Marian.panganiban

Melody Kramer is one of the smartest, most thoughtful people I know in journalism. She has a new post up at Poynter talking about ways to design the news that take into account that news can be overwhelming.

People take breaks, go on vacations, have stretches where they can’t keep up, work weird hours, have different levels of interest and background knowledge, and so forth — but they still want to be informed, connected, and engaged.

How can we deal with that? Here’s one good idea:

We should allow people to check out or pause and return. I envision a website where someone can say how long they’d like to be away from the news and what kinds of news they’d like when they return. This could most easily be accomplished through newsletters. For example, a landing page might allow a user to say: “I am taking [XX] [days / weeks / months] off. When I come back, I’d like to be updated on [topics] on [this frequency.]”

Years ago, some of us called this “my time” or “TiVo time”: a personalized, time-shifted attention economy. (Actually, I don’t think anybody called it “TiVo time” but me. And maybe a few guys who worked for TiVo.)

And for a little while, say around 2000-2010, media consumption in the form of DVRs, IM chats, blogging (and commenting), RSS feeds, Netflix DVDs (by mail!), was sort of unconsciously driven by this principle. It was available in close-to-real-time, but you could dip in and out of the stream much more easily.

Then a lot of factors — including short-form social media, livestream video, Netflix bingeing, a resurgence of TV events, and maybe especially always-available mobile devices — pushed us back to a much more immediate and real-time immersion in media. This hasn’t always been to everyone’s benefit. Not all consumers’, and not all producers’ either.

Choosing between plunging in or checking out has become a much more all-or-nothing proposition. It doesn’t have to be that way. We know this. We already built a lot of the tech that lets us manage this. Now we just have to figure out the best ways to deploy it.

Tags: attention   Melody Kramer   news   time

Even amid the chaos seen across the nation’s airports since President Donald Trump’s executive order on Muslim immigration, Mohammad Abu Khadra’s story stands out.

Mohammad, a 16-year-old who lives in Katy, Texas, just west of Houston, was detained when he flew into Houston’s George Bush Intercontinental Airport from abroad on Saturday, the Houston Chronicle reports. Mohammad was traveling on a visa; he had returned to Jordan to renew his passport. Upon arriving in the States, he got caught in the dragnet that has snared some visa-holding residents from seven Muslim-majority nations since Friday night.

Except Jordan isn’t one of the seven nations named on the consequential executive order. In fact, on Monday, King Abdullah II of Jordan became the first Arab leader to hold talks with President Trump. Meanwhile, authorities still haven’t released Mohammad, who attends classes at Katy High School. On Monday evening, after more than 48 hours in detention at the airport in Houston, Mohammad was transferred to Chicago, where he is being detained at a shelter under the Office of Refugee Resettlement, part of the U.S. Department of Health and Human Services.

[UPDATE 2/1: The local NBC affiliate reports that Mohammad was traveling on a tourist visa when he was detained.]

Ali Zakaria, an immigration lawyer who showed up at the airport in Houston on Friday to assist travelers affected by the executive order, says that it’s common for adolescent refugees to be transferred to separate detention facilities that are set up for children. But Mohammad’s case is exceptional. He is not a refugee, for starters. Also, Houston has a refugee resettlement camp able to accommodate children.

“We’re not sure why this kid was not sent to the facility in Houston,” Zakaria says. “We’re also not sure why this kid was held at the airport for 48 hours.”

Zakaria says that he hopes to see Mohammad released within the next two weeks. U.S. Immigration and Customs Enforcement will file the notice to appear in immigration court and “take whatever action they deem in this matter based on whatever the problem is with the kid’s visa,” Zakaria says. He has yet to see that charge sheet.

“Our first priority at this stage is to get him released, and get him united with his family,” Zakaria says. Mohammad has an older brother, Rami, a green-card holder living in Katy, per the Chronicle; the American Civil Liberties Union, which is working with immigrants and visa holders from countries named under the executive order, connected the brother with the attorney.

A 16-year-old’s detention at a federal facility in Chicago might be a matter of improper paperwork or mistaken identity under other circumstances. But Mohammad’s case exposes significant challenges associated with the executive order, Zakaria says. Whether or not by design, confusion is a feature of the travel ban.

No one in Houston knew it was happening, for starters. “It’s not the practice of [U.S. Customs and Border Protection] to inform the city,” says Kris Banks, a special assistant to the mayor’s office in Houston. “We for instance didn’t know how many people had been detained over the course of the weekend.”

Local officials would not have jurisdiction in a federal immigration case, of course. But no one in the mayor’s office in Chicago knew, either, that a Houston resident was being detained there, a spokesperson said on the phone. And Mohammad has no access to a cell phone.  

Zakaria says that he is unaware of any other Jordanian visa holders being detained. But he notes that airlines are already refusing passengers from citizens of the seven countries named in the executive order, even though, for visa holders, their legal status is subject to case-by-case interpretation, for now. Chaos in the rollout, Zakaria says, is strengthening the order as a ban.

It would be an alternative fact to say that it’s not a Muslim ban,” Zakaria says. “My personal observation, by being at the airport for Sunday and Monday, and from talking to clients and a lot of other attorneys, is that Muslims who are not even citizens of these seven countries are being pulled from the line and are being put in secondary inspection areas and are having to wait three to nine hours.”

Zakaria adds, “Of course I think this case has everything to do with the executive order issued by Trump.”

UPDATE: This post has been updated with new information.

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It might be impossible to avoid all bumps, scratches, and bone-jarring accidents while traversing the big city, but your chances of arriving unscathed are better when you ride the bus rather than drive a car.

That’s the conclusion of researchers studying injuries along major traffic corridors in Montreal. By perusing police reports from 2001 to 2010, they found motorists on these routes had more than three times the injury rate of bus passengers. Buses were also safer for people sharing the road. Cars were responsible for 95 percent of pedestrian and 96 percent of cyclist injuries on these arteries, they write in a presentation for this month’s meeting of the Transportation Research Board.

During the same time period in Montreal, nobody was killed while riding the bus, though 668 people were injured. (It’s unknown if that number includes bus operators, who are powerful magnets for abuse.) Meanwhile, auto occupants suffered 19 deaths and 10,892 injuries. Cars were linked to 42 pedestrian and three cyclist deaths, while buses were linked to four and zero, respectively.

The researchers don’t drill down into the hows and whys of these discrepancies. But their work backs up, on the city level, what’s been known for some time on the macro scale. In the United States car occupants have a fatality rate 23 times greater than bus passengers, while it’s respectively 11 and 10 times higher in Australia and Europe. They suggest getting more people on public transit could make a large impact on public health. Here’s more from their full presentation:

We estimated that a 50% modal shift from car toward bus would prevent 35% of all injuries and 38% of severe injuries. The benefits may be underestimated, because we did not take into account the effect of having fewer vehicles on the road, the risk reduction—for all road users—associated with a reduction in traffic volume. However, the benefits may also be overestimated, because a modal shift towards public transit would likely increase the number of pedestrians and which is associated with an increase in pedestrian casualties or in the overall number of road casualties. It is worth mentioning that in Canada’s large metropolitan areas, transit access points are concentrated at intersections of wide major roads with the greatest rate of crashes and pedestrian injuries. To offset an increase in pedestrian exposure to crashes, a large reduction in traffic volume and the area-wide implementation of traffic calming measures and safer pedestrian crossings might be needed.

