways to influence equitable access and compensation models,” he said.

By now, there’s almost a sense of inevitability that transit agencies will fold ride-hailing into some aspect of their operations. Livingston, the co-author of the report, said that she expects TNC/transit tie-ins will eventually be the default in smaller markets. Many of the partnerships so far have been pilot programs, “giving the agency experience in this area so that they can figure out what’s going to be successful in the long term,” she said. PSTA has expanded the Direct Connect program since it launched, but not all have hit the target; at least eight of the initiatives counted in her and Schwieterman’s survey have been discontinued.

Indeed, the million-dollar question about these transit agency partnerships may be what “success” looks like. Is it finding a cheaper way to do business on a seldom-used bus route? Is it creating connection points in neighborhoods that didn’t have them before? Or is buddying up with Uber and Lyft more about branding, a way for a fuddy-duddyish agency to look a little cooler and more relevant as its riders drop away? The more clearly defined the goal, the better, Schwieterman said. Public transit should embrace TNCs very carefully, lest they end up sabotaging themselves.

Sometimes, cities are not only the places where stories happen but characters in and of themselves. Here Tyler Malone explores the works of Joyce, Döblin, and Dos Passos and their city centred novels.

These three novels are modernist city novels of the interwar period that move beyond story and character to build structures and trace movements, reconstructing modern metropolises that a world war would soon change forever. Joyce, Dos Passos, and Döblin fashioned not novels but eternal text-cities in which the reader may witness, wander, get lost. […]

Cities are cement and furniture, building and bustle, things that stay still and things that move. Of course, things that stay still in a city can suddenly, and will eventually, move, grow, change, decay, disappear. Buildings crumble, stores go out of business, streets age, accumulating faultlines like faces. Things that move can and do also momentarily pause. A busker stares up at a pedestrian silhouetted by the sun, still as a statue, his last note lingering. The maelstrom of traffic often screeches to a halt.

In fact, those novels are not only city centred but text-cities in themselves:

In other words, Ulysses is not an atlas of Dublin, it is a Dublin; Berlin Alexanderplatz, likewise, is a Berlin. These are not novels; they are cities unto themselves, writ in text of stone and concrete. […]

For the reader-flâneur, linearity isn’t important; it’s about wandering through the text and seeing what one sees, letting the city speak.

—
Also on cities and books; Justin McGuirk reviews at length Richard Sennett’s Building and Dwelling: Ethics for the City on cities as communities, as buildings, and on his vision of open cities.

It also extends to the offices of tech giants like Google, which supply everything a neighborhood has to offer without employees needing to leave the building. Each of these is, for Sennett, a ghetto. Instead, he argues for a city that embraces difference, a place of porous membranes and spatial invitations. […] (emphasis mine)

[The book] has an almost Taoist attachment to harmony and balance. Give architects and planners too much control and the cité suffers; too much faith in the citizen and the ville withers.

(First article via @matthieudugal)

Tags: books   cities

A few weeks ago, I asked the readers of the Noticing newsletter to send in links to their blogs and newsletters (or to their favorite blogs and newsletters written by others). And boy, did they! I pared the submissions list down to a representative sample and sent it out as last week’s newsletter. Here’s a smaller excerpt of that list…you can find the whole thing here.

Several people wrote in about Swiss Miss, Subtraction, Damn Interesting, Cup of Jo, sites I also read regularly.

Ted pointed me towards Julia Evans’ blog, where she writes mostly (but not exclusively) about programming and technology. One of my favorite things about reading blogs is when their authors go off-topic. (Which might explain why everything on kottke.org is off-topic. Or is everything on-topic?)

Bruce sent in Follow Me Here, which linked to 3 Quarks Daily, a high-quality blog I’d lost track of.

Marcelo Rinesi blogs infrequently about a little bit of everything. “We write to figure out who we are and what we think.”

Futility Closet is “a collection of entertaining curiosities in history, literature, language, art, philosophy, and mathematics, designed to help you waste time as enjoyably as possible”. (Thx, Peter)

Michael Tsai blogs about technology in a very old school way…reading through it felt like a wearing a comfortable old t-shirt.

Sidebar: the five best design links, every day. And Nico Lumma’s Five Things, “five things everyday that I find interesting”.

Pamela wrote in with dozens of links, among them visual blog But Does It Float, neuroscience blog Mind Hacks, the old school Everlasting Blort.

Elsa recommends Accidentally in Code, written by engineer Cate Huston.

Madeleine writes Extraordinary Routines, “sharing interviews, musings and life experiments that explore the intersection between creativity and imperfection”.

Kari has kept her blog for the last 15 years. I love what she wrote about why she writes:

I also keep it out of spite, because I refuse to let social media take everything. Those shapeless, formless platforms haven’t earned it and don’t deserve it. I’ve blogged about this many times, but I still believe it: When I log into Facebook, I see Facebook. When I visit your blog, I see you.

Social media is as compelling as ever, but people are increasingly souring on the surveillance state Skinner boxes like Facebook and Twitter. Decentralized media like blogs and newsletters are looking better and better these days…

Tags: lists   weblogs

Data & Society Research Institute is seeking an early-career Researcher, with a background in social science, media studies, information studies, or science and technology studies to work with the Media Manipulation Initiative, providing original research and supporting project-related activities. This researcher will manage a project entitled the “Civil Society Intelligence Unit,” a rapid response network that informs reporters, researchers, and civil society organizations of media manipulation and disinformation campaigns. We are particularly interested in hiring a dynamic researcher who can clearly communicate the ethical, political, social, and economic ramifications of technological change. Scholars with an interest in public engagement with civil society organizations and public knowledge projects are encouraged to apply. This is a two-year, full-time position with the possibility of renewal.

The Media Manipulation Initiative (MMI) examines how different groups use the participatory culture of the internet to turn the strengths of a free society into vulnerabilities, ultimately threatening expressive freedoms and civil rights. Efforts to exploit technical, social, economic, and institutional configurations of media can catalyze social change, sow dissent, and challenge the stability of social institutions. Broadly, this initiative takes a sociotechnical approach to understanding the social, political, and economic incentives to game information systems, websites, platforms, and search engines—especially in cases where the attackers intend to destabilize democratic, social, and economic institutions.

Responsibilities:

You will be a project lead on the “Civil Society Intelligence Unit” where you will be responsible for the following:

• Map and track the ecosystem of research subjects/internet communities who are developing techniques to manipulate algorithms and platforms.
• Manage and oversee the media manipulation listserve email community.
  • Actively build networks through in-person and online interactions.
  • Research and write (or oversee production of) weekly briefings sent to a listserve.
• Publish institutional advisories and better practices documents as needed.
  • Contribute to media advisories with partnership organizations.
  • Engage with a network of disinformation researchers and collect feedback through phone calls, reports, and in-person meetings
  • Synthesize data collection into cohesive reporting strategies.
  • Work closely with the media manipulation research lead on crafting an engagement strategy for public-facing research.
  • Research and author short and long public-facing op-eds, articles, briefs, and primers.
  • Perform long-term research projects resulting in primers and white papers.
  • Write shorter, media-friendly op-eds, and articles.
  • Partner with the communications team for external content related to the project.
  • Provide commentary for journalists reporting on media manipulation.
  • Advise journalists on best reporting practices.
  • Attend events focused on disinformation and intervention and represent the organization.
  • Give academic and conference talks on media manipulation topics.

Qualities of job candidate:

• You are committed to social change and are oriented to practical applications of research.
• You bring a unique and self-reflexive perspective to analyzing phenomena and ideas in the world.
• You are committed to understanding how different groups use the tools and technologies of networked communication to manipulate sociotechnical systems.
• Because this research project deals with extremist groups, the materials you will encounter during your research are very disturbing and will include violent text, images, and video. Content can be explicit, sexist, racist, or pornographic. You must be able to communicate with your manager when you need to be reassigned to other research. We will provide self-care trainings led by Equality Labs.
• You are capable of monitoring and capturing multiple streams of fast-moving data across numerous platforms and explaining this content to other researchers, knowing when to include or omit details.
• You are looking for a team in which you can grow and strengthen research and communication skills, while taking deep dives on specific topics. You pay attention to detail, but always keep an eye on the big picture.
• Most importantly, you are excited by team-based research and are eager to share ideas and create new public research that engages multiple audiences and stakeholders.

Qualifications:

• Ability to plan and execute a project with attention to detail.
• Excellent written communication skills with ability to conduct research using multiple methods.
• Experience with organizing small and medium-sized events, from scoping participants to organizing travel to helping to define structure and outcomes.
• Comfort with a range of actors, including journalists, civil society, government, tech industry, and academia.
• Working understanding of the current state of online manipulation and disinformation and how different groups and individuals use technology to influence public conversation.
• Education: Master’s Degree, PhD preferred. (You must be finished with your degree by July 1, 2018.)

Practical considerations:

• This is not a remote position; you must work full time from the Data & Society office in the Flatiron section of New York City.
• You will be offered a generous benefits package, paid time off, and a budget for travel and projects. Additionally, we are able to provide relocation assistance if necessary.
• You must be eligible to work in the United States; we are unable to sponsor visas.

