Koi Champagne
Original Design for the 'Recycling Symbol' • Gary Anderson (Right)
Amazon gift card in Amazon box
Free Wifi/100+ Beers
Bulgari Octo Finissimo Ultra
WW1 Memorial
Ulster Wildlife logo – badger and fish
Friday, June 7, 2024
Japan Runs on Vending Machines. It’s About to Break Millions of Them.
The vending machine at Hiroshi Nishitani’s Tokyo ramen restaurant has been reliable for a decade. Customers feed it money, and it prints out their orders while he makes fresh noodles in the kitchen. The food is served within minutes once the customer delivers the order to the pair of cooks at the counter.
But the machine’s days are numbered. Japan is set to introduce a new set of bank notes this summer, something it does every 20 years or so to thwart counterfeiters. The machine, already too old to accept recent coin designs, won’t accept the new bills, Mr. Nishitani said.
“There’s nothing wrong with the vending machine,” he said, expressing frustration with the need to buy an expensive new unit compatible with the new notes.
All over Japan, restaurants, cafeterias, bathhouses and other businesses are facing a similar prospect. The country has 4.1 million vending machines, according to Nikkei Compass, a database for industry reports. Many of them will be obsolete once the new 1,000-, 5,000- and 10,000-yen bills roll out in July featuring hologram technology.
In Japan, where the work force is shrinking, the machines reduce the need for cashiers and servers. Among the most reliant on the machines are ramen shops, which serve one of the Japanese working class’s favorite, most affordable meals. (...)
On a recent Tuesday afternoon, students from a nearby university filed in for a late lunch at Mr. Nishitani’s nine-seat shop, Goumen Maruko.
He and his three employees sell about 100 dishes a day. Each is priced under 1,000 yen, or roughly $6.50. The most popular dish is a $5 Jiro-style bowl: noodles with a mountain of vegetables and clumps of pork fat soaked in a steaming broth of pork and chicken. The most expensive meals, which come in larger portions, cost about $6.20.
To defray the cost of upgrading or replacing vending machines, some municipalities offer subsidies, but most of the cost will fall on shop owners. A new machine can cost two million yen, or about $13,000, said Masahiro Kawamura, a sales manager at Elcom, a Tokyo company that sells vending machines that dispense tickets.
Yoshihiro Serizawa, who runs a soba shop in Tokyo, said he spent about $19,000 on his new machine, which also accepts cashless payment — “a huge financial burden.” The amount is equivalent to more than 6,000 orders of his most popular dish: soba with mixed vegetables and seafood tempura, which costs just over $3. (...)
Among ramen chefs, the widely accepted limit for a bowl of ramen is known as the “1,000-yen wall.”
“I really don’t want to raise the price any further,” Mr. Nishitani said.
When Japan released its last set of bills in 2004, modifying the vending machines and issuing 10 billion new bank notes cost hundreds of millions of dollars. Demand was so high that one manufacturer near Osaka, called Glory, saw its net income triple, according to an annual report.
Transitioning to new machines could take years.
by Kiuko Notoya and John Yoon, NY Times | Read more:
Every vending machine is a battleground. Profits are ruthlessly haggled over. Competition for spots is intense. Broadly speaking, the vending game is built on deals between operators (who own machines and have the skills to install them, fix them, constantly fill them with fats and sugars) and site owners (who have the rights to advantageous pieces of land). Either a machine is placed on private property – say, a factory, where the site owner surrenders profits to the operator in return for keeping a workforce fed and present – or, a machine is placed somewhere public, inside a teeming airport, for instance. Here the site owner will expect a cut of each item sold, anywhere from 10% to 30%. (...)
If Wakefield is the literal birthplace of the automated sale, Japan is the spiritual home. There they vend umbrellas, ice-cream, fancy dress. In Nagasaki, there is a machine that sells the edible chrysalises of silkworms. You can vend fresh tomatoes in Kobe and, in Tatsuno, fresh oysters. In Osaka, during the summer of 2021, a Japanese airline had started selling tickets to mystery destinations from a machine that asked 5,000 yen, or £30, per turn. This concept was so popular that 10,000 tickets were sold by the end of 2021 and the airline put duplicate machines in Tokyo, Nagoya and Fukuoka.
At the last formal count, conducted by a trade body in December 2020, there were 2.7m vending machines spread around Japan: one for every 46 citizens, the highest density anywhere. Affection for vending is so pronounced that a machine selling something unique may become the subject of fascination, even pilgrimage."
“There’s nothing wrong with the vending machine,” he said, expressing frustration with the need to buy an expensive new unit compatible with the new notes.
All over Japan, restaurants, cafeterias, bathhouses and other businesses are facing a similar prospect. The country has 4.1 million vending machines, according to Nikkei Compass, a database for industry reports. Many of them will be obsolete once the new 1,000-, 5,000- and 10,000-yen bills roll out in July featuring hologram technology.
In Japan, where the work force is shrinking, the machines reduce the need for cashiers and servers. Among the most reliant on the machines are ramen shops, which serve one of the Japanese working class’s favorite, most affordable meals. (...)
On a recent Tuesday afternoon, students from a nearby university filed in for a late lunch at Mr. Nishitani’s nine-seat shop, Goumen Maruko.
He and his three employees sell about 100 dishes a day. Each is priced under 1,000 yen, or roughly $6.50. The most popular dish is a $5 Jiro-style bowl: noodles with a mountain of vegetables and clumps of pork fat soaked in a steaming broth of pork and chicken. The most expensive meals, which come in larger portions, cost about $6.20.
To defray the cost of upgrading or replacing vending machines, some municipalities offer subsidies, but most of the cost will fall on shop owners. A new machine can cost two million yen, or about $13,000, said Masahiro Kawamura, a sales manager at Elcom, a Tokyo company that sells vending machines that dispense tickets.
Yoshihiro Serizawa, who runs a soba shop in Tokyo, said he spent about $19,000 on his new machine, which also accepts cashless payment — “a huge financial burden.” The amount is equivalent to more than 6,000 orders of his most popular dish: soba with mixed vegetables and seafood tempura, which costs just over $3. (...)
Among ramen chefs, the widely accepted limit for a bowl of ramen is known as the “1,000-yen wall.”
“I really don’t want to raise the price any further,” Mr. Nishitani said.
When Japan released its last set of bills in 2004, modifying the vending machines and issuing 10 billion new bank notes cost hundreds of millions of dollars. Demand was so high that one manufacturer near Osaka, called Glory, saw its net income triple, according to an annual report.