Now that self-driving cars have moved beyond mere speculation and are roaming the streets of Pittsburgh, among other places, federal and local officials are busily trying to figure out how to regulate them.

During a recent conference in Washington, D.C., Paul Lewis, vice-president of policy and finance at the Eno Center for Transportation, talked about how local and regional governments can lead the way in this mobility revolution. What’s needed, he said, are policies “that both protect public safety and bring some accountability to this rapidly changing environment while still enabling the technology to bring the benefits.” But, as December’s spat between San Francisco authorities and Uber’s self-driving fleet indicates, the regulatory road ahead could be a rocky one.

The National Highway Traffic Safety Administration has published a 15-point safety assessment that laid out some early autonomous vehicle (AV) guidelines. But many more questions await. For example, who’s liable—the driver, the manufacturer, or the other vehicle’s operator—when a self-driving vehicle fails to negotiate a scenario to which it doesn’t know how to react?

Truly fully-automated vehicles may not be common for another 10, 20, or even 50 years, but cities need to prepare now.

“In the past, where technology has been pushed too fast, too far, and negative reaction has happened, either the Congress or public vote ends up putting that technology in the box for a very long time,” said panelist Nat Beuse, a NHTSA administrator. That means, above all, figuring out the kind of collaboration needed between governments and the private sector. He also emphasized the need to prove that AVs are safe not on a test track but out on public roads.

Two philosophy professors at Carnegie Mellon University over in Pittsburgh have a novel idea about how to do that: In an op-ed published Thursday in IEEE Intelligent Systems, they suggested that AV regulations should mirror the U.S. drug approval process.

Alex J. London and David Danks, who also study machine learning, say that the problem with applying current auto safety guidelines to AVs is that they have a binary view: Either the product works and gets rolled out en masse or it doesn’t. It’s a relatively straightforward process to test whether a vehicle’s braking system, for example, performs well enough to meet safety standards. But for self-driving cars, the important factor is whether the vehicle knows if it should hit the brakes. What’s lacking is a set of dynamic standards to assure the public that the vehicle can appropriately distinguish what to do in different scenarios.

“The more you're relying on [the vehicle’s] decision-making in an unconstrained environment, where context can change rapidly and where there may be noisy signals, validating that may have to be more like the way we validate pharmaceuticals—by relying more on trial and error,” says London, who studies the ethics of technology and medicine.

So they recommend testing AVs out in phases, first testing out the vehicles in simulated environments that provide a series of “unforeseen” situations—the “pre-clinical trials,” if you will. When the vehicle’s decision-making process is deemed sufficient in a range of contexts, it can be slowly rolled out in selective settings in the real world, closely watched by drivers and monitors with special training. As each “trial” is declared successful, regulators can gradually grant companies permission to expand the testing into different roads and eventually different cities.

Companies like Google and Uber have been doing a limited amount of testing on public roads, but London calls for more coordination with the federal government. “Some groups would have a van that would just deliver packages in Pittsburgh, but consumers aren't going to want to buy a car that they can only drive in [one city],” says London. “So what are the places that are sufficiently similar to Pittsburgh that the car would also do well in, and what are the places that are sufficiently different that we need to validate the car's ability to drive there. Those are questions that should be sharpened.”

So rather than having individual companies vet the process, federal regulators would used the data shared with them to establish what an “acceptable performance” entails before moving on to the next phase—how many hours of driving in the city does it takes, for example, or how many accidents are tolerable. Over time, market restrictions can be relaxed as the system is refined.

As with introducing potentially dangerous new medications, such a pathway to the marketplace would require a heavy hand with the regulation. This could be a problem. We appear to be entering a radically deregulated federal era—the new presidential administration has pledged to roll back standards governing drug safety, the environment, financial misbehavior, and, well, everything. A methodical trial-and-error method also consumes a lot of time. But London says there’s another advantage to their vision: By rolling out AVs in phases rather than en masse, companies and policymakers can see how pedestrian behavior changes over time and adjust regulations accordingly.

“You try to diagnose what the failures were, and you extend the environment in which you are operating the vehicle,” he says. “Largely, this is experimental learning—you learn from failure.”

The post Criminal Politicians appeared first on Marginal REVOLUTION.

For his new book, Evolution: A Visual Record, photographer Robert Clark has collected dozens of images that show the varying ways in which plants and animals have adapted to their changing surroundings.

Evidence of evolution is everywhere. Through 200 revelatory images, award-winning photographer Robert Clark makes one of the most important foundations of science clear and exciting to everyone. Evolution: A Visual Record transports readers from the near-mystical (human ancestors) to the historic (the famous ‘finches’ Darwin collected on the Galapagos Islands that spurred his theory); the recently understood (the link between dinosaurs and modern birds) to the simply astonishing.

The photo above is of a southern cassowary, a flightless bird that is particularly dinosaur-esque in stature and appearance.

Tags: biology   evolution   photography   Robert Clark   science

Frank Harrell, author of an influential book on regression modeling and currently both a biostatistics professor and a statistician at the Food and Drug Administration, has started a blog. He sums up “some of his personal philosophy of statistics” here:

Statistics needs to be fully integrated into research; experimental design is all important

Don’t be afraid of using modern methods

Preserve all the information in the data; Avoid categorizing continuous variables and predicted values at all costs

Don’t assume that anything operates linearly

Account for model uncertainty and avoid it when possible by using subject matter knowledge

Use the bootstrap routinely

Make the sample size a random variable when possible

Use Bayesian methods whenever possible

Use excellent graphics, liberally

To be trustworthy research must be reproducible

All data manipulation and statistical analysis must be reproducible (one ramification being that I advise against the use of point and click software in most cases)

Harrell continues:

Statistics has multiple challenges today, which I [Harrell] break down into three major sources:

1. Statistics has been and continues to be taught in a traditional way, leading to statisticians believing that our historical approach to estimation, prediction, and inference was good enough.

2. Statisticians do not receive sufficient training in computer science and computational methods, too often leaving those areas to others who get so good at dealing with vast quantities of data that they assume they can be self-sufficient in statistical analysis and not seek involvement of statisticians. Many persons who analyze data do not have sufficient training in statistics.

3. Subject matter experts (e.g., clinical researchers and epidemiologists) try to avoid statistical complexity by “dumbing down” the problem using dichotomization, and statisticians, always trying to be helpful, fail to argue the case that dichotomization of continuous or ordinal variables is almost never an appropriate way to view or analyze data. Statisticians in general do not sufficiently involve themselves in measurement issues.

The post Frank Harrell statistics blog! appeared first on Statistical Modeling, Causal Inference, and Social Science.

