Wednesday, July 6, 2016
New Payday Options for Making Ends Meet
For decades, most American companies have paid their workers once every week or two, minimizing the administrative costs of frequent paydays and maximizing the interest the companies earn by keeping the money in the bank.
And for equally long, workers have complained about the unfairness of waiting for their paychecks.
But now, thanks in part to the gig economy, a small but growing number of employers and start-ups are testing ways to give employees faster access to their wages. A variety of options — some involving payroll cards, and others using A.T.M.s and other methods — have recently hit the market, permitting people to take home their pay as soon as they have earned it.
On one hand, this could be good news for people who live from paycheck to paycheck. If the trend catches on, it could reduce the demand for products like payday loans, which workers use when they run short of money, but which charge very high interest rates. On the other hand, the services that are providing on-demand wages charge fees every time a worker uses them, so there is a trade-off.
From the employer’s perspective, instant payment for a day’s work has the potential to motivate employees to work longer hours — after all, instant financial gratification is a powerful productivity incentive.
In the ride-sharing market, same-day earnings payouts moved rapidly from an experiment to an industry standard. In November, Lyft began offering its drivers the option of cashing out immediately instead of waiting for their weekly payday. More than a third of them have used the feature, which costs 50 cents a transfer, and Lyft has paid out $200 million, executives say.
Uber started testing a similar system in March, pushing drivers’ earnings to a prepaid debit card from GoBank. Last month, it made the option available to nearly all of its 450,000 active drivers in the United States.
Start-ups are also circling. DailyPay, a New York company that lets on-demand workers collect their earnings faster for fees of $1 to $1.50 a day, has enrolled thousands of drivers and delivery people.
“I’ve been surprised at how fast it caught on,” said Harry Campbell, a driver who writes about the industry on his blog, the Rideshare Guy. “It became a competitive advantage. Once Lyft had it, and it was really popular, Uber had to have it too.”
But gig services are a niche part of the job market. Fast cash has long been a perk for waiters, bartenders and other tipped workers. Most Americans draw their paychecks from companies with more rigid financial systems. In that market, there has been little incentive for change — until recently.
Even among those with steady jobs, financial insecurity is pervasive, and some employers are starting to look at how they can help. Giving raises is expensive. Giving people quicker access to their accrued earnings doesn’t have to be.
Eight months ago, Goodwill of Silicon Valley began testing a system that lets its workers use an A.T.M. near the company’s cafeteria to withdraw up to half of the wages that they have already earned from their next paycheck, to a limit of $500. It was an instant hit. More than half of Goodwill’s 300 eligible employees have used it at least once.
Michael Fox, the company’s chief executive, said he was initially skeptical but became a convert when he saw what a big difference the option made for some workers.
“When you have people living on the edge, very small things can cause a rapid acceleration into very bad conditions,” he said. “If you’re just $60 or $90 short, and can’t make a rent payment or buy medicine, it spirals. One little thing creates a huge disaster.”
Goodwill is using technology from PayActiv, a start-up in San Jose, Calif., that uses employers’ wage and hours information to estimate their employees’ earnings. For a fee of $5 per transaction — of which Goodwill pays half as a courtesy to its workers — PayActiv advances the cash. On payday, it recoups the money directly from the employer.
PayActiv’s founder, Safwan Shah, talks with a missionary zeal about the potential impact. “The biggest bank in this country is the bank of the employer, and two to three weeks of salary for most people is stuck there,” he said. “This is a corporate responsibility issue.”
Getting employers to view it that way, though, is an extremely hard sell. Frank Dombroski knows. He has been making the pitch for five years and is only just starting to see signs of momentum.
Mr. Dombroski’s company, FlexWage, of Mountainside, N.J., also advances employees part of their earned but unpaid wages, but unlike PayActiv, it doesn’t use its own money to fund the transactions — it pulls cash directly from employers’ coffers. That is the most financially sustainable approach, he says, but it appeals to only the most highly motivated employers.
“I would be lying if I didn’t say it’s been a struggle, but we kind of knew that going in,” he said.
He thinks the tide is starting to turn. A new partnership with ADP, a big provider of payroll services, has helped FlexWage get on the radar of bigger businesses. The company says it is finalizing deals with two employers that would double the 8,000 people currently using its system.
“There’s been so much attention to the high cost of short-term lending, like bank overdraft fees and payday loans, that employers understand a lot more clearly now the dire need,” Mr. Dombroski said. “We don’t have to convince them that there’s a problem any longer. Now we need to convince them there’s a solution.”
And for equally long, workers have complained about the unfairness of waiting for their paychecks.
But now, thanks in part to the gig economy, a small but growing number of employers and start-ups are testing ways to give employees faster access to their wages. A variety of options — some involving payroll cards, and others using A.T.M.s and other methods — have recently hit the market, permitting people to take home their pay as soon as they have earned it.
On one hand, this could be good news for people who live from paycheck to paycheck. If the trend catches on, it could reduce the demand for products like payday loans, which workers use when they run short of money, but which charge very high interest rates. On the other hand, the services that are providing on-demand wages charge fees every time a worker uses them, so there is a trade-off.From the employer’s perspective, instant payment for a day’s work has the potential to motivate employees to work longer hours — after all, instant financial gratification is a powerful productivity incentive.
In the ride-sharing market, same-day earnings payouts moved rapidly from an experiment to an industry standard. In November, Lyft began offering its drivers the option of cashing out immediately instead of waiting for their weekly payday. More than a third of them have used the feature, which costs 50 cents a transfer, and Lyft has paid out $200 million, executives say.
Uber started testing a similar system in March, pushing drivers’ earnings to a prepaid debit card from GoBank. Last month, it made the option available to nearly all of its 450,000 active drivers in the United States.
Start-ups are also circling. DailyPay, a New York company that lets on-demand workers collect their earnings faster for fees of $1 to $1.50 a day, has enrolled thousands of drivers and delivery people.
“I’ve been surprised at how fast it caught on,” said Harry Campbell, a driver who writes about the industry on his blog, the Rideshare Guy. “It became a competitive advantage. Once Lyft had it, and it was really popular, Uber had to have it too.”
But gig services are a niche part of the job market. Fast cash has long been a perk for waiters, bartenders and other tipped workers. Most Americans draw their paychecks from companies with more rigid financial systems. In that market, there has been little incentive for change — until recently.
Even among those with steady jobs, financial insecurity is pervasive, and some employers are starting to look at how they can help. Giving raises is expensive. Giving people quicker access to their accrued earnings doesn’t have to be.
Eight months ago, Goodwill of Silicon Valley began testing a system that lets its workers use an A.T.M. near the company’s cafeteria to withdraw up to half of the wages that they have already earned from their next paycheck, to a limit of $500. It was an instant hit. More than half of Goodwill’s 300 eligible employees have used it at least once.
Michael Fox, the company’s chief executive, said he was initially skeptical but became a convert when he saw what a big difference the option made for some workers.
“When you have people living on the edge, very small things can cause a rapid acceleration into very bad conditions,” he said. “If you’re just $60 or $90 short, and can’t make a rent payment or buy medicine, it spirals. One little thing creates a huge disaster.”
Goodwill is using technology from PayActiv, a start-up in San Jose, Calif., that uses employers’ wage and hours information to estimate their employees’ earnings. For a fee of $5 per transaction — of which Goodwill pays half as a courtesy to its workers — PayActiv advances the cash. On payday, it recoups the money directly from the employer.
PayActiv’s founder, Safwan Shah, talks with a missionary zeal about the potential impact. “The biggest bank in this country is the bank of the employer, and two to three weeks of salary for most people is stuck there,” he said. “This is a corporate responsibility issue.”
Getting employers to view it that way, though, is an extremely hard sell. Frank Dombroski knows. He has been making the pitch for five years and is only just starting to see signs of momentum.
Mr. Dombroski’s company, FlexWage, of Mountainside, N.J., also advances employees part of their earned but unpaid wages, but unlike PayActiv, it doesn’t use its own money to fund the transactions — it pulls cash directly from employers’ coffers. That is the most financially sustainable approach, he says, but it appeals to only the most highly motivated employers.
“I would be lying if I didn’t say it’s been a struggle, but we kind of knew that going in,” he said.
He thinks the tide is starting to turn. A new partnership with ADP, a big provider of payroll services, has helped FlexWage get on the radar of bigger businesses. The company says it is finalizing deals with two employers that would double the 8,000 people currently using its system.
“There’s been so much attention to the high cost of short-term lending, like bank overdraft fees and payday loans, that employers understand a lot more clearly now the dire need,” Mr. Dombroski said. “We don’t have to convince them that there’s a problem any longer. Now we need to convince them there’s a solution.”
by Stacy Cowley, NY Times | Read more:
Image: Andrew Burton for The New York Times
Tuesday, July 5, 2016
All the Greedy Young Abigail Fishers and Me
[ed. Follow-up to an earlier post: A Colorblind Constitution: What Abigail Fisher’s Affirmative Action Case Is Really About]
Years ago, I helped Abigail Fishers get into college in Texas. That was my job: I “tutored” entitled teenagers through the application process. Specifically, and ominously for my later life, I taught them to write a convincing personal essay—a task that generally requires identifying some insight, usually gained over some period of growth. And growth often depends on hardship, a thing that none of these 18-year-olds had experienced in a structural sense over the course of their white young lives. Because of the significant disconnect involved in this premise, I always ended up rewriting their essays in the end.
My students were white, and without exception. Their parents were paying me $450 per session, and this was Houston; of course they were white. The means were the essays, and the end was the assurance that the benefits of whiteness would continue to vest themselves even as Texas demographics and UT admissions practices began to put their lovely families in a bind.