To apply, please submit the following to jobs@datasociety.net.

• Two-page cover letter describing relevant background, experience with collaborative research projects, and your interest in the Media Manipulation Initiative.
• Your Curriculum Vitae or resume.
• Submit two writing samples (e.g. dissertation chapters or articles).
• Names, affiliations, and contact information for three professional references.
• The deadline to submit your application is May 15, 2018.
• Please contact jobs@datasociety.net with any questions about the position; inquiries will not be held against your eligibility as a candidate.

Microorganisms are so small compared to humans that you might be tempted to think that they’re all about the same size. As this video shows, that is not at all the case. The rinovirus and polio virus are 0.03 micrometers (μm) wide, a red blood cell is 8 μm, a neuron 100 μm, and a frog’s egg 1 mm. That’s a span of 5 orders of magnitude, about the same difference as the height of a human to the thickness of the Earth’s atmosphere.

Watching the animation, you might have noticed the T4 bacteriophage, which looks like a cross between the aliens in Arrival and a lunar lander. Can’t be real, right? Bacteriophages are really real and terrifying…if you happen to be a bacteria. Bacteriophages attack by attaching themselves to bacteria, piercing their outer membranes, and then pumping them full of bacteriophage DNA. The phage replicates inside of the bacteria until the bacteria bursts and little baby bacteriophages are exploded out all over the place, ready to attack their own bacteria.

Tags: biology   science   video

I don’t know who my old favorite archaeologist was, but my new favorite archaeologist is Doris Jones. Jones is 90 years old and is one of the top volunteer space archaeologists on GlobalXplorer, a site that crowdsources the process of locating potential archaeological sites on satellite imagery. People like Jones look at satellite images for telltale signs of past human activity and promising locations are then passed on to field archaeologists working in the area.

Tags: archaeology   Doris Jones   video

Dieter Rams is one of the world’s most influential designers. Rams acolyte and Apple design chief Jony Ive has said of him:

Dieter Rams’ ability to bring form to a product so that it clearly, concisely and immediately communicates its meaning is remarkable… He remains utterly alone in producing a body of work so consistently beautiful, so right, and so accessible.

Gary Hustwit, director of Helvetica and Objectified, is making a documentary about Rams called Rams. Here are three short clips from the film:

Rams will include in-depth conversations with Dieter, and dive deep into his philosophy, his process, and his inspirations. But one of the most interesting parts of Dieter’s story is that he now looks back on his career with some regret. “If I had to do it over again, I would not want to be a designer,” he’s said. “There are too many unnecessary products in this world.” Dieter has long been an advocate for the ideas of environmental consciousness and long-lasting products. He’s dismayed by today’s unsustainable world of over-consumption, where “design” has been reduced to a meaningless marketing buzzword.

The movie will have original music by Brian Eno and will be released sometime later this year.

Tags: Brian Eno   design   Dieter Rams   Gary Hustwit   Jony Ive   movies   Rams   video

There are many views about how best to make cities happier. But before we get into that, it’s important to be reminded of the essence of the city. As Shakespeare said, “a city is but its people” and we know cities are not empty buildings and infrastructure, or as Edward Glaeser explains in Triumph of the City: “Cities aren’t structures; cities are people.” Therefore, any plans for increasing city happiness, should have the welfare and needs of people at the heart of such plans.

This is especially important because by 2050, 75% of the world’s population will be living in cities. There is a lot at stake. That said, any city plans should also acknowledge the reason cities come about in the first place. Ultimately, cities are economies of agglomerations, providing benefits in social welfare, health, trade and other domains. Cities offer efficient opportunities in these domains. At least they should.

Not surprisingly, city management recognizes the need to enhance such domains, and run the city more efficiently in terms of financial, human and natural resources. Smart cities are one approach to such management paradigms, especially when using technology to achieve such efficiencies. A truly smart city is one that has a wider scope which includes wellbeing, and is also looking for low-lying-fruits in terms of innovations in process improvement as well as new ways of employing low-cost tech for a better quality of life for its residents, e.g. using SMS in Quito, Ecuador to reduce harassment and improve the safety of public transport.

This and many more examples were highlighted in the Global Happiness Policy Report. The report focuses on policy recommendations in various domains such as health, education and workplace, and one chapter particularly aims at exploring the urban context of happiness as Happy Cities in a Smart World. The chapter emphasizes a systematic data-driven approach to the selection and validation of policies and interventions in the city, as well as a wider scope that also fits the notion of a smart city.

Using the findings from an EU report which ranks smart cities according to common dimensions, the GHC policy report organizes the cities chapter along the six smart city dimensions:

• Economy: unemployment, inclusive labour force
• People & Society: health, culture, social inclusion
• Governance: transparency, participation
• Mobility: commute, public transport
• Environment: air quality, sustainability
• Living Enablers: housing, urban planning

The chapter describes each of these domains with the help of cases on how technology and process improvement were used to increase wellbeing in the city. Among the cases presented was Smart Dubai’s tool for Smart Happiness Project Evaluation (SHAPE). Based on data from a sample size of over 4,300 people, the tool is based on an empirically derived model that correlates people’s happiness with the various smart city dimensions.

Using this tool, city managers are able to make objective comparisons, and therefore prioritize amongst proposed projects within the city. In this way, they would have a data-driven tool to maximize happiness and wellbeing in the city, in the context of smart city key performance indicators.

Another case is the Local Initiatives Support Corporation (LISC), a non-profit that brings together governments, private companies and non-profit organizations to revive poor communities across the United States. LISC’s Affordable Housing initiative relies on data about the needs of the population, with evidence-based design to drive grants, loans and equity investments in housing, to give more people access to the city while reducing health care costs, and increasing chances of employment. The initiative adopts a Transit-Oriented Development (TOD) approach to urban development and situates affordable housing in walkable areas near high-quality transit. In this way, LISC brings residents closer to jobs, while reducing their expense on private automobiles.

One of the defining elements of smart cities is the prevalence of public private partnerships (PPP). Such methods of operating the city are also poignant in the context of wellbeing. This is because once a successful PPP model is developed, it will lead to the sustainability of wellbeing in the city, with all stakeholders benefiting. In this manner, city custodians become true brokers of happiness.

The post Turning Smart Cities Into Happy Cities appeared first on NewCities.

Which public school will your child attend? How severe a sentence will you receive in the criminal justice system? Will you earn tenure as a teacher? In many cities, a new force is playing a critical role in answering these questions: algorithms.

Cities rely on algorithms to help make decisions that affect people’s lives in meaningful ways, from assessing teacher performance to predicting the likelihood of criminal re-offense. And yet, the general public knows almost nothing about how they work.

Take a recent example in New York City: The police department began using algorithms to help decide where to deploy officers across the city. In 2015, the New York Police Department partnered with software company Azavea to pilot the HunchLab platform, which considers a variety of factors—from historic crime to proximity to bars and bus stops—to determine where crime is most likely to happen.

The purpose of data-driven algorithms like this one is to make policing more objective and less subject to individual bias. But many worry that the biases are simply baked into the algorithms themselves. Some opponents have argued that HunchLab will disproportionately target areas with more people of color and low-income residents because they reinforce old stereotypes: Data on patterns of past arrest rates, for example, might cause an algorithm to target low-income neighborhoods where officers were historically more likely to pick up black kids for possession. Others dispute whether or not the program is effective. A study by the RAND Corporation of a similar predictive policing program in Shreveport, Louisiana, found no measurable effect on crime.  

Even if these algorithms do improve policing, mistrust will continue so long as public information is lacking. Despite a recent lawsuit by NYU’s Brennan Center for Justice that required the NYPD to release parts of its correspondence with Azavea, the public knows little about how HunchLab works, whether it uses tainted data, or is effective at reducing crime. As it stands, residents, advocates, and researchers have little ability to evaluate these tools to determine whether they are accurate or fair. Even City Council members have struggled to understand how their own precincts make staffing decisions.  

Granted, some opacity around algorithms is inevitable. Some algorithms are too complex to be communicated in a simple and satisfying way, source code is often the proprietary secret of private companies, and releasing detailed information can pose cybersecurity risks.

These caveats make algorithmic transparency tricky, but it’s worth figuring out. Governments need mechanisms for making sure algorithms are subject to the same scrutiny as other types of public decision-making. This transparency should be proactive, rather than requiring years of legal action as in the Azavea case.

This past summer, New York City Councilman James Vacca proposed a bill that was one of the first attempts to address this issue. The proposal opened a spirited debate in the city over algorithmic transparency, drawing testimony from academics and advocates eager to see radical transparency, local tech companies urging the city to remain conscious of interests in the private sector, and public leaders looking to ensure both accountability and security for algorithms. The city ultimately landed on a compromise proposal, which creates an expert task force to develop transparency recommendations for the mayor.