Behavioral economics identifies myriad deviations from classical economic assumptions about consumer decision-making, but lacks evidence on how its diverse phenomena fit together and whether they are amenable to modeling as low-dimensional constructs. We pursue such parsimony on three fronts, with success on two and instructive failure on the third. Elicitation parsimony reduces impediments to data collection by streamlining standard methods for directly measuring a person's behavioral tendencies. We do so for 17 potentially behavioral factors per individual in a large, nationally representative sample, and several sets of results indicate that our streamlined elicitations yield low-cost, high-quality data. Behavioral sufficient statistic parsimony aggregates information across behavioral factors, within-person, to create two new lower-dimensional, consumer-level measures of behavioral tendencies. These statistics usefully capture cross-sectional variation in behavioral tendencies, strongly and negatively correlating with a rich index of financial condition even after (over-)controlling for demographics, classical risk attitudes and patience, cognitive skills including financial literacy, and survey effort. Our quest for common factor parsimony largely fails: within-consumer correlations between behavioral factors tend to be low, and the common factor contributing to all 17 behavioral factors within-individual is weakly identified and does not help explain outcomes conditional on the other covariates. Altogether our results provide many new insights into behavioral factors: their distributions, inter-relationships, distinctions from classical factors, and links to outcomes. Our findings also support the two leading approaches to modeling behavioral factors--considering them in relative isolation, and summarizing them with reduced-form sufficient statistics--and provide data and methods for honing both approaches.

That is the title of a new paper by Avi Goldfarb, Mara Lederman and myself.

In 1970, Albert Hirschman wrote a widely read book, Exit, Voice and Loyalty, whereby he noted that economists relied solely on a particular mechanism — exit — to think about how organisations that aren’t performing well are disciplined. Don’t like what you are buying, leave. He noted that political scientists seemed to be more predisposed to an alternative mechanism — voice –to discipline organisations. Don’t like what you are buying, complain. But while those notions were talked about following Hirschman, suffice it to say, economics at least has gone on regardless, continuing to pay scant attention to voice even if they themselves seem quite disposed to complaining pretty much constantly (well, amongst my circles anyway).

One of the constraints has been that it has been hard to measure voice. Exit can kind of be captured by market share or consumer churn data. But voice tends to be more obscure. To be sure, some people did study consumer boycotts but compared with the amount of voice actually being exercised, this was surely the tip of the iceberg. Fortunately for us, big data has come along — and by “big” I mean more data than can be held in a Excel spreadsheet.

Our big data comes from Twitter. We noted that people seemed to use Twitter to complain about airlines. This is certainly a big activity amongst economists but as it turned out if you looked in a year you could find millions of tweets directed at airlines in the US. We looked and wondered if this could be a measure of voice.

First of all, we wanted to make sure it wasn’t just noise. We could look at tweets and how they were phrased but our big task was to match the tweets with location and time data from airlines to see what particular airline markets the tweets were likely about. That was challenging but thanks to the data being big, we were able to do that. Moreover, we found that tweet volume was associated with data on airline delays so it seemed that it wasn’t all hot air.

Second, we were interested in how tweet volume related to competition. Hirschman had thought that voice was more likely to be exercised when consumers couldn’t really exit but then had wondered if that made sense because why would a firm who knew they had locked in consumers care about voice. We took a different approach and noted that as markets became less competitive, consumers could still exit but more importantly, if they did exit, that was a bigger loss for a firm precisely because they could earn more in the face of less competition. In other words, if a firm who had market power was actually going to care more about their relationship with their consumer and so would like to talk before separation. Consumers, knowing this, would exercise voice more as a result.

Our paper determined that was in fact the case. Controlling for delays, the tweet volume (including negative tweets) went up as concentration in the market rose. Moreover, we found evidence that airline responsiveness (i.e., replies to complaints) tracked this as well. Finally, we also determined that this was stronger when tweets gave us indications of a long-term relationship (i.e., “a platinum fantasic member I …”).

So we think Hirschman is back and is back because digitisation now provides us with a window into complaints. US airlines are one matter and we don’t know if the exercise of voice actually helps in terms of performance. But we think that voice might finally get the attention it deserves from economists.

Conan O’Brien was once the upstart of the late-night comedy world, a pretender to the throne hoping to one day rise to the level of luminaries like Jay Leno and David Letterman. Just a few years ago, O’Brien’s sense of humor was still viewed by NBC executives as too unusual and young-skewing, sparking fears that he couldn’t hold onto the broader, older audience of The Tonight Show. O’Brien’s brief 2010 tenure at The Tonight Show, and his abrupt replacement with the program’s previous host Leno, seems like a lifetime ago. In the intervening years, old hands like Leno, Letterman, Craig Ferguson, and Jon Stewart have all retired, and now O’Brien, the longest-tenured late-night host in the business, firmly occupies the middle of the road. So it’s no wonder Conan’s days suddenly seem numbered.

Last week, news broke that TBS, the basic-cable network that has hosted O’Brien’s nightly show Conan for the last six years, was planning to retool it as a weekly show, in the mold of the newer TBS hit Full Frontal with Samantha Bee. O’Brien has hosted a daily late-night talk show for 24 years now, with brief breaks as he moved from NBC’s Late Night to The Tonight Show, and then jumped to TBS after a bitter contract dispute over Leno’s re-hiring. O’Brien’s departure from a daily format would mark a real end of an era that has already begun to pass into memory, and would make Jimmy Kimmel the longest-running late-night host on the air.

But that change would also make a sad sort of sense. O’Brien is not a particularly buzzy host in the era of Jimmy Fallon, James Corden, Seth Meyers, and Trevor Noah. Yet his show is still a consistently funny one. It also provides space for the kind of offbeat sketch and stand-up comedy that’s no longer en vogue in late night, which would make the loss of Conan, as it exists now, tough to bear.

Conan is contracted by TBS through 2018, and since The Wrap reported that the network was planning to take it weekly, the TBS president Kevin Reilly tried to walk back the news, saying there were no plans “at this time” to change anything. “Conan remains an invaluable franchise, partner, and producer for our TBS brand and we’ll be in business with him for a long time,” Reilly said in a statement. “As the media landscape continues to evolve, Conan will continue to lead the evolution of what a talk show will be in the digital age.”

Though Reilly’s statement sounds like a dismissal, it’s not too dissimilar from what Turner Broadcasting’s chief executive John Martin told The Wrap—that TBS was going to retool the series, and that the weekly format would help O’Brien stand out in the way it has for Bee (and for other weekly hosts like HBO’s John Oliver). Reilly is just soft-pedaling the news by saying O’Brien will “lead the evolution” of the talk show in the digital age—and more recent news has suggested that “digital” will be the focus for TBS. “The definition of a television network in 10 years, what’s that going to mean?” the company’s president David Levy asked Variety in response to the reports. “Premium video content is what’s really important to Turner.”