Texas parents—as ability permits, and like parents throughout the country—pay good money to live in good school zones. These schools are “good” in a double and mutually reinforcing sense: they are academically vibrant, supportive, and competitive; they also draw from a wealthy population, which means most of the students are white. As Abigail Fisher’s case, a.k.a. Becky With the Bad Grades v. UT Austin, reminded us: the top 7 percent (formerly 10 percent) at all Texas high schools get admitted to UT’s flagship campus automatically. This means that a second-rate student at a first-rate school, a.k.a. an Abigail Fisher, does not automatically get in. This means that a portion of white kids don’t get the educational success those property taxes were supposed to pay for. The 10 percent policy is implicit discrimination against “good schools,” the party line goes.
Most of the UT student body gets in through the Top 10 rule. The rest—approximately 8 percent, the year Fisher applied—are admitted through a holistic evaluation process, which takes into account things like extracurriculars, leadership, personal essays (thus the $450), and race. This is the part of UT admissions policy that Fisher’s case was challenging. Note that it was easier for her (or the anti-affirmative-action zealot who bankrolled her) to take a margin of UT admissions to the Supreme Court than to envision a version of justice in which she had, along with 92 percent of admitted students, straight-up earned her way in.
Because UT Austin is a terrific place—the rare kind of school that radiates both capaciousness and prestige—it is the top choice for many Texas high school students, and its unique admissions policy carries a lot of weight. It is discussed ad nauseam during application season; however, the reasoning behind this policy—behind the 10 percent rule, behind affirmative action—is not. I figured that part out only after I left the state and saw how much about my previous surroundings had been determined by the fact that rich white people can still game the system simply by living—that they are still reaping the benefits of centuries of preferential access to everything that sets a person up for success.
Today, certain measures have been enacted to level the playing field. But, as the Abigails among us can’t seem to admit, the mere existence of these measures does not mean that the need for them has expired. White people remain uniquely able, in a monetary sense, to game the system. For a summer, at $150 an hour, I was paid to help.
And I did. The kids were sweet, and I knew how to elicit and identify whatever topic would make their voice speed up when they talked about it. We wrote about canoes capsizing at summer camp, about football injuries, about girlfriends freezing us out at youth group. For the most part, they got in where they wanted, and I worked a leisurely three hours a day, helping them cheat.
I’ve had a lot of relatively demeaning jobs in my life. I never thought I deserved better than any of them—first because I didn’t, and second, because a sense of entitlement means nothing without capital to back it up. I’ve waitressed in short shorts and cowboy boots. I’ve street-canvassed for recycling. When I was 16, I was paid minimum wage to participate in a reality TV show in Puerto Rico that included challenges like eating mayonnaise on camera with my hands tied behind my back.
This job—writing college essays for Abigail Fishers—was the only job I have ever been truly ashamed of, and I am so ashamed of it now that it hurts. I did it, too, for a particularly embarrassing reason: because it paid so well that I could keep my earning hours to a minimum, and for four months spend most of my time writing fiction so I could get into an MFA program. Once I did get in, my boyfriend started looking at me reproachfully when he came home from work and saw me sending invoices. “Stop doing this,” he said flatly, in the late afternoon one day.
The first time Abigail Fisher filed a Supreme Court case because she didn’t get into college, she was 18 and reaching. She had a 3.59 GPA, an 1180 SAT score. She had not cracked her high school’s top 10 percent, and so, by the book, she did not qualify for guaranteed admission to UT. But she deserved admission nonetheless, she believed, and primarily—it appears—because she wanted it. She had “dreamt of going to UT ever since the second grade,” she said, in a 2012 video. Her dad had gone there, and so had her sister, and so had “tons” of friends and family. “It was a tradition I wanted to continue,” she said. For Fisher, basic competence and a powerful sense of unexamined entitlement was admissions criteria enough.
Fisher’s temperament—this exact sort of greedy placidity—made her an ideal figurehead for Edward Blum, the University of Texas graduate (’73, hook ’em!) who is bankrolling her case. Blum, who is white, runs an organization called the Project on Fair Representation, which takes on the noble work of arranging legal representation to fight race-based policies aimed at combating inequity. Blum took the underlying, incorrect instinct that is latent in people like Fisher and turned it into the basis of a court case: Fisher went from a tautological belief (“I deserve to be admitted because I deserve to be admitted”) to a frankly insane one—that she deserved admission because she’d been discriminated against, and specifically, discriminated against for being white.
by Jia Tolentino, Jezebel | Read more:
Image: Jim Cooke
Years ago, I helped Abigail Fishers get into college in Texas. That was my job: I “tutored” entitled teenagers through the application process. Specifically, and ominously for my later life, I taught them to write a convincing personal essay—a task that generally requires identifying some insight, usually gained over some period of growth. And growth often depends on hardship, a thing that none of these 18-year-olds had experienced in a structural sense over the course of their white young lives. Because of the significant disconnect involved in this premise, I always ended up rewriting their essays in the end.
My students were white, and without exception. Their parents were paying me $450 per session, and this was Houston; of course they were white. The means were the essays, and the end was the assurance that the benefits of whiteness would continue to vest themselves even as Texas demographics and UT admissions practices began to put their lovely families in a bind.
Texas parents—as ability permits, and like parents throughout the country—pay good money to live in good school zones. These schools are “good” in a double and mutually reinforcing sense: they are academically vibrant, supportive, and competitive; they also draw from a wealthy population, which means most of the students are white. As Abigail Fisher’s case, a.k.a. Becky With the Bad Grades v. UT Austin, reminded us: the top 7 percent (formerly 10 percent) at all Texas high schools get admitted to UT’s flagship campus automatically. This means that a second-rate student at a first-rate school, a.k.a. an Abigail Fisher, does not automatically get in. This means that a portion of white kids don’t get the educational success those property taxes were supposed to pay for. The 10 percent policy is implicit discrimination against “good schools,” the party line goes.Most of the UT student body gets in through the Top 10 rule. The rest—approximately 8 percent, the year Fisher applied—are admitted through a holistic evaluation process, which takes into account things like extracurriculars, leadership, personal essays (thus the $450), and race. This is the part of UT admissions policy that Fisher’s case was challenging. Note that it was easier for her (or the anti-affirmative-action zealot who bankrolled her) to take a margin of UT admissions to the Supreme Court than to envision a version of justice in which she had, along with 92 percent of admitted students, straight-up earned her way in.
Because UT Austin is a terrific place—the rare kind of school that radiates both capaciousness and prestige—it is the top choice for many Texas high school students, and its unique admissions policy carries a lot of weight. It is discussed ad nauseam during application season; however, the reasoning behind this policy—behind the 10 percent rule, behind affirmative action—is not. I figured that part out only after I left the state and saw how much about my previous surroundings had been determined by the fact that rich white people can still game the system simply by living—that they are still reaping the benefits of centuries of preferential access to everything that sets a person up for success.
Today, certain measures have been enacted to level the playing field. But, as the Abigails among us can’t seem to admit, the mere existence of these measures does not mean that the need for them has expired. White people remain uniquely able, in a monetary sense, to game the system. For a summer, at $150 an hour, I was paid to help.
And I did. The kids were sweet, and I knew how to elicit and identify whatever topic would make their voice speed up when they talked about it. We wrote about canoes capsizing at summer camp, about football injuries, about girlfriends freezing us out at youth group. For the most part, they got in where they wanted, and I worked a leisurely three hours a day, helping them cheat.
I’ve had a lot of relatively demeaning jobs in my life. I never thought I deserved better than any of them—first because I didn’t, and second, because a sense of entitlement means nothing without capital to back it up. I’ve waitressed in short shorts and cowboy boots. I’ve street-canvassed for recycling. When I was 16, I was paid minimum wage to participate in a reality TV show in Puerto Rico that included challenges like eating mayonnaise on camera with my hands tied behind my back.
This job—writing college essays for Abigail Fishers—was the only job I have ever been truly ashamed of, and I am so ashamed of it now that it hurts. I did it, too, for a particularly embarrassing reason: because it paid so well that I could keep my earning hours to a minimum, and for four months spend most of my time writing fiction so I could get into an MFA program. Once I did get in, my boyfriend started looking at me reproachfully when he came home from work and saw me sending invoices. “Stop doing this,” he said flatly, in the late afternoon one day.
The first time Abigail Fisher filed a Supreme Court case because she didn’t get into college, she was 18 and reaching. She had a 3.59 GPA, an 1180 SAT score. She had not cracked her high school’s top 10 percent, and so, by the book, she did not qualify for guaranteed admission to UT. But she deserved admission nonetheless, she believed, and primarily—it appears—because she wanted it. She had “dreamt of going to UT ever since the second grade,” she said, in a 2012 video. Her dad had gone there, and so had her sister, and so had “tons” of friends and family. “It was a tradition I wanted to continue,” she said. For Fisher, basic competence and a powerful sense of unexamined entitlement was admissions criteria enough.
Fisher’s temperament—this exact sort of greedy placidity—made her an ideal figurehead for Edward Blum, the University of Texas graduate (’73, hook ’em!) who is bankrolling her case. Blum, who is white, runs an organization called the Project on Fair Representation, which takes on the noble work of arranging legal representation to fight race-based policies aimed at combating inequity. Blum took the underlying, incorrect instinct that is latent in people like Fisher and turned it into the basis of a court case: Fisher went from a tautological belief (“I deserve to be admitted because I deserve to be admitted”) to a frankly insane one—that she deserved admission because she’d been discriminated against, and specifically, discriminated against for being white.
by Jia Tolentino, Jezebel | Read more:
Image: Jim Cooke
Synthetic Spider Silk Could Be the Biggest Technological Advance in Clothing Since Nylon
Spider silk’s qualities are nearly mythical. Its tensile strength is comparable to steel’s. Yet it is lighter, and can be as stretchy as a rubber band. Those traits in combination make it tougher than Kevlar. To give you an idea: If the spider webs that shoot from Spider Man’s wrists were real spider silk, the superhero could genuinely have pulled the runaway train to a halt in that dramatic scene in Spider Man 2.