Transitioning to new machines could take years.
by Kiuko Notoya and John Yoon, NY Times | Read more:
Image: Noriko Hayashi
[ed. Vending machine culture in Japan is so unique. For a detailed explanation of why (and what it takes to run an industry like this - leasing; placement; restocking; repairs for heating, chilling, mixing components, etc.), see this fascinating essay: A day in the life of (almost) every vending machine in the world (Guardian):]
[ed. Vending machine culture in Japan is so unique. For a detailed explanation of why (and what it takes to run an industry like this - leasing; placement; restocking; repairs for heating, chilling, mixing components, etc.), see this fascinating essay: A day in the life of (almost) every vending machine in the world (Guardian):]
***
"He led us into a control room that had large screens mounted on the walls and employees arranged Nasa-style, facing screens on which stationary dots and travelling arrows identified thousands of vending machines and the technicians who roved between them. We watched a live ticking record of the day’s sales activity, north to Aberdeen, south to the Isle of Wight. A couple of quick clicks on a technician’s computer and we were marvelling at the snacking history of a loyal, I would say fanatical, Broderick customer in Manchester, someone who must have been sourcing two full meals a day from behind glass. While Johnny Brod made a note to slip this customer a thank-you tenner via the app, I asked his team if they’d be able to find the record of my midnight Doritos. A few keyboard taps and there it was. (...)Every vending machine is a battleground. Profits are ruthlessly haggled over. Competition for spots is intense. Broadly speaking, the vending game is built on deals between operators (who own machines and have the skills to install them, fix them, constantly fill them with fats and sugars) and site owners (who have the rights to advantageous pieces of land). Either a machine is placed on private property – say, a factory, where the site owner surrenders profits to the operator in return for keeping a workforce fed and present – or, a machine is placed somewhere public, inside a teeming airport, for instance. Here the site owner will expect a cut of each item sold, anywhere from 10% to 30%. (...)
If Wakefield is the literal birthplace of the automated sale, Japan is the spiritual home. There they vend umbrellas, ice-cream, fancy dress. In Nagasaki, there is a machine that sells the edible chrysalises of silkworms. You can vend fresh tomatoes in Kobe and, in Tatsuno, fresh oysters. In Osaka, during the summer of 2021, a Japanese airline had started selling tickets to mystery destinations from a machine that asked 5,000 yen, or £30, per turn. This concept was so popular that 10,000 tickets were sold by the end of 2021 and the airline put duplicate machines in Tokyo, Nagoya and Fukuoka.
At the last formal count, conducted by a trade body in December 2020, there were 2.7m vending machines spread around Japan: one for every 46 citizens, the highest density anywhere. Affection for vending is so pronounced that a machine selling something unique may become the subject of fascination, even pilgrimage."
Thursday, June 6, 2024
Catching Crumbs From The Table
In the face of metahuman science, humans have become metascientists. [ed. Fiction]
It has been 25 years since a report of original research was last submitted to our editors for publication, making this an appropriate time to revisit the question that was so widely debated then: what is the role of human scientists in an age when the frontiers of scientific inquiry have moved beyond the comprehensibility of humans?
No doubt many of our subscribers remember reading papers whose authors were the first individuals ever to obtain the results they described. But as metahumans began to dominate experimental research, they increasingly made their findings available only via DNT (digital neural transfer), leaving journals to publish second-hand accounts translated into human language.
Without DNT, humans could not fully grasp earlier developments nor effectively utilize the new tools needed to conduct research, while metahumans continued to improve DNT and rely on it even more. Journals for human audiences were reduced to vehicles of popularization, and poor ones at that, as even the most brilliant humans found themselves puzzled by translations of the latest findings.
No one denies the many benefits of metahuman science, but one of its costs to human researchers was the realization that they would probably never make an original contribution to science again. Some left the field altogether, but those who stayed shifted their attentions away from original research and toward hermeneutics: interpreting the scientific work of metahumans.
Textual hermeneutics became popular first, since there were already terabytes of metahuman publications whose translations, although cryptic, were presumably not entirely inaccurate. Deciphering these texts bears little resemblance to the task performed by traditional palaeographers, but progress continues: recent experiments have validated the Humphries decipherment of decade-old publications on histocompatibility genetics.
The availability of devices based on metahuman science gave rise to artefact hermeneutics. Scientists began attempting to ‘reverse engineer’ these artefacts, their goal being not to manufacture competing products, but simply to understand the physical principles underlying their operation. The most common technique is the crystallographic analysis of nanoware appliances, which frequently provides us with new insights into mechanosynthesis. (...)
The question is, are these worthwhile undertakings for scientists? Some call them a waste of time, likening them to a Native American research effort into bronze smelting when steel tools of European manufacture are readily available. This comparison might be more apt if humans were in competition with metahumans, but in today's economy of abundance there is no evidence of such competition. In fact, it is important to recognize that — unlike most previous low-technology cultures confronted with a high-technology one — humans are in no danger of assimilation or extinction.
There is still no way to augment a human brain into a metahuman one; the Sugimoto gene therapy must be performed before the embryo begins neurogenesis in order for a brain to be compatible with DNT. This lack of an assimilation mechanism means that human parents of a metahuman child face a difficult choice: to allow their child DNT interaction with metahuman culture, and watch him or her grow incomprehensible to them; or else restrict access to DNT during the child's formative years, which to a metahuman is deprivation like that suffered by Kaspar Hauser. It is not surprising that the percentage of human parents choosing the Sugimoto gene therapy for their children has dropped almost to zero in recent years.
As a result, human culture is likely to survive well into the future, and the scientific tradition is a vital part of that culture. Hermeneutics is a legitimate method of scientific inquiry and increases the body of human knowledge just as original research did. Moreover, human researchers may discern applications overlooked by metahumans, whose advantages tend to make them unaware of our concerns.
For example, imagine if research offered hope of a different intelligence-enhancing therapy, one that would allow individuals to gradually ‘upgrade’ their minds to a level equivalent to that of a metahuman. Such a therapy would offer a bridge across what has become the greatest cultural divide in our species' history, yet it might not even occur to metahumans to explore it; that possibility alone justifies the continuation of human research.
by Ted Chiang, Nature | Read more:
Image: JACEY
[ed. I've been a big fan of Ted for a long time now and have all his books of short stories. Besides the example above, here's another one: The Great Silence (Electric Lit); and the post following this one: The Lifecycle of Software Objects (Subteranian Press). Finally, see also: Interview: Ted Chiang (transcript from the Ezra Klein Show podcast/NYT):]
TED CHIANG: Well, in terms of at what point does that happen, it’s unclear, but it’s a very long ways from us right now. With regard to the question of, will we create machines that are moral agents, I would say that we can think about that in three different questions. One is, can we do so? Second is, will we do so? And the third one is, should we do so?
I think it is entirely possible for us to build machines that are moral agents. Because I think there’s a sense in which human beings are very complex machines and we are moral agents, which means that there are no physical laws preventing a machine from being a moral agent. And so there’s no obstacle that, in principle, would prevent us from building something like that, although it might take us a very, very long time to get there.