O’Brien is pretty good at providing “premium video content” for the network. His YouTube channel has 4.6 million subscribers, millions more than his network rivals Seth Meyers or Stephen Colbert (though far fewer than viral-video standouts Jimmy Fallon and James Corden). His recurring feature “Clueless Gamer,” where he plays video games with his avuncular assistant Aaron Bleyaert and various celebrities, is enough of a standalone hit that it’s been picked up for its own series (which O’Brien will produce). The New York Post reported Monday that O’Brien was being courted by YouTube to be the face of its premium Red channel, though such a move likely wouldn’t happen for at least a year.

O’Brien’s future in the late-night business is as unclear as the future of the business itself.

For all his streaming prowess, O’Brien hasn’t been a major ratings factor in years. Recent Nielsen Live +3 numbers peg his viewing audience at 638,000 (Trevor Noah, a direct competitor since both their shows air at 11 p.m., gets 1.3 million at The Daily Show). O’Brien was brought over to TBS in 2010 to help establish a late-night brand for the network. With that accomplished, there may not be a reason to keep his show as a far more expensive daily production, when he can shift to some mix of a weekly show and online content (which is far cheaper to produce), or perhaps to a 30-minute episode format.

O’Brien represents the old guard of late night in more than just his years on the job, however. His show is still far ahead of his rivals in terms of promoting new voices in stand-up comedy. As Jesse David Fox noted at Vulture, Conan continues the tradition started by Johnny Carson at The Tonight Show of giving young stand-ups their shot at a nationwide audience. There were 41 such sets last year on O’Brien’s show. Meanwhile, Colbert’s Late Show had 16, Fallon’s Tonight Show 15, Corden and Meyers eight each, and Jimmy Kimmel only three—and all of those shows air more episodes a year than O’Brien’s. Cut back to a weekly format, and these chances for young comics would largely disappear, as a weekly Conan would have much less versatility in terms of what it could offer audiences.

Conan has tapped into viral comedy by promoting series like “Clueless Gamer” and airing whole weeks of episodes from far-flung locations like South Korea, Cuba, Germany, and Armenia. But O’Brien has also continued the noble brand of absurd sketch-comedy humor that he pioneered at Late Night in the ’90s (an influence that permeates every level of scripted comedy to this day, given that most young comedians grew up watching Conan). Only Late Night with Seth Meyers comes close to airing as many strange sketches as Conan, probably because its host, like O’Brien, is a Saturday Night Live alumnus.

Perhaps O’Brien would be best suited to moving on to YouTube or some other digital platform that’s in search of the legitimacy he gave TBS in 2010. The media (and late-night) landscape has evolved rapidly since then, but O’Brien has remained its most reliably hilarious host by sticking to his brand. Despite his long career, O’Brien is only 53; Leno and Letterman were both in their mid-60s when they called it quits. O’Brien’s future in this business is as unclear as the future of the business itself, but as Levy said, in 10 years, people may not care about networks. They will care about celebrity names, though, and there’s still no other comedian out there called Conan.

Uber has long had a somewhat rocky relationship with cities, from its most recent public spat with San Francisco authorities over testing autonomous vehicles to its feud with New York City planners over access to the company’s ridership data. But in what seems like a move calculated to mend ties, Uber has opened up that cherished trove of info to city planners, researchers, and (eventually) the public.

Just a peek, though.

Uber isn’t releasing all the data collected over the last six years the company has been in operation. But its new tool, Movement, lets cities in on traffic patterns based on millions of trips taken over time. (The data released is anonymous.) The tool, which is currently available in Boston, Manila, Sydney, and Washington, D.C., tracks how long it takes to get from one point to another, and how that changes depending on the time of the day, day of the week, and factors like road shutdowns or city-wide events. It also allows users to look at patterns over a period of time.

That’s only one of the many ways Andrew Salzberg, Uber’s head of transportation, imagines cities can take advantage of the tool. It’s all part of the company’s efforts to improve its relationship with cities: In fact, Salzberg says that creating the product involved collaborating with city planners to figure out what they need.

At a recent launch event in D.C., Uber product manager Jordan Gilbertson showed off what Movement could do by showing what gridlock looked like when D.C. shut down its entire metro system in March for emergency inspections. (Non-scientific answer: hellish!) He plugged in the specific date and time, and the program did the rest. Analysis showed that overall, travel time in the city increased by anywhere from 10 to 30 percent. Along entry points to major highways, it was as much as 50 percent.

That experience served as a reminder that ride-hailing services, despite what they sometimes seem to say, are no replacement for true mass transit. “There’s no way in any system that Uber and any sharing models can move as many people as rail trains can, and I think we’ve demonstrated that with the shutdown,” Salzberg told reporters afterward. “If you look at the data for that day, you get a dramatic increase in congestion when rail transit doesn’t run. That’s one reason we’re putting this data out there—to be helpful in policy arguments around how to use these [road] spaces effectively.”

It isn’t quite the highly coveted data that cities want from Uber and the like. New York City, along with other local governments, is more interested in knowing when and where passengers get picked and dropped off—what Mayor Bill de Blasio has demanded and Uber has refused to deliver, on grounds of privacy protection for its riders.

So if city governments aren’t getting what they want from this tool, can Movement still be useful for local planners? Yes and no.

“A lot of cities, especially New York City, are fighting to get a lot more data from Uber, and it’s kind of an act of contrition, in a way, allowing some of that data to be released,” says Tim Welch, an assistant professor of city and regional planning at Georgia Tech. “It can be useful, but the level of detail and the type of data isn’t something that’s not already used by planners through other data sources.” Uber’s set of data is aggregated through Traffic Analysis Zones, which Welch says is a common unit of geography and planning analysis already used by cities. So in terms of how much further Movement contributes to urban planners’ work, he doesn’t think “it moves it much.”

But Zak Accuardi at the Transit Center, a New York-based foundation, says that while the data might not be nuanced enough for cities, regional transportation planners could benefit from that additional layer of traffic information when determining how road projects or new public transportation initiatives might impact travel time from one part of the region to another. He calls it a positive first step for both the company and cities to foster a relationship around data-sharing. “It opens the door for productive conversation for cities and makes it possible for cities to approach Uber and say, ‘We know you have this platform, and here’s what we’d like to see on it.’”

But it’s worth remembering that Uber is releasing this data on its own terms and may continue to keep certain information out of the public eye. Welch also notes that Uber’s data covers only a small subset of commuters: those who own smartphones and those who use Uber. “Planners ought to be very concerned about the lower-mobility groups,” he says. “How is the lower-income person in a location not using Uber getting around? And what kind of conditions are they facing?”

Uber’s Salzberg says this is just the beginning. And the company’s new commitment to swapping traffic intel with metros isn’t just about PR: In the end, Uber itself also stands to benefit from such civic collaboration (as do with other ride-sharing companies that collect their own data). “We ultimately benefit from streets that move effectively and from decisions made based on data,” he says. “We all share the goal of putting more people into fewer cars.”

Many people care about how they are perceived by those around them. A number of recent field experiments in economics have found that such social image concerns can have powerful effects on a range of behaviors. In this paper, we first review this recent literature aimed at identifying social image concerns or social pressure. We then highlight and discuss two important areas that have been comparatively less well-explored in this literature: understanding social pressure, including the underlying mechanisms, and whether such pressure can be shaped or influenced.