So it’s no surprise that the race is on to create a synthetic version.
After years of hype and false starts, including one now-bankrupt effort that involved genetically modified goats producing it in their milk, a few companies think they’ve figured it out. The two leading the pack are Spiber, a Japanese company, and a California-based startup called Bolt Threads. Bolt Threads believes it has the edge, and that spider silk is only the beginning of what it can do.
A real spider generates silk in specialized glands in its abdomen, and creates the silk strands using a spinning organ called a spinneret. Some spiders produce up to seven types of silk, each with its own purpose and attributes.
But unlike silkworm silk, which silkworms produce to make their cocoons (the stuff used for diaphanous dresses and smart neckties), spider silk can’t be farmed in large quantities because spiders are cannibals, and will eat one another in close quarters.
Bolt Threads doesn’t use spiders to make its silk. The principal ingredients are genetically modified yeast, water, and sugar. The raw silk is produced through fermentation, much like brewing beer, except instead of the yeast turning the sugar into alcohol, they turn it into the raw stuff of spider silk. Bolt Threads spins that into threads using a method similar to the wet-spinning process used to create cellulose-based fibers such as Lyocell. Levin says it’s molecularly the same as natural spider silk, except for a few deliberate variations that only a chemical biologist would recognize.
Synthetic spider silk could be used for everything from automobile parts to medical devices to performance outdoor gear, which is the area that’s attracting some of the most attention thus far. Bolt Threads recently announced a $50 million round of funding, as well as a new partnership with the outdoor brand Patagonia, which demonstrates a major vote of confidence in its technology.
Neither Bolt Threads nor Patagonia will give details on what products they’re working on just yet, but Matt Dwyer, Patagonia’s director of material innovation, promises when something does come out, it will be “awesome.”
“We think they’ve cracked the code,” he says. “For them to have come up with this capability… is just the kind of stuff that blows your mind.”
So it’s no surprise that the race is on to create a synthetic version.After years of hype and false starts, including one now-bankrupt effort that involved genetically modified goats producing it in their milk, a few companies think they’ve figured it out. The two leading the pack are Spiber, a Japanese company, and a California-based startup called Bolt Threads. Bolt Threads believes it has the edge, and that spider silk is only the beginning of what it can do.
A real spider generates silk in specialized glands in its abdomen, and creates the silk strands using a spinning organ called a spinneret. Some spiders produce up to seven types of silk, each with its own purpose and attributes.
But unlike silkworm silk, which silkworms produce to make their cocoons (the stuff used for diaphanous dresses and smart neckties), spider silk can’t be farmed in large quantities because spiders are cannibals, and will eat one another in close quarters.
Bolt Threads doesn’t use spiders to make its silk. The principal ingredients are genetically modified yeast, water, and sugar. The raw silk is produced through fermentation, much like brewing beer, except instead of the yeast turning the sugar into alcohol, they turn it into the raw stuff of spider silk. Bolt Threads spins that into threads using a method similar to the wet-spinning process used to create cellulose-based fibers such as Lyocell. Levin says it’s molecularly the same as natural spider silk, except for a few deliberate variations that only a chemical biologist would recognize.
Synthetic spider silk could be used for everything from automobile parts to medical devices to performance outdoor gear, which is the area that’s attracting some of the most attention thus far. Bolt Threads recently announced a $50 million round of funding, as well as a new partnership with the outdoor brand Patagonia, which demonstrates a major vote of confidence in its technology.
Neither Bolt Threads nor Patagonia will give details on what products they’re working on just yet, but Matt Dwyer, Patagonia’s director of material innovation, promises when something does come out, it will be “awesome.”
“We think they’ve cracked the code,” he says. “For them to have come up with this capability… is just the kind of stuff that blows your mind.”
by Marc Bain, Quartz | Read more:
Image: Bolt Threads
To Know a Town, Know Its Fish Market
Bobby was the first person I met in Korea. He sold flounder and baby octopus at the fish market. In Dubai, my first acquaintance was the immigrant cook who made me a breakfast of South Indian fish curry. If you want to understand daily life in an alien place — to meet the people who give a city its rhythms — go straight to the fish market.
As a food and travel writer, the first thing I do whenever I arrive in a new place is hit the fish market. In a world where entire countries have altered their streets and customs to attract moneyed tourists, fish markets — and the people who work there, hauling carcasses in the wee hours — remain relatively authentic. No other single site offers such a thorough orientation to a people, an economy, and a culture. Except for a few of the biggest (Tokyo’s Tsukiji or Seattle’s Pike Place), these aren’t marketed as tourist attractions. Yet for travelers looking to taste local delicacies — Hawaiian limpets called opihi, Seattle’s famous salmon, or baby octopus in Korea still wriggling around on the plate — seafood markets offer a no-frills place to find not only the food, but the life of a city.
Fish markets rarely compete with palaces or parks in the mind of the average tourist — you’re unlikely to frame a photograph of mollusks the way you’d frame a photo of Westminster Abbey; you’re unlikely to Instagram your fish congee for breakfast at Tekka Market in Singapore the way one might a croissant in a Paris café. Yet these markets are still visual feasts. These are the scenes that remain in my mind after travel: Stall after stall of iridescent stock in Negombo or simply laid on a tarp in Passikudah (both in Sri Lanka); silver fish stacked over sparkling ice in Seoul, South Korea; countless crabs, climbing upward, claws akimbo, in Dubai’s Deira Fish Souk.
Everywhere in the world, fish markets fill up before dawn with working-class people hustling to make a living through a fragile and expensive commodity. Fish markets are both a reflection of the values and economy of a place, and a microcosm of the city itself.
Take Noryangjin, Seoul’s largest fish market, where tuna auctions wrap by 6:30 a.m. and workers hustle to pack up the fish that’s been sold. Tables overflow with large carcasses, sorted by type, down the center of the room.
Like the rest of Seoul, Noryangjin teems with people and fast-moving hand-carts that brush by brisk walkers. I met Bobby there along a series of stalls where smaller tanks showcase live fish. Bobby overheard me speaking in English and came over to talk. This was common in Korea, to find offers of help and hospitality proffered from within the chaos of the street. The same people who jumble against you as you’re packed into the a Seoul subway car will stop everything on the street and offer directions if you so much as glance at a map.
After years living abroad — in Texas, of all places — Bobby returned to his home country of Korea, where he now ran this two-square-foot fish stall. “What kind of fish do you want?” he asked, offering to translate for other vendors if he didn’t have it. The kitchens that line Noryangjin’s outer aisles are BYOF: bring your own fish. I bought a flounder and a baby octopus, and he followed me to the restaurant behind his stall to translate my preparation requests to the chef.
Fish markets serve the best breakfasts. While I waited for my platter of sashimi, fish head-and-skeleton soup, and still-twitching raw baby octopus, I surveyed the room. A table of 20-somethings all dove from their seats to catch their friend as she swayed with drunkenness. A young couple, too, seemed to be soaking up booze. A table of men still wearing waterproof overalls from their night shift gathered over what was, for them, dinner. They seemed excited to see a visitor in the market and fed me bites of their food, including abalone — which tastes like an oyster, except more so: chewier, saltier, sweeter, and just a bit buttery. I was, possibly, the only person starting their day, rather than ending it.
by Naomi Tomky, Pacific Standard | Read more:
Image:Dan Kitwood /Getty Images
As a food and travel writer, the first thing I do whenever I arrive in a new place is hit the fish market. In a world where entire countries have altered their streets and customs to attract moneyed tourists, fish markets — and the people who work there, hauling carcasses in the wee hours — remain relatively authentic. No other single site offers such a thorough orientation to a people, an economy, and a culture. Except for a few of the biggest (Tokyo’s Tsukiji or Seattle’s Pike Place), these aren’t marketed as tourist attractions. Yet for travelers looking to taste local delicacies — Hawaiian limpets called opihi, Seattle’s famous salmon, or baby octopus in Korea still wriggling around on the plate — seafood markets offer a no-frills place to find not only the food, but the life of a city.
Fish markets rarely compete with palaces or parks in the mind of the average tourist — you’re unlikely to frame a photograph of mollusks the way you’d frame a photo of Westminster Abbey; you’re unlikely to Instagram your fish congee for breakfast at Tekka Market in Singapore the way one might a croissant in a Paris café. Yet these markets are still visual feasts. These are the scenes that remain in my mind after travel: Stall after stall of iridescent stock in Negombo or simply laid on a tarp in Passikudah (both in Sri Lanka); silver fish stacked over sparkling ice in Seoul, South Korea; countless crabs, climbing upward, claws akimbo, in Dubai’s Deira Fish Souk.Everywhere in the world, fish markets fill up before dawn with working-class people hustling to make a living through a fragile and expensive commodity. Fish markets are both a reflection of the values and economy of a place, and a microcosm of the city itself.
Take Noryangjin, Seoul’s largest fish market, where tuna auctions wrap by 6:30 a.m. and workers hustle to pack up the fish that’s been sold. Tables overflow with large carcasses, sorted by type, down the center of the room.
Like the rest of Seoul, Noryangjin teems with people and fast-moving hand-carts that brush by brisk walkers. I met Bobby there along a series of stalls where smaller tanks showcase live fish. Bobby overheard me speaking in English and came over to talk. This was common in Korea, to find offers of help and hospitality proffered from within the chaos of the street. The same people who jumble against you as you’re packed into the a Seoul subway car will stop everything on the street and offer directions if you so much as glance at a map.
After years living abroad — in Texas, of all places — Bobby returned to his home country of Korea, where he now ran this two-square-foot fish stall. “What kind of fish do you want?” he asked, offering to translate for other vendors if he didn’t have it. The kitchens that line Noryangjin’s outer aisles are BYOF: bring your own fish. I bought a flounder and a baby octopus, and he followed me to the restaurant behind his stall to translate my preparation requests to the chef.