This bill was a good opening salvo, but now comes the more difficult task: actually developing these mechanisms for transparency. If implemented in the right way, efforts towards transparency can actually benefit cities and vendors by maximizing the value and reach of analytics work. There are a few basic requirements the task force should consider:

• Share the motivation for using an algorithm. When a city communicates its goal—for example, predicting when and where crime will happen—residents can assess intentions, and government has a benchmark for evaluating results.

• Explain what data went into the model and why. Revealing sources gives residents the opportunity to identify potential bias from data tainted by historically discriminatory practices.   

• Describe how developers analyzed the data. Different from publishing source code—which is both potentially dangerous and unhelpful to most residents—a description of process includes information that allows the public to understand how developers get from data to an output. For example, the New York Mayor’s Office of Data Analytics (MODA) explained that it used a Monte Carlo technique to optimize funding for a school lunch program, and outlined the steps involved in this process.  

• Publish performance data. Governments should release any performance evaluations provided to them by vendors, and publish their own data on success achieving policy goals initially communicated.

Regulators need to be careful that these requirements do not place so large a burden on cities that they would eschew data-driven strategies in favor of old-fashioned intuitive decision-making. But the creators of algorithms already have these conversations in private, so fulfilling these reporting mandates is really a matter of better documenting processes that are already happening.

Disclosing more information about algorithms is not only valuable from an ethical standpoint, but also benefits cities by expanding the reach and value of data analytics work. By making analytics processes publicly available, cities allow other agencies to find inspiration and insight to pursue similar projects, as well as criticize and improve existing efforts. Increased reliance on data and evidence, and increased transparency, are movements that can and should support each other as cities continue to push towards a tech-driven future.

This time it was going to be different.

Last August, Governor Andrew Cuomo of New York told the New York Times that “congestion pricing is an idea whose time has come” for New York City.

In January, New York City Council Speaker Corey Johnson announced that “we need congestion pricing, this year, this session.”

In March, Kathryn Wilde, president of the Partnership for New York City and member of Fix NYC, a group appointed by the governor to study congestion relief and transit financing in New York, wrote, “the most promising source of new revenues [to fund transit] are charges on private cars, trucks, buses and for-hire vehicles.”

Advocates believed they had finally found common ground with state and local politicians in support of charging drivers to enter Manhattan during peak hours, an idea first fleshed out in 2008 during the administration of Mayor Michael Bloomberg. Now it seems unlikely that 2018 will finally be the year of congestion pricing: Last week Assembly Democrats advanced a terrible plan that would only levy a surcharge on taxis and for-hire vehicles—hardly a congestion pricing plan or sound policy. And the clock is running out on the state budget process that will decide the fate of the plan put forth by Fix NYC in January.

But as New York’s transit crises and traffic jams continue to get worse, congestion pricing will undoubtedly remain an attractive concept that an adroit politician will eventually shepherd through Albany in some form. Unfortunately, that’s the problem. We need to talk about congestion pricing not as an abstract idea, but as a set of discrete and thoughtful plans.

In New York, Cuomo’s support of congestion pricing was lauded by advocates as a major step for the cause. In fact, by talking about congestion pricing without concrete terms or details, Cuomo has arguably done as much to undermine the policy as advance it.

For example, days before Fix NYC released its congestion pricing plan in January, the governor described the forthcoming proposal as an infinitely flexible policy with “literally an ongoing spectrum of options.” When Fix NYC was made public, Cuomo issued a statement of support with a vague concluding paragraph that undercut the plan and invoked outer-borough populism:

But, as a born and raised Queens boy, I have outer borough blood in my veins, and it is my priority that we keep costs down for hard working New Yorkers, and encourage use of mass transit. We must also find a way to reduce the costs for outer borough bridges in any plan ultimately passed.

Cuomo seems to hope that a politically painless solution to New York City’s transportation woes will just present itself. Yet it’s decades of politically painless solutions that have exacerbated congestion, degraded transit service, and allowed capital spending on transit infrastructure to reach a level of profligacy unmatched by any other city in the world. If congestion pricing is to become law in New York City and be viable as a congestion mitigator, it’s time to get specific.

At the heart of this debate sit two fundamental questions: What is congestion pricing, and why should we care about congestion? The abstract idea is simple. To impose a congestion charge, you must merely define a geography and charge motorists a price for access to it. In practice, congestion pricing comprises a multitude of options and choices that need to be considered carefully. The success or failure of any plan hinges on the careful calibration of fees, the technology used to collect fees, boundaries, exemptions, complementary policies, and adjustments to the policy as congestion levels increase.

The first dilemma any planner must grapple with is the fact that congestion is not inherently bad—in a sense, it’s what animates cities and attracts people to places like New York City in the first place. The “congestion” of people, jobs, and institutions is New York’s greatest asset. Automobile congestion, however, hinders positive forms of congestion. The more room we turn over to cars, the more they eat the city and introduce spatial barriers that are only surmounted by more automobiles and infrastructure dedicated to supporting them. If, however, we seek a balance between the different forms of congestion, we need to find ways to conserve space that can be traversed by walking, bicycles, and transit.

The congestion-pricing narrative has often verged on the ecstatic. The New York Times, for example, recently published an article that pitched congestion pricing as a policy prescription that would “unsnarl” Manhattan’s traffic. Pointing to Stockholm, Singapore, and London—three cities that have enacted congestion pricing, with varying degrees of success—the Times suggested that the main difficulty is a public relations issue more than anything else.

But by focusing on the PR challenges, the story largely ignored some key differences between each city’s congestion pricing scheme. While reports out of Stockholm are positive, travel speeds and congestion levels have moved in the wrong direction in Singapore and London over time. Singapore has even taken the step of adopting a more aggressive congestion mitigation strategy by prohibiting the number of allowable cars to increase until at least 2020.

There are currently only five congestion pricing schemes in the world that approximate what New York was trying to do, so it’s more important to consider the nuts-and-bolts of each program, rather than glossing over them and assuming congestion pricing is a well-defined and agreed-upon policy that one orders online and installs on a lazy Sunday afternoon.    

The five main things to get right are the charge; the geographic boundaries, complementary policies (such as how to spend the revenues), exemptions to the fee, and ongoing adjustments needed to ensure traffic mitigation goals are met over the long run.

The hallmark of congestion pricing is the price. How that price is determined is more art than science when politics are introduced. Many economists who study congestion pricing argue that the optimal price should approximate the short-run marginal costs of driving—pollution, deterioration of the road, and congestion. They also argue that those costs change based on levels of congestion; the price should increase as the availability of road space decreases.  

Keeping all of this straight requires a fee-collection technology that is able to compute real-time prices based on levels of congestion on a specific stretch of roadway. Move New York, a variable-price tolling plan that gained traction from elected officials and advocates starting in 2010, captures some of this dynamism by calling for different tolls on different bridges. Fix NYC proposed a blunter flat fee that mimics London’s Congestion Charge and Milan’s Area C policy. Singapore’s Electronic Road Pricing and Stockholm’s Congestion Tax, on the other hand, are more dynamic and charge different prices based on the type of vehicle, time of day, and geography.  

As tedious as it is to determine the right fee to charge motorists, selecting the right boundaries are equally challenging. New York City looks easy: Manhattan is an island, so you draw a ring around it and call it a day. That’s the approach that Stockholm has taken, more or less, while London, Singapore, and Milan created a smaller congestion zone within the larger boundaries of each city. Fix NYC’s boundaries run from 60th Street to the southern tip of Manhattan, with an exemption for drivers who use the FDR Drive without ever entering Manhattan’s grid south of 60th. Taxis and for-hire vehicles would be subject to charges anywhere south of 96th Street.

While these boundaries have some logic, they cover less than 5 percent of New York’s 300+ square miles. Pricing trips into the core of Manhattan will impact motorists from New Jersey, Westchester, Connecticut, and Long Island, but a larger zone that extends beyond Manhattan would also provide immediate benefits to the majority of bus passengers in New York City who are stuck in traffic beyond 60th Street in Manhattan. The larger zone would also help absorb growing automobile congestion as population and job growth continue at a faster pace outside of central Manhattan.  

Exemptions, by and large, are to be avoided. Several cities included exemptions for hybrid and electric cars, to encourage greener behavior. But the result of those good intentions in Stockholm, London, and Milan was a greater shift to exempted modes than anticipated, which reduced the congestion benefits of pricing. Stockholm initially provided an exemption for green vehicles, but as more motorists shifted to these vehicles and travel speeds reduced, decision-makers eliminated the exemption. London had a similar experience with its licensed-private-hire vehicle exemption. The number of these vehicles grew from just under 50,000 in 2009 to more than 87,000 by 2016. Much like what has happened in New York, this boom has been blamed for slowing down average travel speeds to pre-congestion pricing levels at just over 8 miles per hour.

What kinds of exemptions might New York end up with? Fix NYC only offered an exemption for the FDR Drive, but Governor Cuomo’s comments seem to indicate his willingness to entertain more exemptions for outer-borough and suburban travelers.

Finally, all recent attempts to implement congestion pricing in New York City have promised to dedicate new funds to support transit, which should be a no-brainer. The main caveat here is that the MTA might be the worst transit agency in the world when it comes to spending money judiciously on transit infrastructure.  