A friend asked me this question and I decided to turn my long email into a blog post, to somehow justify the ridiculous amount of time I spent on the email. The big buyer beware warning here is that I haven’t been to Uganda in a few years, and I haven’t does touristy things since 2007. So my knowledge is out of date. Hopefully readers can add and subtract in the comments.

• I will begin with wildlife because that is one of the really unique and amazing aspects of East Africa. Safaris are tacky or cliche mostly to people who haven’t gone. I’ve seen them beguile even the most cynical people, including me.
• You absolutely must go to Bwindi Impenetrable Forest and do the gorilla tracking. This is an awesome tourist and conservation program, beloved by visitors as well as my conservationist and scientist friends who work there. And spending an hour with a gorilla troop is possibly one of the most memorable and amazing experiences of my life. This is partly because a silverback decided to try to intimidate me. There are few slots per day, since only three families are acclimatized to visits, and so you must book early and make this the center of your trip.
• The other safari options in Uganda are quite good, but not on the same level as Bwindi. This is partly because Uganda is very forested and you do not have the magnificent savannah of Kenya or Tanzania. You have to stick to the trails rather than roam at will or see afar. I would suggest going to the best places in the world, which are not far away: Masai Mara (Serengeti on the Tanzania side) or the Ngorongoro crater in Tanzania. (I almost wrote Tora Bora crater, which is when the US hunted and shelled Bin Laden for years. Not recommended).
• One place in Uganda you might consider is Kidepo Valley, up on the Sudanese border. Sometimes it is safe, sometimes it is not. I can’t speak for the moment, but if hotels are operating there, it is probably fine. This is probably one of the least visited parks in the world, because for so long it was cut off by the conflict in northern Uganda. I believe it’s ok now, but you should check. I went briefly, for about 20 minutes, when a small propeller plane I was flying in was diverted there during a storm. There were no hotels or development at the time, and not much of a runway. Scores of very surprised animals cleared the way for our landing. I have always wanted to go back for a proper visit.
• When it comes to game parks, I also love Kenya for some of it’s unique places, like Hell’s Gate, where there are no predators, so you can bike instead of drive.
• That said there are excellent parks in Uganda to go to, and they tend to be less touristed than Kenya, which I like.Murchison Falls includes a lot of hippo and crocodiles, and is beautiful. Queen Elizabeth park is close to Bwindi, and is remarkable for having lions sleeping in trees (the only place in the world apparently). For example, this from immediately underneath the tree, in our land cruiser:

• I really recommend driving yourself if you feel up to driving on the left (or, as in my case, are married to someone with a Ugandan driver’s license). This is easiest in small parks like those in Uganda, or Nakuru and Naivasha in Kenya (which I attempted and enjoyed). There is a big difference between being a passenger and learning to navigate yourself around giraffe and buffalo. Here, for example, is me and Jeannie in a parking lot, trying to figure out how to get past this hippo and into our car. They are fast and aggressive and we are trying to plot our next move.

Getting away from the safari parks, there are a few other highlights.

• Bushara Island Lodge is a little place with what I’d call luxury tents, on an island in a lake far in the southwest of Uganda. It’s owned by the Church of Uganda, and very close to Bwindi. Ten years ago it was one of the most peaceful little places I ever visited, and I relaxed and swam and canoed and read many books. For example:

• We also stayed on a little isolated lodge on a crater lake near Fort Portal, also not so far from Bwindi (or Queen Elizabeth park). It’s been ten years and also now seems to be a bit more developed, but well rated. We rented bikes from some random person and biked through the foothills of the Rwenzori mountains. They were the classic east Africa bikes made from steel, nonexistent brakes, no gears, and looking like something from 1920, and my hands were bruised from all the bumps for about a week. It was great.
• I imagine you can also do trekking in the Rwenzori mountains but we never tried. A lot of people trek Mount Kenya. I personally am not a mountaineer. I like hiking flat or hilly surfaces or climbing vertical surfaces but things in between aren’t my thing.
• I never did the whitewater rafting on the Nile. I was not impressed with the safety record, and frankly figured I could do world class rafting in a lot of places if I really wanted to. I’d rather spend my time in East Africa doing what can’t easily be done elsewhere.
• For instance, if you do broaden the trip to East Africa at large, some of the coastal towns and islands are terrific. Lamu and Zanzibar come to mind, though they might have become more touristed since I was there. (My last big Kenya/Tanzania tourism stint was shortly after someone tried to blow up an Israeli passenger plane in Kenya, so I had nearly every place to myself.)
• Hiking the waterfalls around Sipi in eastern Uganda was nice but nothing special. If you lived in Kampala I’d say it’s a great weekend trip but not worth going around the world to see.
• What about Kampala? I loved my stays there, but find it hard to recommend the city to a short term tourist. If it weren’t for the traffic it would be a nice place to live (and was) but there’s not much to see. I didn’t discover a great music scene (possibly my failing) and I never toured the historical sites to do with the historical Buganda kingdom, and those could be interesting. But I think the best site burned down and I’m not sure what’s left. 
• I personally love economic and political tourism. My work mostly involves figuring out how different businesses work, or how different political systems work. I don’t really know how to do this as a tourist. but if you’re biking around the countryside (in my Rwenzori example above) then stop and ask people to show you their farms. Or talk to people in the markets about business and how it works.
• Finally I always suggest avoiding any slum or refugee/displacement camp tourism. I don’t think there are many opportunities in Uganda. But I have sick memories of crowds, sometimes busloads, of tourists and church groups on day tours of displacement camps in Uganda after the war. Some “slum tours” have redeeming features (graffiti tours in Medellin come to mind) but these are the exception.

Culturally I will give a few recommendations:

• Get someone to teach you to play Omweso, a traditional Ugandan board game. It’s a lot of fun. You’ll see the boards around.
• See if someone will take you to their church on Sunday, especially if it has lively singing. This is a really important part of life and can be really enjoyable. Of course some are also four hours long and hot and miserable. You never know what you’re going to get.
• Book-wise, I always liked the novel Abyssinian Chronicles by Moses Isegawa. But there are surprisingly few Ugandan authors compared to Kenya or Ethiopia. Even though I’m not a big fan of President Museveni, I did enjoy his war memoir, Sowing the Mustard Seed.
• I really wish public intellectual Andrew Mwenda would write a book about development. It’s hard to point to an article that captures his charm, cleverness and playfulness. You should pick up his magazine The Independent. Here is his TED talk. Here is his blog, which is very Uganda specific. He is best on radio.
• For food, Ugandan cuisine is fairly simple but I really love it.
  • In south/central parts of the country, any local fish in the groundnut (peanut) sauce, with matoke (mashed plantain) is probably excellent.
  • I always loved northern food the most, though it’s hard it find outside the north (maybe around Murchison). This includes greens or other vegetables stewed in sim sim (sesame) paste or groundnut sauce.
  • The beans and chapati are always good, and I like to eat with fresh avocado chopped in.
  • Season everything with the only seasonings available: salt and (if you ask for it) piri-piri (little red peppers that some restaurants keep in the back for such requests).
  • I also love the street food, including the guys on the main highway. My only gastrointestinal problems have come from restaurants. Street favorites include goat skewers, grilled maize, samosas, or rolex (chapati rolled with eggs, onion and tomato).
  • If you’re there in grasshopper or termite or white ant season, the fried bugs are actually super delicious. And I say this as someone who would not normally eat a fried bug. Finally, once you have the small sweet bananas of Uganda (only about 4 inches long) you will never enjoy a US banana again.
• No Ugandan I know thinks restaurant food is any good compared to home cooking. If someone invites you to their home, accept.