Fish markets serve the best breakfasts. While I waited for my platter of sashimi, fish head-and-skeleton soup, and still-twitching raw baby octopus, I surveyed the room. A table of 20-somethings all dove from their seats to catch their friend as she swayed with drunkenness. A young couple, too, seemed to be soaking up booze. A table of men still wearing waterproof overalls from their night shift gathered over what was, for them, dinner. They seemed excited to see a visitor in the market and fed me bites of their food, including abalone — which tastes like an oyster, except more so: chewier, saltier, sweeter, and just a bit buttery. I was, possibly, the only person starting their day, rather than ending it.
by Naomi Tomky, Pacific Standard | Read more:
Image:Dan Kitwood /Getty Images
Balmuda, the $230 Toaster From Japan
It's a plain little oven, but what comes out is both mundane and magical: perfectly toasted bread.
Balmuda, a small appliance maker based in Tokyo's suburbs, has taken an ordinary kitchen appliance—the toaster—and turned it into a high-tech gadget. Using steam and carefully calibrated heat cycles, it transforms store-bought bread into something that smells, tastes and feels like it popped out of a baker's oven.
The toaster costs 24,000 yen ($230), or almost five times the price of a regular device in Japan (the smaller appliances with doors and trays are the norm here, rather than the pop-up variety). With at least a three-month wait in stores, the gadget has become a quiet hit, even though the manufacturer hasn't bought ads or aired any commercials since it debuted in June—an unusual glimmer of innovation in a country that once wooed consumers with Walkmans, digital cameras and flat-panel TVs.
It was at a company picnic on a rainy day, warming bread on a grill, that company founder Gen Terao and his band of product designers accidentally made great toast. After the showers stopped, they tried to reproduce it in a parking lot and realized that water was the key. Thousands of slices later, they figured out that steam traps moisture inside the bread while it's being warmed at a low temperature. The heat is cranked up just at the end, giving it a respectable crust.
"The best results are with croissants," said Mark Oda, who works on web and media content in Tokyo and was among the first to buy Balmuda's toaster. "I can never go back to 5,000-yen toasters."
by Reed Stevenson, Bloomberg | Read more:
Image: Akio Kon/Bloomber
Balmuda, a small appliance maker based in Tokyo's suburbs, has taken an ordinary kitchen appliance—the toaster—and turned it into a high-tech gadget. Using steam and carefully calibrated heat cycles, it transforms store-bought bread into something that smells, tastes and feels like it popped out of a baker's oven.
The toaster costs 24,000 yen ($230), or almost five times the price of a regular device in Japan (the smaller appliances with doors and trays are the norm here, rather than the pop-up variety). With at least a three-month wait in stores, the gadget has become a quiet hit, even though the manufacturer hasn't bought ads or aired any commercials since it debuted in June—an unusual glimmer of innovation in a country that once wooed consumers with Walkmans, digital cameras and flat-panel TVs.It was at a company picnic on a rainy day, warming bread on a grill, that company founder Gen Terao and his band of product designers accidentally made great toast. After the showers stopped, they tried to reproduce it in a parking lot and realized that water was the key. Thousands of slices later, they figured out that steam traps moisture inside the bread while it's being warmed at a low temperature. The heat is cranked up just at the end, giving it a respectable crust.
"The best results are with croissants," said Mark Oda, who works on web and media content in Tokyo and was among the first to buy Balmuda's toaster. "I can never go back to 5,000-yen toasters."
by Reed Stevenson, Bloomberg | Read more:
Image: Akio Kon/Bloomber
Consciousness: The Mind Messing With the Mind
A paper in The British Medical Journal in December reported that cognitive behavioral therapy — a means of coaxing people into changing the way they think — is as effective as Prozac or Zoloft in treating major depression.
In ways no one understands, talk therapy reaches down into the biological plumbing and affects the flow of neurotransmitters in the brain. Other studies have found similar results for “mindfulness” — Buddhist-inspired meditation in which one’s thoughts are allowed to drift gently through the head like clouds reflected in still mountain water.
Findings like these have become so commonplace that it’s easy to forget their strange implications.
Depression can be treated in two radically different ways: by altering the brain with chemicals, or by altering the mind by talking to a therapist. But we still can’t explain how mind arises from matter or how, in turn, mind acts on the brain.
This longstanding conundrum — the mind-body problem — was succinctly described by the philosopher David Chalmers at a recent symposium at The New York Academy of Sciences. “The scientific and philosophical consensus is that there is no nonphysical soul or ego, or at least no evidence for that,” he said.
Descartes’s notion of dualism — mind and body as separate things — has long receded from science. The challenge now is to explain how the inner world of consciousness arises from the flesh of the brain.
Michael Graziano, a neuroscientist at Princeton University, suggested to the audience that consciousness is a kind of con game the brain plays with itself. The brain is a computer that evolved to simulate the outside world. Among its internal models is a simulation of itself — a crude approximation of its own neurological processes.
The result is an illusion. Instead of neurons and synapses, we sense a ghostly presence — a self — inside the head. But it’s all just data processing.
“The machine mistakenly thinks it has magic inside it,” Dr. Graziano said. And it calls the magic consciousness.
It’s not the existence of this inner voice he finds mysterious. “The phenomenon to explain,” he said, “is why the brain, as a machine, insists it has this property that is nonphysical.”
The discussion, broadcast online, reminded me of Tom Stoppard’s newest play, “The Hard Problem,” in which a troubled young psychology researcher named Hilary suffers a severe case of the very affliction Dr. Graziano described. Surely there is more to the brain than biology, she insists to her boyfriend, a hard-core materialist named Spike. There must be “mind stuff that doesn’t show up in a scan.”
Mr. Stoppard borrowed his title from a paper by Dr. Chalmers. The “easy problem” is explaining, at least in principle, how thinking, memory, attention and so forth are just neurological computing. But for the hard problem — why all of these processes feel like something — “there is nothing like a consensus theory or even a consensus guess,” Dr. Chalmers said at the symposium.
Or, as Hilary puts it in the play, “Every theory proposed for the problem of consciousness has the same degree of demonstrability as divine intervention.” There is a gap in the explanation where suddenly a miracle seems to occur.
In ways no one understands, talk therapy reaches down into the biological plumbing and affects the flow of neurotransmitters in the brain. Other studies have found similar results for “mindfulness” — Buddhist-inspired meditation in which one’s thoughts are allowed to drift gently through the head like clouds reflected in still mountain water.
Findings like these have become so commonplace that it’s easy to forget their strange implications.Depression can be treated in two radically different ways: by altering the brain with chemicals, or by altering the mind by talking to a therapist. But we still can’t explain how mind arises from matter or how, in turn, mind acts on the brain.
This longstanding conundrum — the mind-body problem — was succinctly described by the philosopher David Chalmers at a recent symposium at The New York Academy of Sciences. “The scientific and philosophical consensus is that there is no nonphysical soul or ego, or at least no evidence for that,” he said.
Descartes’s notion of dualism — mind and body as separate things — has long receded from science. The challenge now is to explain how the inner world of consciousness arises from the flesh of the brain.
Michael Graziano, a neuroscientist at Princeton University, suggested to the audience that consciousness is a kind of con game the brain plays with itself. The brain is a computer that evolved to simulate the outside world. Among its internal models is a simulation of itself — a crude approximation of its own neurological processes.
The result is an illusion. Instead of neurons and synapses, we sense a ghostly presence — a self — inside the head. But it’s all just data processing.
“The machine mistakenly thinks it has magic inside it,” Dr. Graziano said. And it calls the magic consciousness.
It’s not the existence of this inner voice he finds mysterious. “The phenomenon to explain,” he said, “is why the brain, as a machine, insists it has this property that is nonphysical.”
The discussion, broadcast online, reminded me of Tom Stoppard’s newest play, “The Hard Problem,” in which a troubled young psychology researcher named Hilary suffers a severe case of the very affliction Dr. Graziano described. Surely there is more to the brain than biology, she insists to her boyfriend, a hard-core materialist named Spike. There must be “mind stuff that doesn’t show up in a scan.”
Mr. Stoppard borrowed his title from a paper by Dr. Chalmers. The “easy problem” is explaining, at least in principle, how thinking, memory, attention and so forth are just neurological computing. But for the hard problem — why all of these processes feel like something — “there is nothing like a consensus theory or even a consensus guess,” Dr. Chalmers said at the symposium.
Or, as Hilary puts it in the play, “Every theory proposed for the problem of consciousness has the same degree of demonstrability as divine intervention.” There is a gap in the explanation where suddenly a miracle seems to occur.
by George Johnson, NY Times | Read more:
Image: Chris Silas Neal
Saturday, July 2, 2016
Stuck Waiting at Airport Security? Blame This Company and TSA
The Transportation Security Administration would have us believe that those outrageous waits at airport checkpoints that made headlines recently were caused by a screener shortage or a surge in passengers. But there’s another reason for the crushing lines: a private contractor.
MorphoTrustUSA, in charge of scaling up the agency’s PreCheck fast-track lanes at airports around the country, is suing the federal government, a move that could prevent relief for millions of angry travelers.
Tens of thousands of travelers have missed their flights in recent months as wait times at checkpoints exceeded two hours at busy hubs in places like Chicago and Seattle. And there’s another pressing reason to fix the problem: big crowds at airports are potential targets for terrorists as recent attacks in Brussels, and now, Istanbul, have shown.
While Congress quickly gave TSA money to bring in reinforcements after lines spilled out of terminals, the fix that has the best chance of succeeding in the long run, experts say, is to get PreCheck enrollment into high gear.
MorphoTrust already has a contract with the TSA to bring millions of new members into PreCheck so they can keep their shoes on and their laptops stored as they whisk through security. But TSA believes that burden is too much for one company to handle and it’s been trying since 2013 to bring in more private sector vendors to join the effort to boost enrollments from 3 million today to 25 million by 2019, when 50 percent of all fliers would get the express treatment.