As for the question of, will we do so, if you had asked me, like, 10 or 15 years ago, I would have said, we probably won’t do it, simply because, to me, it seems like it’s way more trouble than it’s worth. In terms of expense, it would be on the order of magnitude of the Apollo program. And it is not at all clear to me that there’s any good reason for undertaking such a thing. However, if you ask me now, I would say like, well, OK, we clearly have obscenely wealthy people who can throw around huge sums of money at whatever they want basically on a whim. So maybe one of them will wind up funding a program to create machines that are conscious and that are moral agents.
However, I should also note that I don’t believe that any of the current big A.I. research programs are on the right track to create a conscious machine. I don’t think that’s what any of them are trying to do. So then as for the third question of, should we do so, should we make machines that are conscious and that are moral agents, to that, my answer is, no, we should not. Because long before we get to the point where a machine is a moral agent, we will have machines that are capable of suffering.
Suffering precedes moral agency in sort of the developmental ladder. Dogs are not moral agents, but they are capable of experiencing suffering. Babies are not moral agents yet, but they have the clear potential to become so. And they are definitely capable of experiencing suffering. And the closer that an entity gets to being a moral agent, the more that it’s suffering, it’s deserving of consideration, the more we should try and avoid inflicting suffering on it. So in the process of developing machines that are conscious and moral agents, we will be inevitably creating billions of entities that are capable of suffering. And we will inevitably inflict suffering on them. And that seems to me clearly a bad idea.
EZRA KLEIN: But wouldn’t they also be capable of pleasure? I mean, that seems to me to raise an almost inversion of the classic utilitarian thought experiment. If we can create these billions of machines that live basically happy lives that don’t hurt anybody and you can copy them for almost no marginal dollar, isn’t it almost a moral imperative to bring them into existence so they can lead these happy machine lives?
TED CHIANG: I think that it will be much easier to inflict suffering on them than to give them happy fulfilled lives. And given that they will start out as something that resembles ordinary software, something that is nothing like a living being, we are going to treat them like crap. The way that we treat software right now, if, at some point, software were to gain some vague glimmer of sentience, of the ability to perceive, we would be inflicting uncountable amounts of suffering on it before anyone paid any attention to them.
Because it’s hard enough to give legal protections to human beings who are absolutely moral agents. We have relatively few legal protections for animals who, while they are not moral agents, are capable of suffering. And so animals experience vast amounts of suffering in the modern world. And animals, we know that they suffer. There are many animals that we love, that we really, really love. Yet, there’s vast animal suffering. So there is no software that we love. So the way that we will wind up treating software, again, assuming that software ever becomes conscious, they will inevitably fall lower on the ladder of consideration. So we will treat them worse than we treat animals. And we treat animals pretty badly.
EZRA KLEIN: I think this is actually a really provocative point. So I don’t know if you’re a Yuval Noah Harari reader. But he often frames his fear of artificial intelligence as simply that A.I. will treat us the way we treat animals. And we treat animals, as you say, unbelievably terribly. But I haven’t really thought about the flip of that, that maybe the danger is that we will simply treat A.I. like we treat animals. And given the moral consideration we give animals, whose purpose we believe to be to serve us for food or whatever else it may be, that we are simply opening up almost unimaginable vistas of immorality and cruelty that we could inflict pretty heedlessly, and that given our history, there’s no real reason to think we won’t. That’s grim.
TED CHIANG: It is grim, but I think that it is by far the more likely scenario. I think the scenario that, say, Yuval Noah Harari is describing, where A.I.’s treat us like pets, that idea assumes that it’ll be easy to create A.I.’s who are vastly smarter than us, that basically, the initial A.I.’s will go from software, which is not a moral agent and not intelligent at all. And then the next thing that will happen will be software which is super intelligent and also has volition.
Whereas I think that we’ll proceed in the other direction, that right now, software is simpler than an amoeba. And eventually, we will get software which is comparable to an amoeba. And eventually, we’ll get software which is comparable to an ant, and then software that is comparable to a mouse, and then software that’s comparable to a dog, and then software that is comparable to a chimpanzee. We’ll work our way up from the bottom.
It has been 25 years since a report of original research was last submitted to our editors for publication, making this an appropriate time to revisit the question that was so widely debated then: what is the role of human scientists in an age when the frontiers of scientific inquiry have moved beyond the comprehensibility of humans?
No doubt many of our subscribers remember reading papers whose authors were the first individuals ever to obtain the results they described. But as metahumans began to dominate experimental research, they increasingly made their findings available only via DNT (digital neural transfer), leaving journals to publish second-hand accounts translated into human language.
No one denies the many benefits of metahuman science, but one of its costs to human researchers was the realization that they would probably never make an original contribution to science again. Some left the field altogether, but those who stayed shifted their attentions away from original research and toward hermeneutics: interpreting the scientific work of metahumans.
Textual hermeneutics became popular first, since there were already terabytes of metahuman publications whose translations, although cryptic, were presumably not entirely inaccurate. Deciphering these texts bears little resemblance to the task performed by traditional palaeographers, but progress continues: recent experiments have validated the Humphries decipherment of decade-old publications on histocompatibility genetics.
The availability of devices based on metahuman science gave rise to artefact hermeneutics. Scientists began attempting to ‘reverse engineer’ these artefacts, their goal being not to manufacture competing products, but simply to understand the physical principles underlying their operation. The most common technique is the crystallographic analysis of nanoware appliances, which frequently provides us with new insights into mechanosynthesis. (...)
The question is, are these worthwhile undertakings for scientists? Some call them a waste of time, likening them to a Native American research effort into bronze smelting when steel tools of European manufacture are readily available. This comparison might be more apt if humans were in competition with metahumans, but in today's economy of abundance there is no evidence of such competition. In fact, it is important to recognize that — unlike most previous low-technology cultures confronted with a high-technology one — humans are in no danger of assimilation or extinction.
There is still no way to augment a human brain into a metahuman one; the Sugimoto gene therapy must be performed before the embryo begins neurogenesis in order for a brain to be compatible with DNT. This lack of an assimilation mechanism means that human parents of a metahuman child face a difficult choice: to allow their child DNT interaction with metahuman culture, and watch him or her grow incomprehensible to them; or else restrict access to DNT during the child's formative years, which to a metahuman is deprivation like that suffered by Kaspar Hauser. It is not surprising that the percentage of human parents choosing the Sugimoto gene therapy for their children has dropped almost to zero in recent years.
As a result, human culture is likely to survive well into the future, and the scientific tradition is a vital part of that culture. Hermeneutics is a legitimate method of scientific inquiry and increases the body of human knowledge just as original research did. Moreover, human researchers may discern applications overlooked by metahumans, whose advantages tend to make them unaware of our concerns.