No policy is perfect from the outset. The clear lesson from Stockholm, Milan, Singapore, and London is that adjustments over time are critical. Closing exemptions, redrawing boundaries, incorporating new technology, and intervening when congestion creeps back up are vital to success. Each city has achieved some of its goals, but some have been faster to act than others. Stockholm has done an excellent job with adjustments as traffic dynamics change. London, on the other hand, has struggled to amend its policy as travel speed gains have eroded.

And even if a city does everything right, it’s possible that congestion will increase. Singapore introduced pricing, made adjustments to it, and complemented it by increasing the price of parking, vehicle registration fees, and fuel taxes. Despite that, the city’s congestion has continued to grow. And that’s a reflection of something bigger than just traffic: This is a city that provides opportunities for those searching for jobs, housing, and amenities; as in New York, Singapore’s pile-up of people is the product of its success. This “congestion noodle,” to paraphrase architect and critic Michael Sorkin, is about finding a way to nurture the traffic that allows cities to thrive while moderating the traffic that saps them of their vitality.

Governor Cuomo is right that congestion pricing is a policy whose time has arrived. But as New York’s elected officials continue to cobble together politically painless and practically useless solutions, the fight over Fix NYC has galvanized advocates and decision-makers who remain committed to its implementation. Even if 2018 isn’t the year, congestion pricing has arrived, and that means it won’t go away.

Guest post by Jeff Mosenkis of Innovations for Poverty Action.

Above: Some lessons from Rachel Glennerster on policy vs. academic research paths

• Nick Kristof talks with Amanda Glassman at the Center for Global Development about trying to get the world’s attention to alleviation of poverty and suffering. (FYI there are a number of tools that will let you covert youtube videos to audio MP3 to listen to like podcasts).
• A nice pair of short podcasts with Alice Evans and David Evans (who are unrelated but apparently share the massive enthusiasm gene). The first is on the World Development Report and what we know about education, and the second on how one uses RCTs to test an idea. David brings up an important nuance in the difference between an efficacy (does the program work at all under ideal conditions?), vs effectiveness (does it work as implemented in the practical world?) trial, and how one’s inferences from each might differ. (Apple podcasts).
• The slides above are from  a very good talk Rachel Glennerster gave at the Oxford Centre for the Study of African Economies conference about how to do policy work from an economics perspective, and the difference between academic and policy uses of the economist’s toolkit.
  • She gave a several nice examples of how to think about abstracting the mechanisms behind particular findings to general principles, using vaccines as an example. Unvaccinated kids: If families never start vaccines, the problem might be access (look at price or other barriers). If they start their series of scheduled vaccines but don’t complete them, a social/behavioral solution like incentives or other nudge might be appropriate.
• Agenda here (scroll down for the descriptions), videos here, and a roundup on Dev Impact Blog, by Goldstein and Evans, summarizing a ton of papers in single bullet points with links (114 by my count), sorted by sector.
• It’s hard to escape the irony of a bunch of Americans (and others) flying to England to talk about African economies, but the Centre does have a two-month fellowship for scholars from any African country.
• The majority of $4 billion of U.S. philanthropic grants made to African universities between 2003 and 2013 went to institutions in English-speaking countries (h/t John Branch). But even politically minded academics aren’t immune to this bias – over 20 years the majority of published papers in two journals specifically about African politics focus on politics of English-speaking countries.
• Two really interesting articles via Rachel Strohm:
  • “Vanilla hustlers” of Madagascar. How a vanilla boom has brought wealth, but also a lot of danger there. It was eerily reminiscent of the paper suggesting that the boom in demand for citrus following its discovery as a cure for scurvy in the 1800’s fueled Sicilian organized crime. (NPR’s The Indicator econ podcast goes into the details of the latter).
  •  A group of female attorneys in the DRC who specialize in fighting domestic violence.

Going back to Rachel’s and David’s point on types of RCTs, it’s important to remember that even though we use the same language to talk about outcomes (“vaccination rates”) or inputs (“vocational training”), that doesn’t mean they’re actually identical.

The post IPA’s weekly links appeared first on Chris Blattman.

Every 90 days I lie in a whirling CT machine, dye coursing through my veins, and the doctors look to see whether the tumors in my liver are growing. If they are not, the doctors smile and schedule another scan. The rhythm has been the same since my doctors told me I had stage IV colon cancer two and a half years ago. ...

What does the suffering person really want? How can you navigate the waters left churning in the wake of tragedy? I find that the people least likely to know the answer to these questions can be lumped into three categories: minimizers, teachers and solvers.

The minimizers are those who think I shouldn’t be so upset because the significance of my illness is relative. These people are very easy to spot because most of their sentences begin with “Well, at least ….” Minimizers often want to make sure that suffering people are truly deserving before doling out compassion. ...

Some people minimize spiritually by reminding me that cosmically, death isn’t the ultimate end. “It doesn’t matter, in the end, whether we are here or ‘there.’ It’s all the same,” said a woman in the prime of her youth. She emailed this message to me with a lot of praying-hand emoticons. I am a professor at a Christian seminary, so a lot of Christians like to remind me that heaven is my true home, which makes me want to ask them if they would like to go home before me. Maybe now?

Atheists can be equally bossy by demanding that I immediately give up any search for meaning. One told me that my faith was holding me hostage to an inscrutable God, that I should let go of this theological guesswork and realize that we are living in a neutral universe. But the message is the same: Stop complaining and accept the world as it is.

The second exhausting type of response comes from the teachers, who focus on how this experience is supposed to be an education in mind, body and spirit. ...

The hardest lessons come from the solutions people, who are already a little disappointed that I am not saving myself. There is always a nutritional supplement, Bible verse or mental process I have not adequately tried. ...

A tragedy is like a fault line. A life is split into a before and an after, and most of the time, the before was better. Few people will let you admit that out loud. Sometimes those who love you best will skip that first horrible step of saying: “I’m sorry. I’m so sorry this is happening to you.” Hope may prevent them from acknowledging how much has already been lost. But acknowledgment is also a mercy. It can be a smile or a simple “Oh, hon, what a year you’ve had.” It does not ask anything from me but makes a little space for me to stand there in that moment. Without it, I often feel like I am starring in a reality program about a woman who gets cancer and is very cheerful about it.

After acknowledgment must come love. This part is tricky because when friends and acquaintances begin pouring out praise, it can sound a little too much like a eulogy. I’ve had more than one kindly letter written about me in the past tense, when I need to be told who I might yet become.

But the impulse to offer encouragement is a perfect one. There is tremendous power in touch, in gifts and in affirmations when everything you knew about yourself might not be true anymore. I am a professor, but will I ever teach again? I’m a mom, but for how long? A friend knits me socks and another drops off cookies, and still another writes a funny email or takes me to a concert. These seemingly small efforts are anchors that hold me to the present, that keep me from floating away on thoughts of an unknown future. They say to me, like my sister Maria did on one very bad day: “Yes, the world is changed, dear heart, but do not be afraid. You are loved, you are loved. You will not disappear. I am here.”
--Kate Bowler, NYT, on just loving

Is artificial intelligence the future for economic development? Earlier this month, a group of World Bank staff, academic researchers, and technology company representatives convened at a conference in San Francisco to discuss new advances in artificial intelligence. One of the takeaways for Bank staff was how AI technologies might be useful for Bank operations and clients. Below you’ll find a full round-up of all the papers and research-in-progress that was presented. All slides that were shared publicly are linked here, as well as papers or other relevant sites.

Keynotes

• Tom Kalil: the Bank will need staff who are familiar with both development and computer science, who understand the technology developments coming from computer science and can turn them into development knowledge and action. He (and many other speakers) emphasized the need for more high quality micro datasets, to train AI algorithms.
• Joshua Blumenstock: machine learning (ML) is particularly promising in data scarce environments (e.g. many of the Bank’s client countries). ML opens the possibility of using new data sources to measure poverty and vulnerability, and could be trained to predict changes in welfare, which could improve project targeting, facilitate crisis response, and create new approaches to impact evaluation (slides).
• Susan Athey spoke on the potential uses of AI for causal inference. ML has primarily been used for prediction and there is little literature on the use of ML for causality. While ML won’t solve identification problems, it certainly helps when data is scarce, and can help systemize the search for optimal model specification. All materials (slides, videos, r scripts and a github data link) from Susan’s AEA course with Guido Imbens on the same topic are available publicly here.