According to those familiar with the bidding process thus far, the aim is to make it as easy to sign up for PreCheck as it is to purchase a product online, while maintaining the integrity of the vetting process.
But since January, MorphoTrust has been fighting back.
First, the company filed what’s known as a “bid protest” that basically stopped TSA from issuing awards to more companies. When that protest was overruled by the TSA and the Government Accountability Office, MorphoTrust sued the government in federal claims court. While the legal process drags on, TSA is effectively blocked from issuing the new contracts and reaping the benefits this could bring.
“It is frankly bizarre,” said Robert Poole, director of transportation policy for the Reason Foundation, who has followed TSA since its inception after the 9/11 attacks. “It would be tragic for air travelers if this gets held up for another year or two.” (...)
A Delay Two Decades in the Making
The story dates back to the beginnings of TSA in 2001, when Congress mandated that the nascent agency establish a “trusted passenger” program to give low-risk travelers expedited treatment so screeners could focus their attention on fliers who might merit more scrutiny. For more than a decade TSA struggled with how to meet that goal, rolling out a series of failed schemes; they ranged from the comically ineffectual (“Black Diamond” lanes for “expert” travelers, dreamed up by a TSA chief who liked to ski) to the downright creepy, with a far-fetched plan to tap credit rating firms for personal information to establish a vast database onall passengers (who would be given “threat scores” for a good measure).
Finally, TSA in 2011 came up with PreCheck, which it believed would be less controversial since it was voluntary. The idea would be to give fliers who submitted to a background check and fingerprinting a sort of “screening lite” at airports that, like EZ Pass lanes at toll plazas, would make everything move more efficiently.
TSA didn’t have the resources to jumpstart the plan so it selected MorphoTrust to set up a network of enrollment services; after all, the company was working under contract with TSA, performing vetting services for things like a transportation worker ID program. Morpho’s role has been mainly a passive one: collecting the application forms and obtaining fingerprints, which are passed on to the TSA, so the data can be run through the FBI’s criminal background check apparatus.
TSA made its first blunder with PreCheck at inception by announcing a goal of having 25 percent of all air travelers using the speedy lanes by the end of 2013. It soon became clear that wasn’t going to happen: after an initial surge of interest, PreCheck enrollment proceeded at a desultory pace. Maybe it was the required in-person appearance at a TSA-approved center, or the $85 fee for five-year membership, but whatever the reason, sign-ups fell below expectations.
“This disastrous enrollment process is producing a chokepoint” that’s depriving millions of travelers of the benefits of PreCheck, said Kevin Mitchell, who heads the Business Travel Coalition. He added that these express security lanes produce on average three times the passenger throughput as regular security lines.
But TSA instead saw another way to reach that 25 percent goal: reel in passengers who were not part of PreCheck, but who popped up as low-risk in the routine assessments TSA gives to all passengers before flight time. (That’s under something called Secure Flight, which is why you provide your date of birth and exact legal name when you book a flight.) The number of people using the lines exploded by 300 percent.
“It was a fiasco,” Poole said, with clueless passengers clogging the lanes and slowing things down for everyone. And when an infamous 1970s terrorist, Sara Jane Olsen, was waved into a PreCheck lane by a screener (over objections from another TSA agent who recognized the former fugitive) this one too bit the dust.
MorphoTrustUSA, in charge of scaling up the agency’s PreCheck fast-track lanes at airports around the country, is suing the federal government, a move that could prevent relief for millions of angry travelers.
Tens of thousands of travelers have missed their flights in recent months as wait times at checkpoints exceeded two hours at busy hubs in places like Chicago and Seattle. And there’s another pressing reason to fix the problem: big crowds at airports are potential targets for terrorists as recent attacks in Brussels, and now, Istanbul, have shown.While Congress quickly gave TSA money to bring in reinforcements after lines spilled out of terminals, the fix that has the best chance of succeeding in the long run, experts say, is to get PreCheck enrollment into high gear.
MorphoTrust already has a contract with the TSA to bring millions of new members into PreCheck so they can keep their shoes on and their laptops stored as they whisk through security. But TSA believes that burden is too much for one company to handle and it’s been trying since 2013 to bring in more private sector vendors to join the effort to boost enrollments from 3 million today to 25 million by 2019, when 50 percent of all fliers would get the express treatment.
According to those familiar with the bidding process thus far, the aim is to make it as easy to sign up for PreCheck as it is to purchase a product online, while maintaining the integrity of the vetting process.
But since January, MorphoTrust has been fighting back.
First, the company filed what’s known as a “bid protest” that basically stopped TSA from issuing awards to more companies. When that protest was overruled by the TSA and the Government Accountability Office, MorphoTrust sued the government in federal claims court. While the legal process drags on, TSA is effectively blocked from issuing the new contracts and reaping the benefits this could bring.
“It is frankly bizarre,” said Robert Poole, director of transportation policy for the Reason Foundation, who has followed TSA since its inception after the 9/11 attacks. “It would be tragic for air travelers if this gets held up for another year or two.” (...)
A Delay Two Decades in the Making
The story dates back to the beginnings of TSA in 2001, when Congress mandated that the nascent agency establish a “trusted passenger” program to give low-risk travelers expedited treatment so screeners could focus their attention on fliers who might merit more scrutiny. For more than a decade TSA struggled with how to meet that goal, rolling out a series of failed schemes; they ranged from the comically ineffectual (“Black Diamond” lanes for “expert” travelers, dreamed up by a TSA chief who liked to ski) to the downright creepy, with a far-fetched plan to tap credit rating firms for personal information to establish a vast database onall passengers (who would be given “threat scores” for a good measure).
Finally, TSA in 2011 came up with PreCheck, which it believed would be less controversial since it was voluntary. The idea would be to give fliers who submitted to a background check and fingerprinting a sort of “screening lite” at airports that, like EZ Pass lanes at toll plazas, would make everything move more efficiently.
TSA didn’t have the resources to jumpstart the plan so it selected MorphoTrust to set up a network of enrollment services; after all, the company was working under contract with TSA, performing vetting services for things like a transportation worker ID program. Morpho’s role has been mainly a passive one: collecting the application forms and obtaining fingerprints, which are passed on to the TSA, so the data can be run through the FBI’s criminal background check apparatus.
TSA made its first blunder with PreCheck at inception by announcing a goal of having 25 percent of all air travelers using the speedy lanes by the end of 2013. It soon became clear that wasn’t going to happen: after an initial surge of interest, PreCheck enrollment proceeded at a desultory pace. Maybe it was the required in-person appearance at a TSA-approved center, or the $85 fee for five-year membership, but whatever the reason, sign-ups fell below expectations.
“This disastrous enrollment process is producing a chokepoint” that’s depriving millions of travelers of the benefits of PreCheck, said Kevin Mitchell, who heads the Business Travel Coalition. He added that these express security lanes produce on average three times the passenger throughput as regular security lines.
But TSA instead saw another way to reach that 25 percent goal: reel in passengers who were not part of PreCheck, but who popped up as low-risk in the routine assessments TSA gives to all passengers before flight time. (That’s under something called Secure Flight, which is why you provide your date of birth and exact legal name when you book a flight.) The number of people using the lines exploded by 300 percent.
“It was a fiasco,” Poole said, with clueless passengers clogging the lanes and slowing things down for everyone. And when an infamous 1970s terrorist, Sara Jane Olsen, was waved into a PreCheck lane by a screener (over objections from another TSA agent who recognized the former fugitive) this one too bit the dust.
by Barbara Peterson, Daily Beast | Read more:
Image: uncredited
Scotty Moore (December, 1931 – June, 2016)
The passing of original Elvis Presley guitarist Scotty Moore this week, despite living to the ripe old age of 84, nevertheless sent shockwaves across the rock ‘n’ roll community already still mourning the deaths of several of its heroes this year.
The loss of Moore, who continued to produce, record and perform right up until before he fell ill with symptoms not exactly revealed at press time, sent a special kind of jolt through the hearts of music fans the world over, because his guitar playing has served as one of the key building blocks of the modern rock infrastructure since that fateful day after the Fourth of July in 1954 when he cut his first session with Elvis at Sun Records with producer Sam Phillips.
The King may have given rock music its swagger in the mid-’50s, but Moore gave the young genre its sense of danger with his sharp, piercing variation of the Chet Atkins style that influenced him on such priceless early Presley cuts as “That’s All Right”, “Mystery Train”, “Long Tall Sally” and that indelible walking riff on “Jailhouse Rock”.
Elvis and his swinging hips might have made millions of teenage girls swoon in the ’50s, but just as many fell in love with the pure rawness and simplicity of Moore’s guitar playing, including some of the most renowned guitar players of the last 60 years: Keith Richards, Jeff Beck, Jimmy Page, George Harrison, Ron Wood, Rick Nielsen, Mark Knopfler, Alvin Lee, Eric Clapton, Bruce Springsteen, Johnny Ramone, the list goes on forever.
“All I wanted to do in the world was to be able to play and sound like that,” Richards once famously stated. “Everyone else wanted to be Elvis; I wanted to be Scotty.”
Listen to the reckless abandon he uses to back Presley in his second performance at the Louisiana Hayride on August 20, 1955, and you will clearly recognize what Keef and countless others heard on the outset, that unbridled purity that made Moore’s tiny little amp sound like Neil Young’s great wall of Fenders. The strings on his Gibson ES-295 were lightning in a bottle, the spark that ignited the biggest youth movement in American history.
The loss of Moore, who continued to produce, record and perform right up until before he fell ill with symptoms not exactly revealed at press time, sent a special kind of jolt through the hearts of music fans the world over, because his guitar playing has served as one of the key building blocks of the modern rock infrastructure since that fateful day after the Fourth of July in 1954 when he cut his first session with Elvis at Sun Records with producer Sam Phillips.The King may have given rock music its swagger in the mid-’50s, but Moore gave the young genre its sense of danger with his sharp, piercing variation of the Chet Atkins style that influenced him on such priceless early Presley cuts as “That’s All Right”, “Mystery Train”, “Long Tall Sally” and that indelible walking riff on “Jailhouse Rock”.