For example, imagine if research offered hope of a different intelligence-enhancing therapy, one that would allow individuals to gradually ‘upgrade’ their minds to a level equivalent to that of a metahuman. Such a therapy would offer a bridge across what has become the greatest cultural divide in our species' history, yet it might not even occur to metahumans to explore it; that possibility alone justifies the continuation of human research.
by Ted Chiang, Nature | Read more:
Image: JACEY
[ed. I've been a big fan of Ted for a long time now and have all his books of short stories. Besides the example above, here's another one: The Great Silence (Electric Lit); and the post following this one: The Lifecycle of Software Objects (Subteranian Press). Finally, see also: Interview: Ted Chiang (transcript from the Ezra Klein Show podcast/NYT):]
***
EZRA KLEIN: Let me flip this now. We’re spending billions to invent artificial intelligence. At what point is a computer program responsible for its own actions?TED CHIANG: Well, in terms of at what point does that happen, it’s unclear, but it’s a very long ways from us right now. With regard to the question of, will we create machines that are moral agents, I would say that we can think about that in three different questions. One is, can we do so? Second is, will we do so? And the third one is, should we do so?
I think it is entirely possible for us to build machines that are moral agents. Because I think there’s a sense in which human beings are very complex machines and we are moral agents, which means that there are no physical laws preventing a machine from being a moral agent. And so there’s no obstacle that, in principle, would prevent us from building something like that, although it might take us a very, very long time to get there.
As for the question of, will we do so, if you had asked me, like, 10 or 15 years ago, I would have said, we probably won’t do it, simply because, to me, it seems like it’s way more trouble than it’s worth. In terms of expense, it would be on the order of magnitude of the Apollo program. And it is not at all clear to me that there’s any good reason for undertaking such a thing. However, if you ask me now, I would say like, well, OK, we clearly have obscenely wealthy people who can throw around huge sums of money at whatever they want basically on a whim. So maybe one of them will wind up funding a program to create machines that are conscious and that are moral agents.
However, I should also note that I don’t believe that any of the current big A.I. research programs are on the right track to create a conscious machine. I don’t think that’s what any of them are trying to do. So then as for the third question of, should we do so, should we make machines that are conscious and that are moral agents, to that, my answer is, no, we should not. Because long before we get to the point where a machine is a moral agent, we will have machines that are capable of suffering.
Suffering precedes moral agency in sort of the developmental ladder. Dogs are not moral agents, but they are capable of experiencing suffering. Babies are not moral agents yet, but they have the clear potential to become so. And they are definitely capable of experiencing suffering. And the closer that an entity gets to being a moral agent, the more that it’s suffering, it’s deserving of consideration, the more we should try and avoid inflicting suffering on it. So in the process of developing machines that are conscious and moral agents, we will be inevitably creating billions of entities that are capable of suffering. And we will inevitably inflict suffering on them. And that seems to me clearly a bad idea.
EZRA KLEIN: But wouldn’t they also be capable of pleasure? I mean, that seems to me to raise an almost inversion of the classic utilitarian thought experiment. If we can create these billions of machines that live basically happy lives that don’t hurt anybody and you can copy them for almost no marginal dollar, isn’t it almost a moral imperative to bring them into existence so they can lead these happy machine lives?
TED CHIANG: I think that it will be much easier to inflict suffering on them than to give them happy fulfilled lives. And given that they will start out as something that resembles ordinary software, something that is nothing like a living being, we are going to treat them like crap. The way that we treat software right now, if, at some point, software were to gain some vague glimmer of sentience, of the ability to perceive, we would be inflicting uncountable amounts of suffering on it before anyone paid any attention to them.
Because it’s hard enough to give legal protections to human beings who are absolutely moral agents. We have relatively few legal protections for animals who, while they are not moral agents, are capable of suffering. And so animals experience vast amounts of suffering in the modern world. And animals, we know that they suffer. There are many animals that we love, that we really, really love. Yet, there’s vast animal suffering. So there is no software that we love. So the way that we will wind up treating software, again, assuming that software ever becomes conscious, they will inevitably fall lower on the ladder of consideration. So we will treat them worse than we treat animals. And we treat animals pretty badly.
EZRA KLEIN: I think this is actually a really provocative point. So I don’t know if you’re a Yuval Noah Harari reader. But he often frames his fear of artificial intelligence as simply that A.I. will treat us the way we treat animals. And we treat animals, as you say, unbelievably terribly. But I haven’t really thought about the flip of that, that maybe the danger is that we will simply treat A.I. like we treat animals. And given the moral consideration we give animals, whose purpose we believe to be to serve us for food or whatever else it may be, that we are simply opening up almost unimaginable vistas of immorality and cruelty that we could inflict pretty heedlessly, and that given our history, there’s no real reason to think we won’t. That’s grim.
TED CHIANG: It is grim, but I think that it is by far the more likely scenario. I think the scenario that, say, Yuval Noah Harari is describing, where A.I.’s treat us like pets, that idea assumes that it’ll be easy to create A.I.’s who are vastly smarter than us, that basically, the initial A.I.’s will go from software, which is not a moral agent and not intelligent at all. And then the next thing that will happen will be software which is super intelligent and also has volition.
Whereas I think that we’ll proceed in the other direction, that right now, software is simpler than an amoeba. And eventually, we will get software which is comparable to an amoeba. And eventually, we’ll get software which is comparable to an ant, and then software that is comparable to a mouse, and then software that’s comparable to a dog, and then software that is comparable to a chimpanzee. We’ll work our way up from the bottom.
The Lifecycle of Software Objects
Chapter One
Her name is Ana Alvarado, and she’s having a bad day. She spent all week preparing for a job interview, the first one in months to reach the videoconference stage, but the recruiter’s face barely appeared onscreen before he told her that the company has decided to hire someone else. So she sits in front of her computer, wearing her good suit for nothing. She makes a halfhearted attempt to send queries to some other companies and immediately receives automated rejections. After an hour of this, Ana decides she needs some diversion: she opens a Next Dimension window to play her current favorite game, Age of Iridium.
The beachhead is crowded, but her avatar is wearing the coveted mother-of-pearl combat armor, and it’s not long before some players ask her if she wants to join their fireteam. They cross the combat zone, hazy with the smoke of burning vehicles, and for an hour they work to clear out a stronghold of mantids; it’s the perfect mission for Ana’s mood, easy enough that she can be confident of victory but challenging enough that she can derive satisfaction from it. Her teammates are about to accept another mission when a phone window opens up in the corner of Ana’s video screen. It’s a voice call from her friend Robyn, so Ana switches her microphone over to take the call.
“Hey Robyn.”
“Hi Ana. How’s it going?”
“I’ll give you a hint: right now I’m playing AoI.”
Robyn smiles. “Had a rough morning?”
“You could say that.” Ana tells her about the canceled interview.
“Well, I’ve got some news that might cheer you up. Can you meet me in Data Earth?”
“Sure, just give me a minute to log out.”
“I’ll be at my place.”
“Okay, see you soon.” Ana excuses herself from the fireteam and closes her Next Dimension window. She logs on to Data Earth, and the window zooms in to her last location, a dance club cut into a giant cliff face. Data Earth has its own gaming continents—Elderthorn, Orbis Tertius—but they aren’t to Ana’s taste, so she spends her time here on the social continents. Her avatar is still wearing a party outfit from her last visit; she changes to more conventional clothes and then opens a portal to Robyn’s home address. A step through and she’s in Robyn’s virtual living room, on a residential aerostat floating above a semicircular waterfall a mile across.