The post Where should you visit in Uganda as a tourist? appeared first on Chris Blattman.

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From Berlin to Cairo, from Medellín to New York City, new start-ups are flourishing in the heart of the city instead of occupying suburban areas or remote technology parks. This is the new model of start-up innovation ecosystems propelled by the so-called “fourth industrial revolution.”

Are these city-based start-up ecosystems generating new economic opportunities and jobs? If so, how are they doing it? To better understand this new model and its potential economic impact, we studied the evolution of the start-up ecosystem in New York City. 

The city’s vibrant start-up scene is a recent phenomenon. With more than 14,500 start-ups and nearly $6 billion in venture capital investments, New York City today has one of the largest and most vibrant start-up ecosystems in the world. Just 10 years ago, the start-up community in the city was small, scattered, and disorganized.

The incredible transformation of the city’s start-up scene provides a few key insights on the characteristics and potential impact of the urban ecosystem model:

• Urban ecosystems can create new business and foster growth. For this to happen, the ecosystem needs to be linked to the local industry base. In New York City, for example, the ecosystem evolved around finance, advertising and fashion. This process not only allowed the ecosystem to retain a specialized workforce, but it also increased the competitiveness and level of innovation of the city’s more traditional industry base. As more and more start-ups emerged, market competition forced local industries to innovate directly, either by introducing open innovation processes with start-ups or by absorbing new technology through start-up acquisition or recruitment.
• Urban ecosystems can generate “new” jobs, as opposed to “old” jobs that are being replaced by technology. These new jobs are the jobs of the future, emerging from new business models propelled from start-ups and innovation. Start-ups create some new jobs themselves. However, the majority of new jobs come from traditional industries that have introduced technology in their processes due to competitive pressures from new business models generated by start-ups or innovation absorption from the start-up ecosystem (as explained above). In New York, traditional industries generated three times more of the “new jobs” (i.e., tech employment) than start-ups themselves, serving as multipliers of “new jobs” catalyzed by the start-ups. Interestingly enough, these new jobs include both low- and high-skilled tech workers in similar proportions, allowing for equal-opportunity growth.
• Urban ecosystems can attract resources for local innovation. As the start-up ecosystem grows, it attracts out-of-the-city “innovation leaders” — for example, R&D institutions and innovation leading companies. This reinforces the innovation process of the ecosystem, further diversifying the local economy and providing another source for competitiveness. In New York, once the ecosystem reached maturity, the city attracted R&D, innovation, and product development functions from leading tech companies from outside the city — for instance, Google, Facebook and IBM.
• Urban ecosystems can transform urban environments. Start-up support infrastructure (such as co-working spaces, accelerators and incubators) and entrepreneurs’ communities can change the economic and social dynamics of entire neighborhoods. In New York City, the startup scene helped revitalize several areas in Manhattan and, most noticeably, Brooklyn. Propelled by start-up activity, formerly depressed neighborhoods like DUMBO have become centers of economic growth and social life.

The New York case also provides interesting insights on how policymakers can support the growth and sustainability of urban start-up ecosystems. To read more about this topic, click here for the full study, “New York City: Transforming a City into a Tech Innovation Leader.”

 

Collaborating with a number of different people from all over the place, filmmaker Oscar Boyson went out into the world and came back with this excellent 18-minute video on the future of cities. Among the cities profiles are Shenzhen, Detroit, Singapore, NYC, Copenhagen, Seoul, Lagos, and Mumbai.

What does “the future of cities” mean? To much of the developing world, it might be as simple as aspiring to having your own toilet, rather than sharing one with over 100 people. To a family in Detroit, it could mean having non-toxic drinking water. For planners and mayors, it’s about a lot of things — sustainability, economy, inclusivity, and resilience. Most of us can hope we can spend a little less time on our commutes to work and a little more time with our families. For a rich white dude up in a 50th floor penthouse, “the future of cities” might mean zipping around in a flying car while a robot jerks you off and a drone delivers your pizza. For many companies, the future of cities is simply about business and money, presented to us as buzzwords like “smart city” and “the city of tomorrow.”

A few tidbits from the video to whet your appetite:

• An estimated 70% of the world’s population will live in urban areas by 2050. (It’s currently 54%.)
• Buying a Toyota Corolla in Singapore costs $140,000.
• In 2012, 52% of the cost of US highways and roads was paid by general tax revenue rather than by drivers (through gas tax and tolls). In 1972, it was only 30%, which means car usage is much more heavily subsidized than it used to be.
• When you buy a car in Denmark, you pay a 150% tax, even if it’s electric.
• And a relevant quote from Jane Jacobs’ The Death and Life of Great American Cities: “Lowly, unpurposeful, and random as they may appear, sidewalk contacts are the small change from which a city’s wealth of public life may grow.”

And boy, listening to Janette Sadik-Khan talk about cities being for people and the importance of public transportation and then, directly after, having to listen to some dipshit from Uber was tough. (via @mathowie)

Tags: architecture   cars   cities   Jane Jacobs   Oscar Boyson   video

I participated at an interesting panel at an antitrust conference in Brussels today. I was about big data and whether it will be a problem for competition policy. This is something that has been widely discussed but there is little resolution on the issue.

When it comes to the potential problems that arise from big data, the focus is usually on two things. First, data is an asset and so are naturally concerned if such assets become concentrated in terms of ownership. Second, that concentration may be at the level of the individual (e.g., data about their behaviour) and that can make it difficult for individuals to switch between suppliers. Both of these may give rise to anti-competitive effects. However, we are really ahead of the game in these concerns. We do not really know which data is significant. And we do not really know which data is replicable (i.e., where substitute services can easily be provided).

In reality, a better place to focus at the moment is on the technologies that will make the data valuable for it is not of value on its own. You need technologies to clean it up and make it useful. And the uses are well known. You can use it to make better products (e.g., suggested Gmail responses, Siri etc). You can use it to allow better value capture through price discrimination (with the usual trade-offs that entails). But what has concerned myself (in discussion with my colleagues Ajay Agrawal and Avi Goldfarb), is that these technologies may be used to reduce competition per se.

How might this occur? Stepping back, as we have already written, machines can use data in dynamic settings and generate better predictions. For instance, machines could observe pricing outcomes and the profits of their firm and use it to find optimal pricing. The machines can also use pricing data to predict other pricing — a key step towards playing a game.