AI for Governance

• Big data to increase trust? In Brazil, researchers used a Mixed Initiative Social Media Analysis (MIXMA) to study the relationship between social protest and citizen trust based on sentiment analysis of twitter activity during the 2014 World Cup (N Calderon et al paper, slides)
• In a study of policy options to reduce criminality among ex-combatants in Colombia, a ML ensemble was used to improve the credibility of propensity score matching by allowing for inclusion of 100+ control variables (best technical explanation we heard: “unleash the statistical zoo”) (C Samii, L Paler, & SZ Daly paper, slides)
• Big data to improve government performance? In India, ML algorithms on tax data can more systematically identify ‘suspicious’ firms to target for physical audits (A Mahajan link)
• To quantitatively analyze qualitative deliberation in Indian village assemblies, the Social Observatory used text-as-data through unsupervised natural language processing. Data shows that women are less likely to speak and the issues they raise are less likely to be picked up by others (Parthasarathy et al paper)

AI for Transport & Urbanization

• Use nighttime lights data to ‘train’ for better classification of urban areas in daytime satellite images (Landsat). Better data on the pace and extent of urbanization could improve infrastructure development, industrial policy, environmental planning, and land management (Goldblatt et al paper, slides)
• The HumNet lab is generating urban demand models using mobile phone data. One of many promising applications is to better manage demand and reduce pressure on infrastructure during large events like the Olympics (Gonzalez & Xu, slides)
• By crowdsourcing location updates through smart phones, Mapbox created models to predict how and when people evacuate during disasters (Farley details, slides)

AI Lightning Talks

• Most data on violence is self-reported, under-reported and not available at disaggregated levels. Computer vision algorithms help identify and label destroyed areas in Syria (Hersh, contact)
• ML to predict the likelihood of farmers adopting the use of lime (On, contact)
• Using AI provide personalized agricultural extension information at low cost through interactive voice response, improved by rapid a/b testing. (Reich, Precision Agriculture for Development)
• ML to predict food security in southern Malawi (Knippenberg, paper)
• Sentiment analysis of news has real signal for economic forecasting (Fraiberger, paper)
• Facebook using satellite-based data and government census information to map global population (Nayak, Facebook)
• Improve Educate Girl’s targeting of out-of-school girls in India, by using random forest regressions to predict likely out-of-school girls based on government data (Brockman, IDinsight)
• Use big data to reduce gender gaps in access to credit, use ML algorithms to predict credit worthiness rather than credit history (which women are less likely to have) and allow for different predictors for men and women (Higgins, details)
• Natural language interfaces (e.g. chatbots) to help low-income people navigate complex bureaucracies (Kendall, Digital Financial Services Lab)
• Use ML on satellite imagery to detect changes in horizontal and vertical growth of cities (Clough, Planet Labs)
• Machine learning should complement, not substitute for, development practitioners. Practitioners are critical for identifying the problem to solve, providing local expertise, and contextualizing analysis. (Paul, USAID Global Development Lab) 
• Introduction to an AI-based social robot scientist for automating impact evaluations, tailored to Ghanaian policy makers (Opoku-Agyemang, contact)

AI for Tracking Poverty, Targeting Development

• Satellite imagery data provides a less expensive and scalable method to estimate consumption expenditure and assets (a convolutional neural network trained to identify image features explains up to 75% of variation in economic outcomes). In 5 African countries, performance of satellite models is tested against ground-truth survey data, for outcomes such as maize yields, poverty and access to electricity. (Burke, paper)
• Man vs. machine? A test of 3 methods to predict likelihood of being a successful entrepreneur in Nigeria – expert judges, models developed by economists, and ML algorithms – showed that ML does not obviously out-perform the other methods (Mckenzie & Sansone, paper, slides)
• Current models of predicting credit worthiness have had limited success. A ML algorithm using data on how people use their mobile phones (5500 indicators such as top-up patterns, usage and mobility) is predictive of loan repayment and can be used as an alternative to credit scores, and therefore could be used to extend credit to the unbanked (Bjorkegren, paper)
• Researchers at Berkeley are working on a new initiative to leverage data-rich environments, such as the US, to build ML models and then systematically degrade the data to mimic data-poor contexts. (Hsiang, paper)
• Deep learning models are used to recognize objects from Google street view; the objects are then used to infer socioeconomic outcomes. In this case, cars (separated by make and model) were identified and used to create measures of safety, segregation, and “greenness” (Gebru, slides, paper)
• Descartes Labs is assessing food security in the Middle East and North Africa, through an automated capability to analyze, monitor and forecast the wheat crop, which will allow for real-time alerts and insights (Moody, details).  

The ethics of AI for development
A panel composed of Florence Kondylis (World Bank), Moorea Brega (Premise), Stefano Ermon (Stanford), and Aubra Anthony (USAID) discussed ethical issues and raised the following concerns:

1. Informed consent? Social science worries a lot about making sure human subjects know what they’re being ‘subjected’ to, but in the case of AI participation is not voluntary.
2. Transparency? Incentives for transparency are well-established in academic computer science. However, for tech start-ups, ‘algorithms are the new oil’ and are typically proprietary. Yet knowing what’s in an algorithm is important for establishing trust. If transparency won’t happen on its own, what type of intervention is needed?
3. Privacy? AI presents new twists to concerns over personally identified data, such as ‘demographically identified data’, which need to be carefully considered.
4. Is the ‘ground-truth’ true? Survey data has its own sources of error and bias, which need to be considered when it is used to train ML models.

I’m always on the lookout for how people try to signal high status.

Here’s a subtle example I’ve discovered recently. Tell someone a fact they don’t know, and listen for the answer: “That doesn’t surprise me.”

The other day I told a guy who’s well connected in tech: “Did you know that Joe had a falling out with his cofounder, and so he has moved on to a new project?”

The other guy’s reply: “That doesn’t surprise me.”

The alternative answer would have been: “Huh, I didn’t know that.” By saying “That doesn’t surprise me,” he conveyed that he did not, in fact, know the thing that was just said to him, but rather than stop there — which would have lowered his status relative to me in that moment — he simultaneously conveyed the fact that he would have guessed the fact to be the case had he been asked. All done in one tidy sentence.

As another example, Donald Trump’s first quoted response to the Harvey Weinstein news was: “I’m not surprised.”

Signaling status in this way is not necessarily good or bad or even that important. It’s fun to notice it. And, sometimes, it can be a useful data point as you build psychological models of how the people around you operate, and in particular, as you predict how status-oriented a person might be.

A friend emailed me the below excerpt from Mark Nepo’s The Book of Awakening. The closer we get to the core of all being, the more synonymous the effort and its reward.

---

So often we anticipate a reward for the uncovering of truth. For effort, we expect money and recognition. For sacrifice and kindness, we secretly expect acceptance and love. For honesty, we expect justice. Yet as we all know the life of experience unfolds with a logic all its own. And very often, effort is seen, and kindness is embraced, and the risk of truth is held as the foundation of how humans relate. However, the reward for breathing is not applause but air, and the reward for climbing is not a promotion but new sight, and the reward for kindness is not being seen as kind, but the electricity of giving that keeps us alive.

It seems the closer we get to the core of all being, the more synonymous the effort and its reward. Who could have guessed? The reward for uncovering the truth is the experience of honest being. The reward for understanding is the peace of knowing. The reward for loving is being the carrier of love. It all becomes elusively simple. The river’s sole purpose is to carry water, and as the force of the water deepens and widens the riverbed, the river fulfills its purpose more. Likewise, the riverbed of the heart is worn open over time to carry what is living.

All this tells us that no amount of thinking can eliminate the wonder and pain of living. No wall or avoidance or denial – no cause or excuse – can keep the rawness of life from running through us. While this may at times seem devastating, it is actually reassuring, because while the impermanence of life, if fixed on, can be terrifying, leaving us preoccupied with death, the very same impermanence, if allowed its infinite frame, can soothe us with the understanding that even the deepest pain will pass.

Note: Data & Society is reposting this call for a Director of Research with one significant revision. The role was originally scoped as a permanent member of the staff. Instead, the Director of Research will hold a rotating, three-year role at Data & Society while taking leave from their home institution.

Data & Society advances public understanding of the social and cultural implications of data-centric technologies and automation. We conduct interdisciplinary research and build a field of actors to ensure that knowledge guides development and governance of technology.  We are working towards a future in which the values that shape technology should be visible and intentionally chosen with respect for human dignity.

Data & Society is looking for an exceptional candidate to lead our growing, interdisciplinary Research Team as the Director of Research (DoR). The DoR is a new, senior, and central role at Data & Society. The ideal candidate will be passionate about the power of evidence and research to drive impact. They will be an accomplished scholar and a dedicated academic mentor, with deep team management experience. Data & Society’s DoR will bring their own disciplinary and topical expertise to the team, but will be capable and comfortable developing and supporting research across a range of themes, disciplines, and topics.

This crucial role in Data & Society will work closely with danah boyd, Founder and President, to envision, articulate, and manage towards a broader research vision.  The DoR will be responsible for ensuring the rigor, quality, and value of our research outputs, and for strengthening the research culture at the organization. They will also be encouraged to maintain and build their own research agenda and publishing practice, and to build or expand a profile as a public intellectual in their own right.

The Director of Research is a rotational, three-year role at Data & Society. We expect the DoR to take leave from their home institution during their time at D&S, although they may retain some responsibilities.

Responsibilities

Research:

• Develop and implement overall research strategy for the organization, working closely with founder/president, executive director, and research-oriented advisors, with an eye to impact on evolving field debates.
• Ensure quality of Data & Society research outputs, including implementing a rigorous and transparent review process that includes a range of scholars.
• Maintain an active profile as a researcher and scholar.