Their avatars hug. “So what’s up?” says Ana.
“Blue Gamma is up,” says Robyn. “We just got another round of funding, so we’re hiring. I showed your resume around, and everyone’s excited to meet you.”
“Me? Because of my vast experience?” Ana has only just completed her certificate program in software testing. Robyn taught an introductory class, which is where they met.
“Actually, that’s exactly it. It’s your last job that’s got them interested.”
Ana spent six years working at a zoo; its closure was the only reason she went back to school. “I know things get crazy at a startup, but I’m sure you don’t need a zookeeper.”
Robyn chuckles. “Let me show you what we’re working on. They said I could give you a peek under NDA.”
This is a big deal; up until now, Robyn hasn’t been able to give any specifics about her work at Blue Gamma. Ana signs the NDA, and Robyn opens a portal. “We’ve got a private island; come take a look.” They walk their avatars through.
Ana’s half expecting to see a fantastical landscape when the window refreshes, but instead her avatar shows up in what looks at first glance to be a daycare center. On second glance, it looks like a scene from a children’s book: there’s a little anthropomorphic tiger cub sliding colored beads along a frame of wires; a panda bear examining a toy car; a cartoon version of a chimpanzee rolling a foam rubber ball.
The onscreen annotations identify them as digients, digital organisms that live in environments like Data Earth, but they don’t look like any that Ana’s seen before. These aren’t the idealized pets marketed to people who can’t commit to a real animal; they lack the picture-perfect cuteness, and their movements are too awkward. Neither do they look like inhabitants of Data Earth’s biomes: Ana has visited the Pangaea archipelago, seen the unipedal kangaroos and bidirectional snakes that evolved in its various hothouses, and these digients clearly didn’t originate there.
“This is what Blue Gamma makes? Digients?”
“Yes, but not ordinary digients. Check it out.” Robyn’s avatar walks over to the chimp rolling the ball and crouches down in front of it. “Hi Pongo. Whatcha doing?”
“Pongo pliy bill,” says the digient, startling Ana.
“Playing with the ball? That’s great. Can I play too?”
“No. Pongo bill.”
“Please?”
The chimp looks around and then, never letting go of the ball, toddles over to a scattering of wooden blocks. It nudges one of them in Robyn’s direction. “Robyn pliy blicks.” It sits back down. “Pongo pliy bill.”
“Okay then.” Robyn walks back over to Ana.”What do you think?”
“That’s amazing. I didn’t know digients had come so far.”
“It’s all pretty recent; our dev team hired a couple of PhDs after seeing their conference presentation last year. Now we’ve got a genomic engine that we call Neuroblast, and it supports more cognitive development than anything else currently out there. These fellows here”—she gestures at the daycare center inhabitants—”are the smartest ones we’ve generated so far.”
“And you’re going to sell them as pets?”
“That’s the plan. We’re going to pitch them as pets you can talk to, teach to do really cool tricks. There’s an unofficial slogan we use in-house: ‘All the fun of monkeys, with none of the poop-throwing.’”
Ana smiles. “I’m starting to see where an animal-training background would be handy.”
“Yeah. We aren’t always able to get these guys to do what they’re told, and we don’t know how much of that is in the genes and how much is just because we aren’t using the right techniques.”
She watches as the panda-shaped digient picks up the toy car with one paw and examines the underside; with its other paw it cautiously bats at the wheels. “How much do these digients start out knowing?”
“Practically nothing. Let me show you.” Robyn activates a video screen on one wall of the daycare center; it displays footage of a room decorated in primary colors with a handful of digients lying on the floor. Physically they’re no different from the ones in the daycare center now, but their movements are random, spasmodic. “These guys are newly instantiated. It takes them a few months subjective to learn the basics: how to interpret visual stimuli, how to move their limbs, how solid objects behave. We run them in a hothouse during that stage, so it all takes about a week. When they’re ready to learn language and social interaction, we switch to running them in real time. That’s where you would come in.”
The panda pushes the toy car back and forth across the floor a few times, and then makes a braying sound, mo mo mo. Ana realizes that the digient is laughing. Robyn continues, “I know you studied primate communication in school. Here’s a chance to put that to use. What do you think? Are you interested?”
Ana hesitates; this is not what she envisioned for herself when she went to college, and for a moment she wonders how it has come to this. As a girl she dreamed of following Fossey and Goodall to Africa; by the time she got out of grad school, there were so few apes left that her best option was to work in a zoo; now she’s looking at a job as a trainer of virtual pets. In her career trajectory you can see the diminution of the natural world, writ small.
Snap out of it, she tells herself. It may not be what she had in mind, but this is a job in the software industry, which is what she went back to school for. And training virtual monkeys might actually be more fun than running test suites, so as long as Blue Gamma is offering a decent salary, why not?
#
His name is Derek Brooks, and he’s not happy with his current assignment. Derek designs the avatars for Blue Gamma’s digients, and normally he enjoys his job, but yesterday the product managers asked him for something he considers a bad idea. He tried to tell them that, but the decision is not his to make, so now he has to figure out how to do a decent job of it.
Derek studied to be an animator, so in one respect creating digital characters is right up his alley. In other respects, his job is very different from that of a traditional animator. Normally he’d design a character’s gait and its gestures, but with digients those traits are emergent properties of the genome; what he has to do is design a body that manifests the digients’ gestures in a way that people can relate to. These differences are why a lot of animators—including his wife Wendy—don’t work on digital lifeforms, but Derek loves it. He feels that helping a new lifeform express itself is the most exciting work an animator could be doing.
He subscribes to Blue Gamma’s philosophy of AI design: experience is the best teacher, so rather than try to program an AI with what you want it to know, sell ones capable of learning and have your customers teach them. To get customers to put in that kind of effort, everything about the digients has to be appealing: their personalities need to be charming, which the developers are working on, and their avatars need to be cute, which is where Derek comes in. But he can’t simply give the digients enormous eyes and short noses. If they look like cartoons, no one will take them seriously. Conversely, if they look too much like real animals, their facial expressions and ability to speak become disconcerting. It’s a delicate balancing act, and he has spent countless hours watching reference footage of baby animals, but he’s managed to design hybrid faces that are endearing but not exaggeratedly so.
by Ted Chiang, Subterranean Press | Read more (pdf):
[ed. One of my favorite sci-fi stories by one of my favorite sci-fi authors, Ted Chiang from his stunning collection, Exhalation (it's a bit long - novella length - but mind-blowingly worth it). See also (by Ted Chiang): Understand (Infinity Plus). From a review of Lifecycle:]
"The novella suggests that the only way to create true AI is by long-term, immersive interaction and teaching, just as one must mold the intelligence and capacities of a child. Cognition, in other words, cannot be programmed but is something that must develop and mature through experience. More centrally, this is a story of love and what true reciprocity demands of us and those we love. The relationships that trainers/owners develop with their digients are imagined as analogous to the combination of caring for a companion animal and raising a child: digients are dependents and how they mature is shaped by how they are treated, yet they also have the potential to surpass their guardians in at least some registers. This work remains one of the most nuanced explorations of the ethical challenges we face should we create a digital entity capable of sentience, one perhaps deserving of personhood."