Elvis and his swinging hips might have made millions of teenage girls swoon in the ’50s, but just as many fell in love with the pure rawness and simplicity of Moore’s guitar playing, including some of the most renowned guitar players of the last 60 years: Keith Richards, Jeff Beck, Jimmy Page, George Harrison, Ron Wood, Rick Nielsen, Mark Knopfler, Alvin Lee, Eric Clapton, Bruce Springsteen, Johnny Ramone, the list goes on forever.
“All I wanted to do in the world was to be able to play and sound like that,” Richards once famously stated. “Everyone else wanted to be Elvis; I wanted to be Scotty.”
Listen to the reckless abandon he uses to back Presley in his second performance at the Louisiana Hayride on August 20, 1955, and you will clearly recognize what Keef and countless others heard on the outset, that unbridled purity that made Moore’s tiny little amp sound like Neil Young’s great wall of Fenders. The strings on his Gibson ES-295 were lightning in a bottle, the spark that ignited the biggest youth movement in American history.
by Ron Hart, Observer Culture | Read more:
Image: Scotty Moore
Friday, July 1, 2016
AI, Apple and Google
In the last couple of years, magic started happening in AI. Techniques started working, or started working much better, and new techniques have appeared, especially around machine learning ('ML'), and when those were applied to some long-standing and important use cases we started getting dramatically better results. For example, the error rates for image recognition, speech recognition and natural language processing have collapsed to close to human rates, at least on some measurements.
So you can say to your phone: 'show me pictures of my dog at the beach' and a speech recognition system turns the audio into text, natural language processing takes the text, works out that this is a photo query and hands it off to your photo app, and your photo app, which has used ML systems to tag your photos with ‘dog’ and 'beach’, runs a database query and shows you the tagged images. Magic.
There are really two things going on here - you’re using voice to fill in a dialogue box for a query, and that dialogue box can run queries that might not have been possible before. Both of these are enabled by machine learning, but they’re built quite separately, and indeed the most interesting part is not the voice but the query. In fact, the important structural change behind being able to ask for ‘Pictures with dogs at the beach’ is not that the computer can find it but that the computer has worked out, itself, how to find it. You give it a million pictures labelled ‘this has a dog in it’ and a million labelled ‘this doesn’t have a dog’ and it works out how to work out what a dog looks like. Now, try that with ‘customers in this data set who were about to churn’, or ‘this network had a security breach’, or ‘stories that people read and shared a lot’. Then try it without labels ('unsupervised' rather than 'supervised' learning).
Today you would spend hours or weeks in data analysis tools looking for the right criteria to find these, and you’d need people doing that work - sorting and resorting that Excel table and eyeballing for the weird result, metaphorically speaking, but with a million rows and a thousand columns. Machine learning offers the promise that a lot of very large and very boring analyses of data can be automated - not just running the search, but working out what the search should be to find the result you want.
That is, the eye-catching demos of speech interfaces or image recognition are just the most visible demos of the underlying techniques, but those have much broader applications - you can also apply them to a keyboard, a music recommendation system, a network security model or a self-driving car. Maybe.
This is clearly a fundamental change for Google. Narrowly, image and speech recognition mean that it will be able to understand questions better and index audio, images and video better. But more importantly, it will answer questions better, and answer questions that it could never really answer before at all. Hence, aswe saw at Google IO, the company is being recentred on these techniques. And of course, all of these techniques will be used in different ways to varying degrees for different use cases, just as AlphaGo uses a range of different techniques. The thing that gets the attention is ‘Google Assistant - a front-end using voice and analysis of your behaviour to try both to capture questions better and address some questions before they’re asked. But that's just the tip of the spear - the real change is in the quality of understanding of the corpus of data that Google has gathered, and in the kind of queries that Google will be able to answer in all sorts of different products. That's really just at the very beginning right now.
The same applies in different ways to Microsoft, which (having missed mobile entirely) is creating cloud-based tools to allow developers to build their own applications on these techniques, and for Facebook (what is the newsfeed if not a machine learning application?), and indeed for IBM. Anyone who handles lots of data for money, or helps other people do it, will change, and there will be a whole bunch of new companies created around this.
On the other hand, while we have magic we do not have HAL 9000 - we do not have a system that is close to human intelligence (so-called 'general AI'). Nor really do we have a good theory as to what that would mean - whether human intelligence is the sum of techniques and ideas we already have, but more, or whether there is something else. Rather, we have a bunch of tools that need to be built and linked together. I can ask Google or Siri to show me pictures of my dog on a beach because Google and Apple have linked together tools to do that, but I can't ask it to book me a restaurant unless they've added an API integration with Opentable. This is the fundamental challenge for Siri, Google Assistant or any chat bot (as I discussed here) - what can you ask?
This takes us to a whole class of jokes often made about what does and does not count as AI in the first place:
I think a foundational point here is Eric Raymond's rule that a computer should 'never ask the user for any information that it can autodetect, copy, or deduce' - especially, here, deduce. One way to see the whole development of computing over the past 50 years is as removing questions that a computer needed to ask, and adding new questions that it could ask. Lots of those things didn't necessarily look like questions as they're presented to the user, but they were, and computers don't ask them anymore:
This takes me to Apple.
Apple has been making computers that ask you fewer questions since 1984, and people have been complaining about that for just as long - one user's question is another user's free choice (something you can see clearly in the contrasts between iOS and Android today). Steve Jobs once said that the interface for iDVD should just have one button: ‘BURN’. It launched Data Detectors in 1997 - a framework that tried to look at text and extract structured data in a helpful way - appointments, phone numbers or addresses. Today you'd use AI techniques to get there, so was that AI? Or a 'bunch of IF statements'? Is there a canonical list of algorithm that count as AI? Does it matter? To a user who can tap on a number to dial instead of copy & pasting, is that a meaningful question?
So you can say to your phone: 'show me pictures of my dog at the beach' and a speech recognition system turns the audio into text, natural language processing takes the text, works out that this is a photo query and hands it off to your photo app, and your photo app, which has used ML systems to tag your photos with ‘dog’ and 'beach’, runs a database query and shows you the tagged images. Magic.
There are really two things going on here - you’re using voice to fill in a dialogue box for a query, and that dialogue box can run queries that might not have been possible before. Both of these are enabled by machine learning, but they’re built quite separately, and indeed the most interesting part is not the voice but the query. In fact, the important structural change behind being able to ask for ‘Pictures with dogs at the beach’ is not that the computer can find it but that the computer has worked out, itself, how to find it. You give it a million pictures labelled ‘this has a dog in it’ and a million labelled ‘this doesn’t have a dog’ and it works out how to work out what a dog looks like. Now, try that with ‘customers in this data set who were about to churn’, or ‘this network had a security breach’, or ‘stories that people read and shared a lot’. Then try it without labels ('unsupervised' rather than 'supervised' learning). Today you would spend hours or weeks in data analysis tools looking for the right criteria to find these, and you’d need people doing that work - sorting and resorting that Excel table and eyeballing for the weird result, metaphorically speaking, but with a million rows and a thousand columns. Machine learning offers the promise that a lot of very large and very boring analyses of data can be automated - not just running the search, but working out what the search should be to find the result you want.
That is, the eye-catching demos of speech interfaces or image recognition are just the most visible demos of the underlying techniques, but those have much broader applications - you can also apply them to a keyboard, a music recommendation system, a network security model or a self-driving car. Maybe.
This is clearly a fundamental change for Google. Narrowly, image and speech recognition mean that it will be able to understand questions better and index audio, images and video better. But more importantly, it will answer questions better, and answer questions that it could never really answer before at all. Hence, aswe saw at Google IO, the company is being recentred on these techniques. And of course, all of these techniques will be used in different ways to varying degrees for different use cases, just as AlphaGo uses a range of different techniques. The thing that gets the attention is ‘Google Assistant - a front-end using voice and analysis of your behaviour to try both to capture questions better and address some questions before they’re asked. But that's just the tip of the spear - the real change is in the quality of understanding of the corpus of data that Google has gathered, and in the kind of queries that Google will be able to answer in all sorts of different products. That's really just at the very beginning right now.
The same applies in different ways to Microsoft, which (having missed mobile entirely) is creating cloud-based tools to allow developers to build their own applications on these techniques, and for Facebook (what is the newsfeed if not a machine learning application?), and indeed for IBM. Anyone who handles lots of data for money, or helps other people do it, will change, and there will be a whole bunch of new companies created around this.
On the other hand, while we have magic we do not have HAL 9000 - we do not have a system that is close to human intelligence (so-called 'general AI'). Nor really do we have a good theory as to what that would mean - whether human intelligence is the sum of techniques and ideas we already have, but more, or whether there is something else. Rather, we have a bunch of tools that need to be built and linked together. I can ask Google or Siri to show me pictures of my dog on a beach because Google and Apple have linked together tools to do that, but I can't ask it to book me a restaurant unless they've added an API integration with Opentable. This is the fundamental challenge for Siri, Google Assistant or any chat bot (as I discussed here) - what can you ask?
This takes us to a whole class of jokes often made about what does and does not count as AI in the first place:
- "Is that AI or just a bunch of IF statements?"
- "Every time we figure out a piece of it [AI], it stops being magical; we say, 'Oh, that's just a computation
- "AI is whatever isn't been done yet"
I think a foundational point here is Eric Raymond's rule that a computer should 'never ask the user for any information that it can autodetect, copy, or deduce' - especially, here, deduce. One way to see the whole development of computing over the past 50 years is as removing questions that a computer needed to ask, and adding new questions that it could ask. Lots of those things didn't necessarily look like questions as they're presented to the user, but they were, and computers don't ask them anymore:
- Where do you want to save this file?