Public outreach:

• Represent Data & Society’s work externally to media, funders, civil society, industry, and government as needed.
• With support from other D&S teams and resources, ensure that researchers are able to represent their work in multiple venues and to multiple audiences.

Mentorship:

• Build the research culture at Data & Society. With support from the Managing Director of Research, the DoR will lead the development of policies, norms, best practices, and research infrastructure geared to produce rigorous, frame-breaking, and timely research products.
• Mentor D&S scholars, both directly and by developing mentorship norms and structures that leverage the broader Data & Society network.
• Incorporate faculty fellows into the research team for discrete periods of time.
• With an eye to field building, enhance and sustain the network of researchers whom we work with in academia and beyond.

Management:

• Serve as the senior leader of our in-house research team of approximately 25 people, including initiative leads, researchers, research analysts, and post-doctoral scholars.
• Directly supervise research initiative leads to develop and implement research strategy within thematic verticals.
• Collaborate with Managing Director of Research and other directors and managers at Data & Society on finance/budget oversight, administration, human resources, communications, programs, and publishing.
• Serve on the Managers’ Team at Data & Society, representing research culture and concerns within organizational leadership.
• Share in fundraising and funder relations responsibilities for the research team with executive director, founder/president, and individual researchers.

Qualifications:

• PhD in the social sciences or related field and experience with qualitative sociotechnical research;
• 10+ years academic or research work experience post-PhD;
• Extensive academic and non-academic publication history;
• Extensive professional experience in university or institute research environments;
• Experience in research team building and management;
• Public profile and ability to connect with non-academic audiences via writing and speaking;
• Expertise in the social and cultural implications of data-centric and automated technologies;
• Deep understanding of the public and closed-door debates occurring in media, government, the technology industry, and civil society around the issues raised by data-centric and automated technologies, and a clear set of ideas of the ways in which research can influence and shape those decision-making venues.
• Strong interpersonal skills and demonstrated experience managing down, laterally, and up for successful outcomes.
• Comfort with a fast-paced work environment at a young and rapidly evolving organization.

Practical Considerations:

1. This is not a remote position; you must work full time from the Data & Society office in the Flatiron section of New York City, however this role does allow for some flexible scheduling and telecommuting;
2. As this is a rotational position, we expect the successful candidate to maintain a relationship with their home institution and, in some cases, retain some institutional responsibilities. This will be considered on a case-by-case basis.
3. Annual salary is commensurate based on experience, and you will be offered a generous benefits package, paid time off, and a budget for business travel and projects. Additionally, we are able to provide relocation assistance if necessary.
4. You must be eligible to work in the United States; we are unable to sponsor visas.

 

To apply, please submit the following to jobs@datasociety.net:

1. Cover letter explaining your interest in this role, who referred you or how you learned about this opportunity, and why you would be the ideal candidate for this position;
2. Your Curriculum Vitae;
3. Names, affiliations, and contract information for three professional references.

 

Applications will be reviewed on a rolling basis, and the position should be considered open until filled. Please contact jobs@datasociety.net with any questions about the position; inquiries will not be held against your eligibility as a candidate.

A groundbreaking event to be held on April 24 2018 at The Urban Innovation Centre in Clerkenwell, London. The event is organized by NewCities in partnership with Mistra Urban Futures and Future Cities Catapult, with the participation of Spacehive, Project for Public Spaces, Living Space Project, and the Young Foundation.

NewCities and its partners will bring together the policymakers from more than 20 cities alongside 100 of the most insightful actors in community development, planning, design, real estate, technology, social innovation, and finance. Through interactive workshops, panel presentations and high-level discussions, the gathering will define the emerging tools within civic crowdfunding and crowdsourcing and their capacity in grassroots, public, and private use-cases as a formal tool for developing and enhancing civic spaces and community assets.

The interactive day-long discussion will:

• Emphasize civic environment as a latent resource for public, private, and local development stakeholders; Highlight concrete civic crowdfunding initiatives from around the world;
• Explore crowd urbanism as an emerging tool for ‘sensing the city’ with the potential to fill in the gaps between big-ticket items in profit-driven development;
• Connect stakeholders and the non-traditional actors that should be involved in the future development and implementation of crowd urbanism projects;
• Determine and define the necessary tools and potential in mainstreaming the use of crowd urbanism for private developers, urban designers, city planners, philanthropy, and the smart-city industry.

To request an invitation for this event, please contact us at contact@newcities.org.

Download the Program
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Photo © WMBstudio

The post Crowdsourcing the City appeared first on NewCities.

Imagine the future where Hyperloops take people between cities, clothing gives us superhuman skills, virtual reality is the new textbook, machines start thinking as humans and smartphones are redundant.

 The Internet of Things, mobile applications and various other digital tools are weaved into our daily life and almost practically every sector and industry.

 For instance, services offered by cities

 Be it smart street lamps, smart carts or smart public transport, local governments around the world are increasingly leveraging digital technologies to offer citizens an easier, healthier and safer lifestyle.

In fact, cities are now the innovation hubs of the world where new products and policies are experimented every day.

But only a small proportion of the world’s population is actually contributing to these innovation hubs. Cities are surely populated with intelligent people but they are missing “smart” citizens.

And by smart, I don’t mean people with high IQs.

By smart, I mean people who can be entrepreneurial and creatively design solutions to solve local and global challenges and contribute to build prosperous and inclusive cities.

I joined the NewCities Foundation earlier this month and as each day goes by, I realise how my current and former worlds are tightly intertwined.

So, what is the key to raise a creative and wise generation for our new cities?

It is education.

I don’t mean introducing technology into the fabric of the education system.  Nor do I mean that we should all learn to code.

 On the contrary, we need to reap the benefits of ubiquitous connectivity without becoming its slave.

For centuries, our schools and libraries were guardians of knowledge. Learners travelled miles to rote learn content with immense focus on “what” and “when”.

  But today, when information is abundant and free, finding out the “what” and “when” is a cakewalk or should I say a “click-walk”.

 Now the “how” matters much more, especially as we dive deeper in the post-truth world.

Education means much more than developing a rich vocabulary or mastering science and mathematics.

 Education in the 21st century is about asking the right questions. It’s about developing skills such as critical thinking and deductive reasoning to decipher facts from false beliefs. Education is about being creative and to find concrete solutions to real world problems.

 And this type of education must start at an early age. In fact, as kids we are all creative and curious (remember the endless series of “why” questions?).

 But as we climb up the education ladder, these innate qualities become dormant.

Competition overpowers creativity, rote learning suppresses critical thinking while communication and collaboration take a back seat as each one of us learns to live and work in our individual bubble.

So, what needs to change?

More Collaboration, Less Competition: To combat the rise of the robots, the world needs problem solvers with strong human values and soft skills such as empathy and listening. For acclaimed journalist and author Paul Tough, cultivating self-control and perseverance is not just “nice”. It enables children to do well in subjects like math and reading. In his book How Children Succeed (2012), Tough stresses that children under-perform in school partly because they lack non-cognitive skills like focusing while reading a long passage or perseverance while trying to solve a complicated equation.

1. Smash the STEM-only mindset: Once upon a time, mathematics, science and engineering graduates were considered to be the creators and innovators of the world. Companies ferociously competed to recruit the best data scientists, and business intelligence engineers in the industry. But with automation on the rise, we need to reengage with the Humanities. We need to raise a generation of innovative problem-solvers to address local and global challenges. In fact, many global business leaders such as Jack MA of Alibaba or Susan Wojcicki of YouTube hold degrees in Humanities.

2. Skills for a Purpose:  Moreover, six in ten millennials look for a sense of purpose in their work. They are keen to contribute to society in a one way or another but lack the means and the skills to do so. Learners need to be taught skills that correlate to their real world – at home, at work and in society at large. We need more programs such as Finland’s Me and My City that offers young children a glimpse of the real world through hands-on and project-based learning. Similarly, initiatives such as High Tech High, Big Picture Learning or the Studio Schools are encouraging children to discover their entrepreneurial and innovative mindsets, with our without technology.

3. Real-world and Lifelong Learning: And while we focus on the youth, let us not forget the working-age and the retired population. While MOOCs such as Coursera and ALISON help professionals to upgrade their skills, we need more initiatives like Japan’s Silver Human Resource Center that reintegrate retirees into the workforce and in society.

4. Citizenship: Most importantly, we must take civic education off the backburner. In our fragmented world, civic virtues are key. Citizenship education is vital to build vibrant democracies, to equip learners with tolerance and openness and at the same time maintain one’s identity and culture in a globalized world. For instance, LoYAC (Lothan Youth Achievement Center) in Kuwait that creates opportunities for young people to do community service and internships.

And like many, I wonder about the role of technology in developing a smart citizen. Well, it’s a means, and not an end. And that end is to raise a generation of happy, creative, resilient citizens of inclusive, connected, healthy and vibrant cities

“What is a smart city? It’s a connected city. But that connection doesn’t always have to be about the technology”  Timothy Turrito, GM, Government at Microsoft said at a recent voice.

And indeed, for me, that connection is knowledge.