Her name is Ana Alvarado, and she’s having a bad day. She spent all week preparing for a job interview, the first one in months to reach the videoconference stage, but the recruiter’s face barely appeared onscreen before he told her that the company has decided to hire someone else. So she sits in front of her computer, wearing her good suit for nothing. She makes a halfhearted attempt to send queries to some other companies and immediately receives automated rejections. After an hour of this, Ana decides she needs some diversion: she opens a Next Dimension window to play her current favorite game, Age of Iridium.
The beachhead is crowded, but her avatar is wearing the coveted mother-of-pearl combat armor, and it’s not long before some players ask her if she wants to join their fireteam. They cross the combat zone, hazy with the smoke of burning vehicles, and for an hour they work to clear out a stronghold of mantids; it’s the perfect mission for Ana’s mood, easy enough that she can be confident of victory but challenging enough that she can derive satisfaction from it. Her teammates are about to accept another mission when a phone window opens up in the corner of Ana’s video screen. It’s a voice call from her friend Robyn, so Ana switches her microphone over to take the call.
“Hey Robyn.”
“Hi Ana. How’s it going?”
“I’ll give you a hint: right now I’m playing AoI.”
Robyn smiles. “Had a rough morning?”
“You could say that.” Ana tells her about the canceled interview.
“Well, I’ve got some news that might cheer you up. Can you meet me in Data Earth?”
“Sure, just give me a minute to log out.”
“I’ll be at my place.”
“Okay, see you soon.” Ana excuses herself from the fireteam and closes her Next Dimension window. She logs on to Data Earth, and the window zooms in to her last location, a dance club cut into a giant cliff face. Data Earth has its own gaming continents—Elderthorn, Orbis Tertius—but they aren’t to Ana’s taste, so she spends her time here on the social continents. Her avatar is still wearing a party outfit from her last visit; she changes to more conventional clothes and then opens a portal to Robyn’s home address. A step through and she’s in Robyn’s virtual living room, on a residential aerostat floating above a semicircular waterfall a mile across.
Their avatars hug. “So what’s up?” says Ana.
“Blue Gamma is up,” says Robyn. “We just got another round of funding, so we’re hiring. I showed your resume around, and everyone’s excited to meet you.”
“Me? Because of my vast experience?” Ana has only just completed her certificate program in software testing. Robyn taught an introductory class, which is where they met.
“Actually, that’s exactly it. It’s your last job that’s got them interested.”
Ana spent six years working at a zoo; its closure was the only reason she went back to school. “I know things get crazy at a startup, but I’m sure you don’t need a zookeeper.”
Robyn chuckles. “Let me show you what we’re working on. They said I could give you a peek under NDA.”
This is a big deal; up until now, Robyn hasn’t been able to give any specifics about her work at Blue Gamma. Ana signs the NDA, and Robyn opens a portal. “We’ve got a private island; come take a look.” They walk their avatars through.
Ana’s half expecting to see a fantastical landscape when the window refreshes, but instead her avatar shows up in what looks at first glance to be a daycare center. On second glance, it looks like a scene from a children’s book: there’s a little anthropomorphic tiger cub sliding colored beads along a frame of wires; a panda bear examining a toy car; a cartoon version of a chimpanzee rolling a foam rubber ball.
The onscreen annotations identify them as digients, digital organisms that live in environments like Data Earth, but they don’t look like any that Ana’s seen before. These aren’t the idealized pets marketed to people who can’t commit to a real animal; they lack the picture-perfect cuteness, and their movements are too awkward. Neither do they look like inhabitants of Data Earth’s biomes: Ana has visited the Pangaea archipelago, seen the unipedal kangaroos and bidirectional snakes that evolved in its various hothouses, and these digients clearly didn’t originate there.
“This is what Blue Gamma makes? Digients?”
“Yes, but not ordinary digients. Check it out.” Robyn’s avatar walks over to the chimp rolling the ball and crouches down in front of it. “Hi Pongo. Whatcha doing?”
“Pongo pliy bill,” says the digient, startling Ana.
“Playing with the ball? That’s great. Can I play too?”
“No. Pongo bill.”
“Please?”
The chimp looks around and then, never letting go of the ball, toddles over to a scattering of wooden blocks. It nudges one of them in Robyn’s direction. “Robyn pliy blicks.” It sits back down. “Pongo pliy bill.”
“Okay then.” Robyn walks back over to Ana.”What do you think?”
“That’s amazing. I didn’t know digients had come so far.”
“It’s all pretty recent; our dev team hired a couple of PhDs after seeing their conference presentation last year. Now we’ve got a genomic engine that we call Neuroblast, and it supports more cognitive development than anything else currently out there. These fellows here”—she gestures at the daycare center inhabitants—”are the smartest ones we’ve generated so far.”
“And you’re going to sell them as pets?”
“That’s the plan. We’re going to pitch them as pets you can talk to, teach to do really cool tricks. There’s an unofficial slogan we use in-house: ‘All the fun of monkeys, with none of the poop-throwing.’”
Ana smiles. “I’m starting to see where an animal-training background would be handy.”
“Yeah. We aren’t always able to get these guys to do what they’re told, and we don’t know how much of that is in the genes and how much is just because we aren’t using the right techniques.”
She watches as the panda-shaped digient picks up the toy car with one paw and examines the underside; with its other paw it cautiously bats at the wheels. “How much do these digients start out knowing?”
“Practically nothing. Let me show you.” Robyn activates a video screen on one wall of the daycare center; it displays footage of a room decorated in primary colors with a handful of digients lying on the floor. Physically they’re no different from the ones in the daycare center now, but their movements are random, spasmodic. “These guys are newly instantiated. It takes them a few months subjective to learn the basics: how to interpret visual stimuli, how to move their limbs, how solid objects behave. We run them in a hothouse during that stage, so it all takes about a week. When they’re ready to learn language and social interaction, we switch to running them in real time. That’s where you would come in.”
The panda pushes the toy car back and forth across the floor a few times, and then makes a braying sound, mo mo mo. Ana realizes that the digient is laughing. Robyn continues, “I know you studied primate communication in school. Here’s a chance to put that to use. What do you think? Are you interested?”
Ana hesitates; this is not what she envisioned for herself when she went to college, and for a moment she wonders how it has come to this. As a girl she dreamed of following Fossey and Goodall to Africa; by the time she got out of grad school, there were so few apes left that her best option was to work in a zoo; now she’s looking at a job as a trainer of virtual pets. In her career trajectory you can see the diminution of the natural world, writ small.