- Do you want to defragment your hard disk?
- What interrupt should your sound card use?
- Do you want to quit this application?
- Which photos do you want to delete to save space?
- Which of these 10 search criteria do you want to fill in to run a web search?
- What's the PIN for your phone?
- What kind of memory do you want to run this program in?
- What's the right way to spell that word?
- What number is this page?
- Which of your friends' updates do you want to see?
This takes me to Apple.
Apple has been making computers that ask you fewer questions since 1984, and people have been complaining about that for just as long - one user's question is another user's free choice (something you can see clearly in the contrasts between iOS and Android today). Steve Jobs once said that the interface for iDVD should just have one button: ‘BURN’. It launched Data Detectors in 1997 - a framework that tried to look at text and extract structured data in a helpful way - appointments, phone numbers or addresses. Today you'd use AI techniques to get there, so was that AI? Or a 'bunch of IF statements'? Is there a canonical list of algorithm that count as AI? Does it matter? To a user who can tap on a number to dial instead of copy & pasting, is that a meaningful question?
by Benedict Evans | Read more:
Image: via:
Everything You Know About Surviving Rip Currents Is Wrong (Maybe)
Conventional wisdom says that Jamie MacMahan was doing everything right when, about a decade ago, he found himself caught in a rip current while swimming off the coast of Monterey, California. Rips flow seaward, out to deep water, so beach access signs across the country advise swimmers to paddle parallel to the beach to escape them. The savage, dread-inducing flows kill more beachgoers each year than any other threat and MacMahan, a professor of oceanography and a strong swimmer, was following the “swim parallel” gospel, paddling steadily. But as he thrashed in the cold Pacific, the rip refused to relent. “I thought, ‘That’s interesting,’” MacMahan says.
MacMahan, it’s important to note, had done this to himself. A rip current expert at the Naval Postgraduate School in Monterey, he had volunteered to subject himself to the rip for a safety video the National Oceanic and Atmospheric Organization was filming. With plenty of experience, he wasn’t in serious danger. “But as I was swimming parallel to the shore, left and right, I noticed that it was easier to swim one direction more than the other,” MacMahan says. The safety guidelines he was promoting—the life-saving advice we tell the millions of Americans who flock to the beach each summer—he thought, could be wrong.
In the last five years, MacMahan’s research has upended the field of rip current studies. Since that initial experience in Monterey, he’s used GPS devices to meticulously track nearshore currents in the U.S., England, and France, and has jumped into rips around the world. Rips can form on any beach, MacMahan says, and swimmers usually don’t know a rip’s present until they’re in its clutches. Panicked victims often try to swim directly back to shore—against the powerful offshore flow. Swimmers familiar with rips might try swimming parallel to escape. But MacMahan’s research suggests doing the unthinkable: giving in and going with the flow.
Eighty to 90 percent of rips MacMahan has studied flow in huge circles, from the shallows, out through the breakers and back again, every few minutes. A swimmer stuck in a circulating rip has no way of knowing which way the current is flowing. That means that by swimming parallel to the shore—something signs at nearly every popular beach in the country advise—the swimmer has a 50/50 chance of paddling against the deadly current.
“If you can relax—and it’s a long time, for maybe three minutes—you’re generally going to float back to the beach,” MacMahan says.
It’s a radically simple finding—one that challenges our primordial instincts and everything we think we know about beach safety. The discovery, which MacMahan published in Marine Geology in 2010 and calls rip current “circulation,” is still contentious six years later. His peer-reviewed findings have dramatically changed the way Australia tells its citizens how to survive this menace. But at home, MacMahan’s work is considerably more controversial and his research has opened a gaping divide in the sleepy rip current field.
“The reaction to Jamie’s findings has polarized the community,” says Rob Brander, a prominent rip researcher. For some leaders in the field, MacMahan’s recommendation to simply float through a rip current is, at best, an idea to be ignored and dismissed; at worst, though, the advice is potentially deadly.
MacMahan, it’s important to note, had done this to himself. A rip current expert at the Naval Postgraduate School in Monterey, he had volunteered to subject himself to the rip for a safety video the National Oceanic and Atmospheric Organization was filming. With plenty of experience, he wasn’t in serious danger. “But as I was swimming parallel to the shore, left and right, I noticed that it was easier to swim one direction more than the other,” MacMahan says. The safety guidelines he was promoting—the life-saving advice we tell the millions of Americans who flock to the beach each summer—he thought, could be wrong.In the last five years, MacMahan’s research has upended the field of rip current studies. Since that initial experience in Monterey, he’s used GPS devices to meticulously track nearshore currents in the U.S., England, and France, and has jumped into rips around the world. Rips can form on any beach, MacMahan says, and swimmers usually don’t know a rip’s present until they’re in its clutches. Panicked victims often try to swim directly back to shore—against the powerful offshore flow. Swimmers familiar with rips might try swimming parallel to escape. But MacMahan’s research suggests doing the unthinkable: giving in and going with the flow.
Eighty to 90 percent of rips MacMahan has studied flow in huge circles, from the shallows, out through the breakers and back again, every few minutes. A swimmer stuck in a circulating rip has no way of knowing which way the current is flowing. That means that by swimming parallel to the shore—something signs at nearly every popular beach in the country advise—the swimmer has a 50/50 chance of paddling against the deadly current.
“If you can relax—and it’s a long time, for maybe three minutes—you’re generally going to float back to the beach,” MacMahan says.
It’s a radically simple finding—one that challenges our primordial instincts and everything we think we know about beach safety. The discovery, which MacMahan published in Marine Geology in 2010 and calls rip current “circulation,” is still contentious six years later. His peer-reviewed findings have dramatically changed the way Australia tells its citizens how to survive this menace. But at home, MacMahan’s work is considerably more controversial and his research has opened a gaping divide in the sleepy rip current field.
“The reaction to Jamie’s findings has polarized the community,” says Rob Brander, a prominent rip researcher. For some leaders in the field, MacMahan’s recommendation to simply float through a rip current is, at best, an idea to be ignored and dismissed; at worst, though, the advice is potentially deadly.
by David Ferry, Outside | Read more:
Image: Todd Quackenbush/Unsplash
Teen Created a Robot Lawyer App That Just Overturned 160,000 Parking Tickets
[ed. I can't vouch for this or its creator's true intentions (see below), but anything that's basically altruistic in our get rich quick, profit-driven world should get some kind of recognition.]
Got a bullshit parking ticket? Now you can appeal it in less than a minute. The new chatbot tool, DoNotPay, uses previously successful appeal letters to draw up a customized template, allowing users to avoid courts, legal fees, stress, and having to use a lawyer.
So far, the free app has overturned 160,000 parking tickets in London and New York. With a success rate of 64%, DoNotPay has appealed $4 million in parking fines in just two cities in only nine months of operation. In 2014, New York City collected $546 million in revenue from parking tickets.
Stanford freshman Joshua Bowder created the app after spending an exorbitant amount of time crafting his own appeals for parking tickets. He read thousands of pages of documents related to parking tickets released under the Freedom of Information Act and consulted a traffic lawyer. Then, using PHP and Javascript, he created a conversation algorithm that aggregates keywords, pronouns, and word order. Like many chatbots, Browder’s app becomes more intelligent each time it is used.
DoNotPay is not commercial and Josh plans to keep it that way. In an interview with Anti-Media, Josh said he was driven by a sense of social justice and a desire to help vulnerable people who are exploited by policing-for-profit schemes. Josh also wants to use technology like artificial intelligence for humanitarian purposes.
He finds it “irritating and disappointing” that bots are usually created for vapid commercial uses. In reality, he says, algorithmic intelligence and chatbots are a “humanitarian goldmine.”
DoNotPay also assists with delayed or canceled flights, payment-protection insurance (PPI) claims, and even legally disclosing an HIV-positive health status.
Josh describes his creation as “the first robot lawyer.” People are describing him as the “Robin Hood of the Internet.”
“If it is one day possible for any citizen to get the same standard of legal representation as a billionaire,” Browder says,“how can that not be a good thing?”
Got a bullshit parking ticket? Now you can appeal it in less than a minute. The new chatbot tool, DoNotPay, uses previously successful appeal letters to draw up a customized template, allowing users to avoid courts, legal fees, stress, and having to use a lawyer.
So far, the free app has overturned 160,000 parking tickets in London and New York. With a success rate of 64%, DoNotPay has appealed $4 million in parking fines in just two cities in only nine months of operation. In 2014, New York City collected $546 million in revenue from parking tickets.
Stanford freshman Joshua Bowder created the app after spending an exorbitant amount of time crafting his own appeals for parking tickets. He read thousands of pages of documents related to parking tickets released under the Freedom of Information Act and consulted a traffic lawyer. Then, using PHP and Javascript, he created a conversation algorithm that aggregates keywords, pronouns, and word order. Like many chatbots, Browder’s app becomes more intelligent each time it is used.DoNotPay is not commercial and Josh plans to keep it that way. In an interview with Anti-Media, Josh said he was driven by a sense of social justice and a desire to help vulnerable people who are exploited by policing-for-profit schemes. Josh also wants to use technology like artificial intelligence for humanitarian purposes.
He finds it “irritating and disappointing” that bots are usually created for vapid commercial uses. In reality, he says, algorithmic intelligence and chatbots are a “humanitarian goldmine.”
DoNotPay also assists with delayed or canceled flights, payment-protection insurance (PPI) claims, and even legally disclosing an HIV-positive health status.
Josh describes his creation as “the first robot lawyer.” People are describing him as the “Robin Hood of the Internet.”
“If it is one day possible for any citizen to get the same standard of legal representation as a billionaire,” Browder says,“how can that not be a good thing?”
by Jake Anderson, Anti-Media | Read more:
Image: uncredited
Government Under Review
Like many good arguments, this one started over a stiff drink. An Earl Grey MarTEAni, to be precise.