AIs have already learned to play complex games against themselves and humans (most recently, Go). But what if they learned to play pricing games? Imagine some large online retailers deploying pricing AI that learn to play pricing games (repeated ones) and engage in tacit collusion but in environments where this would be computationally impossible for humans. In fact, to make matters worse, imagine that the environments are so complex that no one can observe how they are doing it and the AI itself — as is common these days — can provide no “explanation.” The AI has just been told to maximise long-run profits and there is nothing wrong with that. But the key is that prices may be coordinated even though there is no agreement or even intention from a human. This would make it very difficult to prosecute under current laws.

We aren’t the only ones to have wondered about this. In their recent book, Virtual Competition, Ariel Ezrachi and Maurice Stucke raise similar concerns. I see such developments as inevitable (maybe in just a few years). Others at the conference were sceptical that machine learning would work with such a general objective and would need more specificity so the human complicity would be more clearly present. I guess we will see.

What might we do about it if the current law isn’t up to it? One of the best ways to counter price collusion is to provide consumers with the means of encouraging competitive entry that undercuts prices. The problem is that if consumers aren’t away of lower prices, that entry effect is muted. In this regard, the best defense against a bad AI is to have a good AI. That is, an AI who operates on behalf of consumers. We have seen this recently with adversarial machine learning whereby AI can be used to uncover the behaviour and predictions of other AI. The problem is that to do this consumers have to have access to the same information as competitors. That is, if a competitor allows other firms to access key data (through an API), they should be required to have such access open to all. It is asymmetry of access we should fear. I wouldn’t be as concerned if a firm just kept pricing and other data to themselves.

Admittedly, this is all speculative stuff. But that is the nature of these things. I am not in favour of pre-empting regulatory and competition battles when technology is uncertain. However, we can still be concerned about asymmetries that seem to favour firms over consumers and the area of data may be one place where we can pre-empt somewhat.

Yale history professor Timothy Snyder took to Facebook to share some lessons from 20th century about how to protect our liberal democracy from fascism and authoritarianism. Snyder has given his permission to republish the list, so I’ve reproduced it in its entirety here in case something happens to the original.

Americans are no wiser than the Europeans who saw democracy yield to fascism, Nazism, or communism. Our one advantage is that we might learn from their experience. Now is a good time to do so. Here are twenty lessons from the twentieth century, adapted to the circumstances of today.

1. Do not obey in advance. Much of the power of authoritarianism is freely given. In times like these, individuals think ahead about what a more repressive government will want, and then start to do it without being asked. You’ve already done this, haven’t you? Stop. Anticipatory obedience teaches authorities what is possible and accelerates unfreedom.

2. Defend an institution. Follow the courts or the media, or a court or a newspaper. Do not speak of “our institutions” unless you are making them yours by acting on their behalf. Institutions don’t protect themselves. They go down like dominoes unless each is defended from the beginning.

3. Recall professional ethics. When the leaders of state set a negative example, professional commitments to just practice become much more important. It is hard to break a rule-of-law state without lawyers, and it is hard to have show trials without judges.

4. When listening to politicians, distinguish certain words. Look out for the expansive use of “terrorism” and “extremism.” Be alive to the fatal notions of “exception” and “emergency.” Be angry about the treacherous use of patriotic vocabulary.

5. Be calm when the unthinkable arrives. When the terrorist attack comes, remember that all authoritarians at all times either await or plan such events in order to consolidate power. Think of the Reichstag fire. The sudden disaster that requires the end of the balance of power, the end of opposition parties, and so on, is the oldest trick in the Hitlerian book. Don’t fall for it.

6. Be kind to our language. Avoid pronouncing the phrases everyone else does. Think up your own way of speaking, even if only to convey that thing you think everyone is saying. (Don’t use the internet before bed. Charge your gadgets away from your bedroom, and read.) What to read? Perhaps “The Power of the Powerless” by V’aclav Havel, 1984 by George Orwell, The Captive Mind by Czeslaw Milosz, The Rebel by Albert Camus, The Origins of Totalitarianism by Hannah Arendt, or Nothing is True and Everything is Possible by Peter Pomerantsev.

7. Stand out. Someone has to. It is easy, in words and deeds, to follow along. It can feel strange to do or say something different. But without that unease, there is no freedom. And the moment you set an example, the spell of the status quo is broken, and others will follow.

8. Believe in truth. To abandon facts is to abandon freedom. If nothing is true, then no one can criticize power, because there is no basis upon which to do so. If nothing is true, then all is spectacle. The biggest wallet pays for the most blinding lights.

9. Investigate. Figure things out for yourself. Spend more time with long articles. Subsidize investigative journalism by subscribing to print media. Realize that some of what is on your screen is there to harm you. Bookmark PropOrNot or other sites that investigate foreign propaganda pushes.

10. Practice corporeal politics. Power wants your body softening in your chair and your emotions dissipating on the screen. Get outside. Put your body in unfamiliar places with unfamiliar people. Make new friends and march with them.

11. Make eye contact and small talk. This is not just polite. It is a way to stay in touch with your surroundings, break down unnecessary social barriers, and come to understand whom you should and should not trust. If we enter a culture of denunciation, you will want to know the psychological landscape of your daily life.

12. Take responsibility for the face of the world. Notice the swastikas and the other signs of hate. Do not look away and do not get used to them. Remove them yourself and set an example for others to do so.

13. Hinder the one-party state. The parties that took over states were once something else. They exploited a historical moment to make political life impossible for their rivals. Vote in local and state elections while you can.

14. Give regularly to good causes, if you can. Pick a charity and set up autopay. Then you will know that you have made a free choice that is supporting civil society helping others doing something good.

15. Establish a private life. Nastier rulers will use what they know about you to push you around. Scrub your computer of malware. Remember that email is skywriting. Consider using alternative forms of the internet, or simply using it less. Have personal exchanges in person. For the same reason, resolve any legal trouble. Authoritarianism works as a blackmail state, looking for the hook on which to hang you. Try not to have too many hooks.

16. Learn from others in other countries. Keep up your friendships abroad, or make new friends abroad. The present difficulties here are an element of a general trend. And no country is going to find a solution by itself. Make sure you and your family have passports.

17. Watch out for the paramilitaries. When the men with guns who have always claimed to be against the system start wearing uniforms and marching around with torches and pictures of a Leader, the end is nigh. When the pro-Leader paramilitary and the official police and military intermingle, the game is over.

18. Be reflective if you must be armed. If you carry a weapon in public service, God bless you and keep you. But know that evils of the past involved policemen and soldiers finding themselves, one day, doing irregular things. Be ready to say no. (If you do not know what this means, contact the United States Holocaust Memorial Museum and ask about training in professional ethics.)

19. Be as courageous as you can. If none of us is prepared to die for freedom, then all of us will die in unfreedom.

20. Be a patriot. The incoming president is not. Set a good example of what America means for the generations to come. They will need it.