Snap out of it, she tells herself. It may not be what she had in mind, but this is a job in the software industry, which is what she went back to school for. And training virtual monkeys might actually be more fun than running test suites, so as long as Blue Gamma is offering a decent salary, why not?
#
His name is Derek Brooks, and he’s not happy with his current assignment. Derek designs the avatars for Blue Gamma’s digients, and normally he enjoys his job, but yesterday the product managers asked him for something he considers a bad idea. He tried to tell them that, but the decision is not his to make, so now he has to figure out how to do a decent job of it.
Derek studied to be an animator, so in one respect creating digital characters is right up his alley. In other respects, his job is very different from that of a traditional animator. Normally he’d design a character’s gait and its gestures, but with digients those traits are emergent properties of the genome; what he has to do is design a body that manifests the digients’ gestures in a way that people can relate to. These differences are why a lot of animators—including his wife Wendy—don’t work on digital lifeforms, but Derek loves it. He feels that helping a new lifeform express itself is the most exciting work an animator could be doing.
He subscribes to Blue Gamma’s philosophy of AI design: experience is the best teacher, so rather than try to program an AI with what you want it to know, sell ones capable of learning and have your customers teach them. To get customers to put in that kind of effort, everything about the digients has to be appealing: their personalities need to be charming, which the developers are working on, and their avatars need to be cute, which is where Derek comes in. But he can’t simply give the digients enormous eyes and short noses. If they look like cartoons, no one will take them seriously. Conversely, if they look too much like real animals, their facial expressions and ability to speak become disconcerting. It’s a delicate balancing act, and he has spent countless hours watching reference footage of baby animals, but he’s managed to design hybrid faces that are endearing but not exaggeratedly so.
by Ted Chiang, Subterranean Press | Read more (pdf):
[ed. One of my favorite sci-fi stories by one of my favorite sci-fi authors, Ted Chiang from his stunning collection, Exhalation (it's a bit long - novella length - but mind-blowingly worth it). See also (by Ted Chiang): Understand (Infinity Plus). From a review of Lifecycle:]
"The novella suggests that the only way to create true AI is by long-term, immersive interaction and teaching, just as one must mold the intelligence and capacities of a child. Cognition, in other words, cannot be programmed but is something that must develop and mature through experience. More centrally, this is a story of love and what true reciprocity demands of us and those we love. The relationships that trainers/owners develop with their digients are imagined as analogous to the combination of caring for a companion animal and raising a child: digients are dependents and how they mature is shaped by how they are treated, yet they also have the potential to surpass their guardians in at least some registers. This work remains one of the most nuanced explorations of the ethical challenges we face should we create a digital entity capable of sentience, one perhaps deserving of personhood."
I Called Off My Wedding
Language is a thing with an objective. At times, this objective is known to us before or during the moments when we choose our words. At other times, the objective is a blur. And it is only through speaking word after word that the other side of our lives comes into focus.
As a grant writer, I am constantly making very specific decisions with syntax in order to reach my objective of getting a woman with generational wealth to fund the institutions that employ me. It’s a very calculated pandering, informed by research, key words, and guilt. Wealthy people want to feel like they are doing something meaningful with the money they acquired through their father or oil or banks or whatever. Guilt is a tool.
As a grant writer, I am constantly making very specific decisions with syntax in order to reach my objective of getting a woman with generational wealth to fund the institutions that employ me. It’s a very calculated pandering, informed by research, key words, and guilt. Wealthy people want to feel like they are doing something meaningful with the money they acquired through their father or oil or banks or whatever. Guilt is a tool.
Since I am a poet, my language also has an objective. It is much more divorced from money, however. I suppose my objective is to take the reader somewhere, to make them think of a topic in a different way, to make me understand my own life in a different way. As with work, I can go back and forth on a single word for hours, questioning whether or not it should go here or there, if it’s the right sort of language to get my point across.
I am less careful with language in my ordinary interactions, and perhaps this is inevitable. People are not a glowing word document on a computer screen; they are living and breathing, attached to narratives, looking at us, waiting. On a sleepy November Saturday morning, I ended my seven-and-a-half-year relationship as the words casually fell out of my mouth: “I think I’m gay.” My partner was silent, then angry. I sobbed. A tower fan was thrown, by him. I changed out of my pajamas and left our rent-controlled Los Feliz apartment—perhaps the true loss being that I would never sleep there again. I had uttered a truth that would shift time and space in an irreversible way. Yet the words were also a fragment of many other truths—I’m gay. I’m unhappy. I’m confused. I’m sexually dead inside. I’m curious. I’m tired. I’m panicking. I’m bored. (...)
The months leading up to this are a flurry of site visits and phone calls. I stalk Instagram wedding content until I want to throw up. I take a quiz online and learn that the style of wedding I want to have is “Bohemian.” So, I go on Pinterest and I type “bohemian wedding” and then “bohemian wedding inspo.” I begin to save images of baby’s breath garlands, exposed wood beams, long 100-person dining tables with flowy linens, clusters of thick white votive candles in borderline fire-hazard arrangements, dresses that give off a vibe of white people in a barnyard being whimsical. On every phone call I have with a potential photographer or wedding planner, I try to make myself clear—I’m looking for something different. I have to try not to say the word “indie” even though I know that’s what I mean.
My mother comes with me to visit venues and we both swallow in silence as they begin to tell us numbers. Weekend rate is $15,000, or we could do a weekday for $8,000. This does not include food or anything else, simply a room with a lot of plants and exposed brick. They offer a discounted rate on the metal folding chairs that are described as “minimalist” and I imagine my whole family flying in from Mexico just to sit for hours, unsupported, on the tiny metal seats. I cool my fiery nerves by thinking of the wedding as an abstract dinner party I get to plan. And my mother soon turns her hesitation into excitement. Because this—her firstborn daughter’s wedding—is the ultimate symbol of successful parenting. The price is steep but she is willing to pay whatever it takes. We have worked hard for this, both of us surviving my rebellious late adolescence, my hatred for institutions and family normalcy. No, we’re here, with a high-strung girly venue coordinator holding a clipboard, and we’ve made it.
In these planning months, I barely sleep.
Before one friend proposes, she tells me about her plan to do so. A fancy restaurant in Ojai, over a short stay, maybe I could be there, hiding at another table, taking photos. I feel privileged to carry this secret. She even shows me the ring online, the one she ordered. It is an ugly lesbian ring that is dark and blunt. I tell her it is beautiful.
She ends up scrapping the Ojai idea and proposing in the Philippines while they are with her family. They have a blissful photo shoot on the beach—a masc and a femme gallivanting on white sand at sunset, rings on their hands. I have never seen a more beautiful sight, and my heart bursts with happiness for them.