This post was originally published in Forbes.

The post How To Raise A Wise Generation For New Cities appeared first on NewCities.

By Danielle Burr, Head of Federal Affairs

Alongside government officials, citizens, and the rest of the business community, we understand how important the role of government policy and funding is to the maintenance and modernization of America’s transportation infrastructure.

These are the principles that inform our thinking and some of the actions we hope officials consider when they work to improve and maintain world-class transportation infrastructure.

Principle #1) Fix It First

Uber advocates for an infrastructure initiative that focuses on the basics — ensuring that ‘low tech’ road infrastructure is maintained at a world class level. Preserving a good state of repair of America’s roads, coupled with replacement and expansion projects, is important for the efficiency of ridesharing and is crucial to the rollout out of Uber’s self-driving vehicles and freight products. Carefully maintained lane striping, road signage, and general maintenance — like filled potholes — are critical since these are ultimately how self-driving vehicles ‘see’ roads and infrastructure. These basic steps are necessary for economic productivity and highway safety for everyone today, but also represent an investment in the future of transportation.

Principle #2) Invest in Public Transit Infrastructure and Expand Public-Private Partnerships

In many communities, mass transit is the backbone of their transportation systems. Increased investment in public transportation is needed to give more people access to affordable transportation while helping to reduce congestion and pollution. To maximize the return on this investment and give communities more flexibility to develop their own tailored transportation solutions, Uber supports a modern regulatory framework that facilitates stronger collaboration between public agencies and private entities. Uber advocates for expansion, flexibility, and increased funding for the Federal Transit Administration’s Mobility on Demand program, which promotes innovation and cross-cutting multimodal services. This will ultimately lead to improved mobility for all communities, especially where commuters have limited transit options.

Principle #3) Promote Shared Rides

Infrastructure legislation should further advance policies that incentivize shared rides and help alleviate gridlock and reduce pollution. Shared rides are also an efficient way to extend the reach of existing mass transit infrastructure. Variable road pricing models, carpooling, and robust mass transit systems are proven modern-day solutions to reduce traffic congestion, facilitate economic opportunity, and improve the quality of living in our communities. Simple provisions in federal legislation could further encourage these pilots and policies at the local level.

Principle #4) Embrace the Future

The transition to new, cutting-edge transportation technologies has the potential to bring transformative economic, safety, and social benefits to our communities. The burgeoning self-driving, electrification, and vertical-takeoff and landing (VTOL) vehicle technologies will usher in a new transportation landscape and help make our communities safer, cleaner, more efficient, and more affordable. Government officials have an opportunity to play a pivotal role in the acceleration of those gains. Empowering pilot programs that plan for the future and promoting safe operational research that utilizes real world testing will help bring the tremendous safety and mobility benefits of these technologies to the public sooner.

Uber’s CEO says moving past private car ownership will benefit the economy and the environment

By Dara Khosrowshahi, Chief Executive Officer

For the first time in many decades, urban transportation is in the midst of rapid change. For many, change can’t come fast enough.

Today’s transportation system, both in the U.S. and increasingly around the world, places personal car ownership at its core. That comes at a high cost. Cities spend billions of dollars on parking spaces, using valuable resources and real estate that could be transformed into housing or office space. In the U.S., we waste seven billion hours a year sitting in traffic. Not only does traffic affect productivity, but also emissions from idling cars make up more than 20% of our total carbon footprint.

This is the transportation landscape in which ride-sharing services like Uber were created, and in just a few years, we’ve begun to witness the transformative impact that ride-sharing can have. By turning personal cars into shared vehicles, services like ours have been able to bring on-demand transportation and an alternative to car ownership to new neighborhoods and populations in large cities, and, increasingly, to smaller towns and even rural areas.

And we’re just getting started. Today, ride-sharing accounts for less than 1% of miles driven globally. By 2030, Morgan Stanley estimates, that number could rise to more than 25%.

Even while these changes take place, others are coming. It’s no secret that self-driving cars will become a reality sooner than anyone may have expected. It’s still very early days, so we expect that the transition will require a hybrid approach for some time. Since self-driving cars will initially be unable to travel along certain tricky routes, handle difficult weather conditions or meet periods of peak demand, we expect that we’ll see a mix of human-driven vehicles alongside self-driving ones for years to come.

But we also know that research has shown that self-driving technology could drastically improve the way we get around, while improving road safety. However, for their benefits to be widely distributed, we strongly believe that self-driving cars must be shared, rather than individually owned and operated. A system of individually owned, self-driving vehicles could replicate — and possibly even exacerbate — our existing transportation challenges.

Ultimately, we understand the goal of reducing private car ownership is one we share with cities across the globe. That’s one reason we work with partners in government around the world. Whether it’s connecting our service with vital mass-transit systems, partnering on deploying electric charging infrastructure or providing data on Uber trips to transportation planners, we’re excited by the steps we’ve already taken in this direction.

We know we can do more, and we will. Technology on its own is not a solution for urban problems — but done right, and in partnership with others, we believe shared mobility has the potential to contribute to a better world for all.

As seen in the Wall Street Journal

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Dara Khosrowshahi on the Power of Shared Mobility was originally published in Uber Under the Hood on Medium, where people are continuing the conversation by highlighting and responding to this story.

by Rik Williams, Data Scientist, Policy Research & Economics, and Nadia Anderson, Manager, Public Policy, Road & Traffic Safety

Ride-hailing apps like Uber have tremendous potential as an alternative to drinking and driving, and anecdotally already help people avoid getting behind the wheel after consuming alcohol. Studies on the broader impacts are not yet conclusive, but our qualitative research with MADD indicates a shift in mindsets about drinking and driving, while trip data support the notion that ridesharing is used during nights and weekends and in close proximity to events and establishments where alcohol is readily available.

Uber continues to explore the ways in which people use ridesharing as a transportation mode during these at-risk times and in certain locations. The following illustrates one way we’re thinking about this very important question: a data-driven analysis demonstrating that Uber is being used in these times and places, and is available as an option to help people make the safe choice — the choice not to drink and drive.

The findings presented here highlight the complexity of this issue and demonstrate how far we have to go to make drinking and driving a thing of the past. We’re committed to being a part of the solution and will continue to work with the research, enforcement and advocacy communities to get to zero.

A Tale of Two Cities : Salem, OR and San Francisco, CA

Salem, Oregon

Salem, the state capital of Oregon, is a mid-sized city (metro area population of 400,000) about an hour’s drive south of Portland. It’s also one of Uber’s newest markets: we launched service there in June 2017.

The downtown area consists of state government offices alongside a bustling commercial center with a large urban mall and numerous quaint coffee shops, restaurants, and boutiques. Beyond downtown, the city and its adjacent suburbs are almost exclusively single-family homes.

Salem’s public transit options are somewhat limited. The Cherriots bus service covers most of the main corridors, but daily service ceases before 10pm (and doesn’t run on weekends or holidays). In the past, if you went out at night to a bar or restaurant and had a few drinks, your options for getting home were limited. Public transportation was sometimes an option, but depending on the hour you may have had to call a taxi or phone a friend.

This all changed in June 2017 when Salem residents were introduced to another reliable, affordable option: Uber. In similar cities, we’ve seen that people do in fact use Uber to get around when public transit service is infrequent — but to better understand Uber as an alternative to drinking and driving we wanted to dig deeper. How have Salem residents actually been using Uber since its launch, especially during times when other options for travel may not be readily available?

To investigate this, we looked at Uber’s trip data in combination with public records. The State of Oregon makes data about establishments that serve alcohol for consumption on premises (including bars, restaurants, brewpubs, and wineries) publicly available, and the map below shows the locations of 298 such establishments in the Salem area (denoted by the blue dots).

Using these locations, we counted the number of Uber trips which started during late weekend nights (10pm-2am Friday and Saturday) within 500 feet of these establishments, and compared them to the total number of Uber pickups during those same hours in the Salem area (grey box).

The results are striking. In the last half of 2017 — essentially the first six months Uber operated in Salem — over 59% of Uber’s late night trips started within 500 feet of an alcohol-serving business. In other words, thousands of Salem residents immediately began using Uber as a way to travel during peak nightlife hours from venues where alcohol is consumed.

The rapid adoption of Uber as a late-night option is encouraging — but what is the story in a city where ride-hailing has been available for years?

San Francisco, California

The San Francisco Bay Area, home of Uber’s headquarters and the first city where Uber service was available, stands in sharp contrast to Salem in many ways. It’s a metropolitan area of nearly 5 million people anchored by the densely-populated 7-by-7 mile San Francisco city proper, which is served by multiple rail lines, 24-hour bus service, and a grid of bicycle- and pedestrian-friendly streets.

Uber has been available in San Francisco since 2010, growing to millions of active unique riders and tens of thousands of drivers in the Bay Area. Once requested through Uber, a vehicle typically shows up within 3–5 minutes — and therefore is considered a reliable transportation mode throughout the city. The below image shows how long it takes on average from requesting a vehicle through Uber to its arrival at the pick-up point. The darker green hexagons are under 3 minutes; as you can see, the vast majority of wait times are within the 3–5 minute range.