A great thought-provoking list. “Corporeal politics”…I like that phrase. And I’ve seen many references to Hannah Arendt’s The Origins of Totalitarianism in recent weeks.

See also Five Steps to Tyranny and The 14 Features of Eternal Fascism.

Note: Illustration by the awesome Chris Piascik.

Tags: history   lists   politics   Timothy Snyder

Machine intelligence is a “prediction technology”, so it will tend to drive down the cost of goods and services that incorporate prediction — such as medical diagnosis. “The value of human prediction skills will decrease because machine prediction will provide a cheaper and better substitute. However, this does not spell doom for human jobs. That’s because the value of human judgment skills will increase. Judgment is a complement to prediction. We’ll want more human judgment”

Portrait of Daniel Kahneman and Amos Tversky, pioneers of behavioural economics and modern behavioural psychology. “In the beginning they were kicking around Danny’s proposition that people didn’t depend on probability or statistics. Whatever human beings did when presented with a problem that had a statistically correct answer, it wasn’t statistics. But how did you sell that to an audience of professional social scientists blinded by theory? And how did you test it?”

Heart-breaking notes from focus-grouping a hospital website. “We wanted to hear about the difficulties of caring for a mother with Alzheimer’s disease. We wanted to know what it felt like to receive a cancer diagnosis after a long journey to many doctors across a spectrum of specialties. We knew that the client was behind the two-way mirror, concerned about the website navigation, but we also knew we were going to get to some place more important by following where these stories took us”

The history and practice of karaoke. “In the late 1960s Daisuke Inoue was working as a club keyboardist in Kobe, accompanying drinkers who wanted to belt out a song. The head of a steel company asked Inoue to join him at a hot springs resort. Inoue declined, but recorded a backing tape tailored to the client’s erratic singing style. It was a success. Intuiting a demand, Inoue built a jukebox-like device fitted with a microphone and leased an initial batch to bars across the city”

Discussion of causality and probability, and how perceptions of them compare in human and artificial intelligence. “I want to build machines that act as if they had a free will and which imagine that I have a free will so that we can communicate with each other as if we both have free will. This is an engineering question. The philosophy of non-determinism is irrelevant. The question that we should be asking is: What gives us the illusion, algorithmically, that we have free will?”

Report from the Internationale Spieltage — the board-gamers’ Comic Con — in Essen. Top pick: A Feast For Odin, by Uwe Rosenberg, which “plays like a total Norse conquest simulator, with hundreds of components and several trees’ worth of cards and cardboard in each box. Players hunt, harvest, mine, refine, and build up their home islands before constructing ships, going a-raiding and stripping the mainland of all of its loot.” Even the solo game is said to be “deeply satisfying”

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If you want to do something fast, do something that has already been done. If you want to hardwire a data innovation into World Bank Operations, be prepared to involve others in a process of learning by doing.  – Holly Krambeck, Senior Transport Specialist, WBG



As the world grows more connected, data flows from a multitude of sources. Mobile networks, social media, satellites, grounds sensors, and machine-to-machine transactions are being used along with traditional data--like household surveys--to improve insights and actions toward global goals.
 
At the World Bank, a cadre of pioneering economists and sector specialists are putting big data in action. Big data sources are being harnessed to lead innovations like:

• satellites to track rural electrification, to monitor crop yields and to predict poverty;
• taxi GPS data to monitor traffic flows and congestion
• mobile phone data for insights into human mobility and behavior, as well as infrastructure and socio-economic conditions 

These stories and others are chronicled in a new World Bank publication Big Data Innovation Challenge.
 
Main Takeaways

These case stories demonstrate that big data solutions can improve development effectiveness and help World Bank operations achieve better results. Each of the stories testify to the value of teamwork and persistence.  A consistent thread throughout highlights:

• Plan meticulously to collect, process and analyze data
• Big data analytics complements traditional research techniques, and even drives the need for more traditional data to calibrate and train machine learning models
• Public-private partnerships are necessary to unlock private sector data and to promote responsible access and use
• Utilizing both human and computing power yields  optimized results
• Data science is a team sport that requires interdisciplinary collaboration between data scientists, technologists and sector specialists.

 
From Inspiration to Operations
 
The projects profiled evolved from a World Bank sponsored (internal) Big Data Innovation Challenge. Finalists were awarded funding, recognition, and technical assistance to hardwire their innovations into operational capabilities.
 
The path to scale involves a rich process of learning.  The big data program works to support this process through co-creation of knowledge and innovation acceleration tactics.  For instance, a new approach like remote sensing to predict crop yield begins with field research to validate the measurements. Once validated, implementation knowledge, including algorithms and good practice are codified and packaged for easy replication and adaptation, and disseminated through peer-to-peer, and organization to organization knowledge exchange fora.



We are confident many of these initiatives will roll-out to both World Bank’s own systems as well as in our country client systems over time. The pathways to scale will not be easy or straightforward, and key capabilities needed to develop, use, and sustain these big data solutions will take time to mature. We remain convinced that our clients will find value in using these big data solutions to complement, enhance and even replace traditional approaches. As some of these solutions will be better, faster, or cheaper, compared to the traditional alternatives. We hope the development community and others will find inspiration from the experiences profiled in Big Data Innovation – Pioneering Approaches to Data-Driven Development.  Feel free to reach out to Adarsh Desai (@adarshdesai) or Trevor Monroe (@tremon28) for information on the program.


 

Every now and then, we remember that there are poor people in the world, and sweatshops become news. Jonah Peretti — the click-accumulating mastermind behind The Huffington Post and BuzzFeed — got his start in viral journalism 15 years ago by baiting Nike with a chain of witty emails requesting that his personalisable Nike trainers be emblazoned with the word SWEATSHOP.

Peretti having moved on to grander projects, the stage storyteller Mike Daisey picked up the baton, delivering a riveting monologue, “The Agony and Ecstasy of Steve Jobs”. It was about Daisey’s heroic unmasking of appalling working conditions in the Chinese factories that make iPads. It made compelling radio when This American Life aired it in 2012. It was even more compelling when This American Life retracted the episode shortly afterwards. Ira Glass, the show’s host, wrote: “Daisey lied to me.”

Economics, of course, offers a less click-worthy perspective. We shouldn’t be surprised if people making sneakers and iPads are paid badly to do tough, hazardous work, because they live in countries where such work is everywhere. And since people are moving away from grinding and precarious rural poverty to work in these grim factories, perhaps they see them as an improvement? The pithiest account of this view comes from the great 20th-century Cambridge economist Joan Robinson: “The misery of being exploited by capitalists is nothing compared to the misery of not being exploited at all.

That’s Tim Harford in the FT, beginning his discussion of my sweatshops study with Stefan Dercon. In case FT is gated, I’ve got a short results summary and of course an academic paper.

The short answer: young people are using these jobs as fallback positions when their better but less formal opportunities don’t work out. But these jobs carried big health risks, so much so that for every month in a job, 1 in 100 complained about a serious health problem, even months after most had quit the unpleasant work.

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