In January 2010, Nathalie Louissaint, a New York City health inspector, visited Pegu Club, an upscale cocktail bar. She watched as the bartender mixed the signature tea-infused drink. Borrowing a technique from the nineteenth century, the bartender added raw egg whites, which give the drink a silky body and an alluring layer of foam. Louissaint decided that the raw egg warning on the menu was insufficient and cited the bar for a health code violation.
The citation outraged many. Paul Clarke, a Seattle-based food writer, was perplexed by the department’s rigid position on raw eggs, writing on the website Serious Eats, “Does this mean the health department will begin targeting restaurants that serve raw eggs in a Caesar salad?” Others decried the health department’s seeming mandate to use pasteurized eggs, but those, said Pegu Club owner Audrey Sanders, “impart this really funky wet-diaper nose.” One bartender, who insisted on anonymity for fear of reprisal, told the New York Times, “If they make it illegal to serve egg-white drinks, that would be Hurricane Katrina for us.” In response to the uproar, the health department overruled the inspector.
This confusion is no outlier. Nationwide, implementation of health codes varies dramatically across inspectors and health departments. In Seattle, two inspectors observed Caesar salad dressing prepared with raw (unpasteurized) eggs in the same restaurant, but disagreed about whether to cite a violation. Contrary to New York City health department guidelines, New York State’s website doesn’t mention menu warnings, instead admonishing, “Consider using commercially pasteurized eggs in recipes that use eggs or consider removing the item from your menu.” The Centers for Disease Control and Prevention (CDC) document that 80 percent of restaurants nonetheless use unpasteurized eggs.
When it comes down to it, the marTEAni fight is not so much about eggs as it is an endemic challenge across government. From airport security checkpoints and routine traffic stops to home construction permits, citizens and government interact frequently through individual officials. At times, the decisions of these frontline government officials can seem disturbingly arbitrary.
A bar can always take a drink off its menu, but sometimes the arbitrariness can have more serious impact. In 2013 the Administrative Conference of the United States reported that administrative law judges grant Social Security Disability claims at rates ranging from 4 percent to 98 percent. In asylum adjudication, New York immigration judges vary in their grant rates from 6 percent to 91 percent when cases are assigned irrespective of merits, leading to a denunciation of the process as “refugee roulette.” A study of Illinois child-welfare case managers found substantial differences in decisions to place children in foster care based on allegations of abuse or neglect. It is no wonder that scholars assail the child-welfare system as a form of institutional “chaos, oppression, and tragic ineffectiveness.” In nuclear safety, violation-detection rates can vary from less than 10 percent to more than 60 percent depending on the inspector. The regulatory requirements are so complex that one nuclear official conceded, “Nondetection is endemic.”
Inconsistency breeds mistrust. A city analyst in New York described the city’s restaurant inspection system as “arbitrary” and concluded, “If we can’t trust the Health Department to provide real scientific data . . . then we can’t trust any agency.” Businesses feel this too. An owner of a fast-food chain with many locations across Washington state observed sharp differences in how individual restaurants were scored and how the same restaurant was scored over time, despite his chain’s uniform food-safety protocol: “We always thought we were doing a great job in putting safety first; but it turns out in many, if not most, cases, inspectors were either not being as thorough as they could have been or were only verbally coaching” rather than writing violations. One Virginia bartender, responding to the Pegu Club episode, said, “I’m not 100 percent sure what the law is.” At a staff meeting in King County, Washington, health inspectors expressed similar misgivings. They hoped for better consistency in order to build “credibility and trust.”
The pervasiveness of these challenges leads some to point fingers, some to throw up their hands, and others to bemoan government altogether. If you are on the right, blame public sector unions, civil service protections, or listless bureaucrats. If you are on the left, blame underfunding, deregulation, or the lack of federal oversight. Governments generally cannot resolve these underlying ideological battles, but they must find ways to address the consistency of frontline decision making nonetheless. The question is, how?
The Peer Review Experiment
One possible solution is peer review. If frontline government officials could review and deliberate over each other’s work, the quality and consistency of decision making might improve. While isolated examples of such peer review exist, we have regrettably little systematic evidence of peer review’s effectiveness in the public sector. The reason is understandable. Due to perceived costs, logistics, and ethical and political concerns, rigorous experiments can be difficult to design and implement when it comes to regulation.
Beginning in 2014, we designed a randomized, controlled trial to test the effectiveness of peer review with the food safety staff of King County, where Seattle is located. Half of the inspection staff was randomly assigned to engage in peer review. For sixteen weeks, these inspectors spent one day per week with a randomly selected fellow inspector, taking turns conducting inspections and independently scoring health code violations. We then used information from these peer inspections to identify and train for violations that cause the most confusion.
The results were remarkable.We discovered that, when observing identical conditions in restaurants, health inspectors disagreed nearly 60 percent of the time.
by Daniel E. Ho and Becky Elias, Boston Review | Read more:
In January 2010, Nathalie Louissaint, a New York City health inspector, visited Pegu Club, an upscale cocktail bar. She watched as the bartender mixed the signature tea-infused drink. Borrowing a technique from the nineteenth century, the bartender added raw egg whites, which give the drink a silky body and an alluring layer of foam. Louissaint decided that the raw egg warning on the menu was insufficient and cited the bar for a health code violation.
The citation outraged many. Paul Clarke, a Seattle-based food writer, was perplexed by the department’s rigid position on raw eggs, writing on the website Serious Eats, “Does this mean the health department will begin targeting restaurants that serve raw eggs in a Caesar salad?” Others decried the health department’s seeming mandate to use pasteurized eggs, but those, said Pegu Club owner Audrey Sanders, “impart this really funky wet-diaper nose.” One bartender, who insisted on anonymity for fear of reprisal, told the New York Times, “If they make it illegal to serve egg-white drinks, that would be Hurricane Katrina for us.” In response to the uproar, the health department overruled the inspector.This confusion is no outlier. Nationwide, implementation of health codes varies dramatically across inspectors and health departments. In Seattle, two inspectors observed Caesar salad dressing prepared with raw (unpasteurized) eggs in the same restaurant, but disagreed about whether to cite a violation. Contrary to New York City health department guidelines, New York State’s website doesn’t mention menu warnings, instead admonishing, “Consider using commercially pasteurized eggs in recipes that use eggs or consider removing the item from your menu.” The Centers for Disease Control and Prevention (CDC) document that 80 percent of restaurants nonetheless use unpasteurized eggs.
When it comes down to it, the marTEAni fight is not so much about eggs as it is an endemic challenge across government. From airport security checkpoints and routine traffic stops to home construction permits, citizens and government interact frequently through individual officials. At times, the decisions of these frontline government officials can seem disturbingly arbitrary.
A bar can always take a drink off its menu, but sometimes the arbitrariness can have more serious impact. In 2013 the Administrative Conference of the United States reported that administrative law judges grant Social Security Disability claims at rates ranging from 4 percent to 98 percent. In asylum adjudication, New York immigration judges vary in their grant rates from 6 percent to 91 percent when cases are assigned irrespective of merits, leading to a denunciation of the process as “refugee roulette.” A study of Illinois child-welfare case managers found substantial differences in decisions to place children in foster care based on allegations of abuse or neglect. It is no wonder that scholars assail the child-welfare system as a form of institutional “chaos, oppression, and tragic ineffectiveness.” In nuclear safety, violation-detection rates can vary from less than 10 percent to more than 60 percent depending on the inspector. The regulatory requirements are so complex that one nuclear official conceded, “Nondetection is endemic.”
Inconsistency breeds mistrust. A city analyst in New York described the city’s restaurant inspection system as “arbitrary” and concluded, “If we can’t trust the Health Department to provide real scientific data . . . then we can’t trust any agency.” Businesses feel this too. An owner of a fast-food chain with many locations across Washington state observed sharp differences in how individual restaurants were scored and how the same restaurant was scored over time, despite his chain’s uniform food-safety protocol: “We always thought we were doing a great job in putting safety first; but it turns out in many, if not most, cases, inspectors were either not being as thorough as they could have been or were only verbally coaching” rather than writing violations. One Virginia bartender, responding to the Pegu Club episode, said, “I’m not 100 percent sure what the law is.” At a staff meeting in King County, Washington, health inspectors expressed similar misgivings. They hoped for better consistency in order to build “credibility and trust.”
The pervasiveness of these challenges leads some to point fingers, some to throw up their hands, and others to bemoan government altogether. If you are on the right, blame public sector unions, civil service protections, or listless bureaucrats. If you are on the left, blame underfunding, deregulation, or the lack of federal oversight. Governments generally cannot resolve these underlying ideological battles, but they must find ways to address the consistency of frontline decision making nonetheless. The question is, how?
The Peer Review Experiment
One possible solution is peer review. If frontline government officials could review and deliberate over each other’s work, the quality and consistency of decision making might improve. While isolated examples of such peer review exist, we have regrettably little systematic evidence of peer review’s effectiveness in the public sector. The reason is understandable. Due to perceived costs, logistics, and ethical and political concerns, rigorous experiments can be difficult to design and implement when it comes to regulation.
Beginning in 2014, we designed a randomized, controlled trial to test the effectiveness of peer review with the food safety staff of King County, where Seattle is located. Half of the inspection staff was randomly assigned to engage in peer review. For sixteen weeks, these inspectors spent one day per week with a randomly selected fellow inspector, taking turns conducting inspections and independently scoring health code violations. We then used information from these peer inspections to identify and train for violations that cause the most confusion.
The results were remarkable.We discovered that, when observing identical conditions in restaurants, health inspectors disagreed nearly 60 percent of the time.
by Daniel E. Ho and Becky Elias, Boston Review | Read more:
Image: Even More Bureaucrats (1993) by Synnøve Anker Aurdal / photo by Bosc d'Anjou
Thursday, June 30, 2016
Subscribe to:
Posts (Atom)