Between public transportation, taxi, Uber, Lyft, and other services, San Francisco residents have numerous safe ways to get around, day or night. Even so, in 2017, the San Francisco Police Department conducted 285 arrests for driving under the influence of alcohol or drugs; tragically, 30 of these incidents resulted in injury. As shown on the map below, every one of these arrests happened in an area where the typical ride through Uber was less than 5 minutes away.

Be a #DesignatedRider

San Francisco and Salem differ in many ways, but together they demonstrate the complexity of this issue and the importance of ongoing and dynamic public engagement and research. In addition to making sure options like public transit, ridesharing and other modes of travel are readily available, the data demonstrate the need to continue building awareness and education around the dangers of drinking and driving.

We hope to see more studies examining the relationship between alternate travel modes, new and innovative countermeasures and education and awareness campaigns on alcohol-impaired driving prevention. And in the interim, whether in Salem, San Francisco, or anywhere else, we’ll continue to encourage everyone to take a ride on the safe side and choose to be a #DesignatedRider.

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Creating Designated Riders: A Tale of Two Cities was originally published in Uber Under the Hood on Medium, where people are continuing the conversation by highlighting and responding to this story.

How, exactly, should policymakers respond to the rapid rise of new private mobility services such as ride-hailing, dockless shared bicycles, and microtransit? As I argued here several months ago, in order to answer that question city leaders will need accurate and detailed information about all urban trips—however the traveler chose to get from one place to another. And that information needs to come in part from the private mobility companies that are moving a growing share of people within our cities.  

In 2017, these services had a tumultuous year. Apocalyptic images of discarded dockless bikes in China left American officials that are experimenting with this model for bikesharing scrambling to ensure their cities avoid the same fate. Meanwhile, Uber’s admission that it paid a $100,000 ransom to hackers who stole 57 million user accounts damaged that company’s credibility as a protector of passenger privacy. And a widely shared study from researchers at University of California-Davis refuted several optimistic hypotheses about ride-hailing’s societal benefits: It found that companies like Uber and Lyft are spurring urban congestion, siphoning public transit riders, and failing to entice many people to give up their cars. Not coincidentally, transit agencies like Washington, D.C.’s WMATA are now launching their own investigations to see if declining ridership can be traced to the emergence of ride-hailing.

Beyond these broad issues, there are a number of specific questions that can’t be answered without access to trip information from Uber, Lyft, Limebike, and the like. For example, without such data it’s hard for policymakers—or the general public—to decide if it’s a good idea to convert a parking meter to a ride-hailing drop-off point, or to ensure pedestrians aren’t obstructed by heaps of dockless bikeshare bikes on the sidewalk. Unfortunately, new mobility services have generally refused to let the public sector see inside their data vaults.

But the tide is turning, especially as the line between public and private forms of urban transportation blurs. American transit agencies are partnering with ride-hailing companies to offer late-night service, move people to bus or rail stations (“first mile/last mile” solutions), and manage paratransit for riders with limited mobility. Ride-hailing companies are in an awkward position if they refuse to share data with governments that subsidize them. “If I’m paying you to move a passenger, the data for that passenger isn’t yours,” I heard a Texas transit official say recently to a ride-hailing executive. “It’s mine.” The executive had no response.

When will policymakers finally be able to access the data they need to manage streets and sidewalks in the public interest, and how will they get it? The most likely solution is via a data exchange that anonymizes rider data and gives public experts (and perhaps academic and private ones too) the ability to answer policy questions.

This idea is starting to catch on. The World Bank’s OpenTraffic project, founded in 2016, initially developed ways to aggregate traffic information derived from commercial fleets. A handful of private companies like Grab and Easy Taxi pledged their support when OpenTraffic launched. This fall, the project become part of SharedStreets, a collaboration between the National Association of City Transportation Officials (NACTO), the World Resources Institute, and the OECD's International Transport Forum to pilot new ways of collecting and sharing a variety of public and private transport data. Kevin Webb, the founder of SharedStreets, envisions a future where both cities and private companies can utilize SharedStreets to solve questions on topics like street safety, curb use, and congestion.

That’s a laudable goal, but Shared Streets will have to solve several challenges in order to become a go-to resource. For example, it’s hard to provide a complete picture of urban mobility unless the heavyweights like Uber, Lyft, Didi Chuxing, Ofo, and Mobike participate; so far none of them has signed on. There is also the question of how tech behemoths like Google and Apple—collectors of massive datasets about individuals’ movement—can be involved. Perhaps they can be sources of reliable revenue that SharedStreets will need in order to scale (at present the initiative is being incubated with philanthropic support).

Finally, there is the critical question of privacy. Although Uber’s hacking scandal has dinged ride-hailing’s credibility as a protector of passenger data, new mobility services do have a point when they push back against handing over rider information to the government. It’s reasonable to assume that at least some customers will balk at the prospect of public agencies accessing their personal ride histories.

Webb says that SharedStreets will handle those concerns by collecting aggregated data that is rich enough to allow for deep analysis while still hiding information about individual rides. New mobility service companies could further protect their passengers by converting trip data into so-called “synthetic populations” of artificial data modeled after trips that people actually took.   

However the new mobility service data arrives—almost certainly aggregated, and potentially artificially modeled—there will need to be a way to ensure it is accurate. After all, companies like Uber and Lyft have a vested interest in the questions policymakers pose about their impact on city streets. Data validation—especially for modeled data—is crucial for such an exchange to be trusted.

There are many questions yet to resolve, but the movement to give city officials reliable and accessible trip data is gaining momentum. Indeed, it’s hard to see how the elusive ideal of a “smart city” is attainable without shared set of facts about how people are moving within an urban area. In addition to SharedStreets, a number of universities, startups, and major tech companies are quietly developing strategies to plug this gap in our civic knowledge. Most of those efforts aren’t public yet, but I expect several to launch in 2018. For those of us who believe in data-driven management of streets and sidewalks, that’s something to be excited about—and to push for.

Inequality is one of the main challenges posed by the proliferation of artificial intelligence (AI) and other forms of worker-replacing technological progress. This paper provides a taxonomy of the associated economic issues: First, we discuss the general conditions under which new technologies such as AI may lead to a Pareto improvement. Secondly, we delineate the two main channels through which inequality is affected - the surplus arising to innovators and redistributions arising from factor price changes. Third, we provide several simple economic models to describe how policy can counter these effects, even in the case of a "singularity" where machines come to dominate human labor. Under plausible conditions, non-distortionary taxation can be levied to compensate those who otherwise might lose. Fourth, we describe the two main channels through which technological progress may lead to technological unemployment - via efficiency wage effects and as a transitional phenomenon. Lastly, we speculate on how technologies to create super-human levels of intelligence may affect inequality and on how to save humanity from the Malthusian destiny that may ensue.

Corporate Social Responsibility (CSR) has become a cornerstone of modern business practice, developing from a "why" in the 1960s to a "must" today. Early empirical evidence on both the demand and supply sides has largely confirmed CSR's efficacy. This paper combines theory with a large-scale natural field experiment to connect CSR to an important but often neglected behavior: employee misconduct and shirking. Through employing more than 3000 workers, we find that our usage of CSR increases employee misbehavior - 20% more employees act detrimentally toward our firm by shirking on their primary job duty when we introduce CSR. Complementary treatments suggest that "moral licensing" is at work, in that the "doing good" nature of CSR induces workers to misbehave on another dimension that hurts the firm. In this way, our data highlight a potential dark cloud of CSR, and serve to forewarn that such business practices should not be blindly applied.

Driver’s diary. “When you’re driving a yellow cab and you don’t have any other irons in the fire — an easy jam to find yourself in, when the game compels you to drive for twelve hours a day, six or seven days a week — you make your peace with every part of your job that’s a pain in the ass, because, at the end of your shift, all you want to do is switch off your brain and collapse, and you lack the creative impulse to imagine a different strategy. Along comes Uber, and it’s imagined for you”

“Reconciling different points of view can be difficult and time-consuming. It is up to the meeting leader to balance conflicting perspectives. A common question I get is: What happens when someone inexperienced offers an opinion? If you’re running the conversation, you should be weighing the potential cost in the time that it takes to explore their opinion versus the potential gain in being able to assess their thinking and gain a better understanding of what they’re like”

In praise of a writer distinguished but also limited by her self-control. “St Joan has always alluded to great feelings, even great passions, but never in a way that threatens to disrupt her prose. No hysteria draws undue attention to individual paragraphs; no menstrual blood stains her ‘action verb, action verb’ diction, as she refers to her literary style. With its newly found appreciation for female self-possession, cinema finally may be ready to embrace this woman’s novels and essays”

There are two ways into the ruling elite — merit and brilliance. You make a show of working hard (merit); or you make a show of not working hard (brilliance). “The Merit Culture’s tropes are quantitative research, evidence, credentials, and detail. The Culture of Brilliance believes that success is a matter of personal and spontaneous genius. It values felicitious answers, quick responses, and narrative excitement. Too much work is a tell of mediocrity”