They are both overwhelmed by the entire thing, and I remind them: I’ve done my research. I offer to send them my Google documents, slides, spreadsheets, references, vendor list, budget breakdowns, anything. We all speak about the logistics without acknowledging the strangeness. Like a ghost, this thing I planned for that never existed. Maps with no destination, piles of documents that will eventually be moved into the trash, after enough time passes that they have not been opened.
Millner recalls the slow deterioration of the straight relationship—opening with an initial intent to escape, pushing the threshold of disagreements—and the messiness of the enlightenment that follows: “I’ve hurt people I love being so / late to my desires.” She muses beautifully on the inevitability of queerness, “the knowing gaze / of Destiny,” and the tumult of those first queer months, at once full of freedom and strangeness.
Turning page after page, I felt deeply that Millner understood me. Understood that it is hard to hurt people, and to admit you have been deceitful, but that it is harder to swallow the truth forever. Both of us mourn and celebrate at once.
“You could have had everything you wanted, / had it been what you wanted.”
¤
The wedding is already fully planned when I call it off. The venue, DJ, photographer, and wedding planner all booked, with nonrefundable deposits.The months leading up to this are a flurry of site visits and phone calls. I stalk Instagram wedding content until I want to throw up. I take a quiz online and learn that the style of wedding I want to have is “Bohemian.” So, I go on Pinterest and I type “bohemian wedding” and then “bohemian wedding inspo.” I begin to save images of baby’s breath garlands, exposed wood beams, long 100-person dining tables with flowy linens, clusters of thick white votive candles in borderline fire-hazard arrangements, dresses that give off a vibe of white people in a barnyard being whimsical. On every phone call I have with a potential photographer or wedding planner, I try to make myself clear—I’m looking for something different. I have to try not to say the word “indie” even though I know that’s what I mean.
My mother comes with me to visit venues and we both swallow in silence as they begin to tell us numbers. Weekend rate is $15,000, or we could do a weekday for $8,000. This does not include food or anything else, simply a room with a lot of plants and exposed brick. They offer a discounted rate on the metal folding chairs that are described as “minimalist” and I imagine my whole family flying in from Mexico just to sit for hours, unsupported, on the tiny metal seats. I cool my fiery nerves by thinking of the wedding as an abstract dinner party I get to plan. And my mother soon turns her hesitation into excitement. Because this—her firstborn daughter’s wedding—is the ultimate symbol of successful parenting. The price is steep but she is willing to pay whatever it takes. We have worked hard for this, both of us surviving my rebellious late adolescence, my hatred for institutions and family normalcy. No, we’re here, with a high-strung girly venue coordinator holding a clipboard, and we’ve made it.
In these planning months, I barely sleep.
¤
It is summer when my two best friends get engaged. We joke that it will be the gay wedding of the century.Before one friend proposes, she tells me about her plan to do so. A fancy restaurant in Ojai, over a short stay, maybe I could be there, hiding at another table, taking photos. I feel privileged to carry this secret. She even shows me the ring online, the one she ordered. It is an ugly lesbian ring that is dark and blunt. I tell her it is beautiful.
She ends up scrapping the Ojai idea and proposing in the Philippines while they are with her family. They have a blissful photo shoot on the beach—a masc and a femme gallivanting on white sand at sunset, rings on their hands. I have never seen a more beautiful sight, and my heart bursts with happiness for them.
They are both overwhelmed by the entire thing, and I remind them: I’ve done my research. I offer to send them my Google documents, slides, spreadsheets, references, vendor list, budget breakdowns, anything. We all speak about the logistics without acknowledging the strangeness. Like a ghost, this thing I planned for that never existed. Maps with no destination, piles of documents that will eventually be moved into the trash, after enough time passes that they have not been opened.
¤
Maggie Millner’s 2023 poetry collection Couplets: A Love Story centers on a narrator who ends her straight, long-term relationship after falling for an older academic dyke—“she was queer and edited periodicals / and I was a poet who had never dated a woman.” Without disclosing too many details, I found kinship in every stanza.Millner recalls the slow deterioration of the straight relationship—opening with an initial intent to escape, pushing the threshold of disagreements—and the messiness of the enlightenment that follows: “I’ve hurt people I love being so / late to my desires.” She muses beautifully on the inevitability of queerness, “the knowing gaze / of Destiny,” and the tumult of those first queer months, at once full of freedom and strangeness.
Turning page after page, I felt deeply that Millner understood me. Understood that it is hard to hurt people, and to admit you have been deceitful, but that it is harder to swallow the truth forever. Both of us mourn and celebrate at once.
“You could have had everything you wanted, / had it been what you wanted.”
by Sarah Yanni, LA Review of Books | Read more:
Image: Little Women/Sony Pictures
Tuesday, June 4, 2024
Does Google Know How Google Works?
You’ve probably already seen many screenshots from the recent, life-affirmingly funny rollout of Google search’s new “AI Overview” feature, which uses a large language model (of the kind that powers ChatGPT, e.g.) to synthesize and summarize search results into a paragraph or two of text, placed prominently above the results. These “overviews,” synthesized from Google search results, are frequently incorrect or incoherent, often in ways that no human would ever be (screenshots below from Twitter and Bluesky; (...)
How do Google search results work?
One particularly fascinating aspect of the AI Overview fiasco is the manner of its failure. Maybe the greatest of the AI Overview errors was the cheerful suggestion to “add 1/8 a cup of non-toxic glue to [pizza] sauce to give it more tackiness,”1 which appears to come from a decade-old joke comment by someone called “Fucksmith” located deep in a Reddit thread somewhere.
In other words, the AI Overview errors aren’t the familiar hallucinations that open-ended large language models like ChatGPT will produce as a matter of course, but something like their opposite. If hallucinations are plausible falsehoods--statements that sound correct but have no grounding in reality--these are implausible “facts”--statements that are facially untrue but have direct textual grounding. Unlike the responses produced by ChatGPT, every string of text in an AI Overview has a specific (and often a cited) source that the model is dutifully summarizing and synthesizing, as it has been directed to do by its prompting. It’s just that, well, sometimes the source is Fucksmith.
In its statement, Google is eager make clear that the AI Overviews don’t “hallucinate,” but I’m not sure this is entirely flattering to Google. What it suggests is that Google’s problem here is not so much a misunderstanding of what LLMs are good at and what they’re for, but--more troublingly--a misunderstanding of what Google is good at and what it’s for. Deploying the AI Overview model to recapitulate a set of specific and narrowly selected texts--that is, the search results--strikes me as a relatively legitimate and logical use of a large language model, insofar as it takes advantage of the technology’s strengths (synthesizing and summarizing information) and minimizes its weaknesses (making bullshit up all the time).2 The LLM is even doing a pretty good job at creating a syntactically coherent summary of the top results--it’s just that “the top results” for any given search string often don’t represent a coherent body of text that can be sensibly synthesized--nor, as Mike Caulfield explains in an excellent post on why this style of synthetic “overview” drawn from Google results is poorly adapted to the task of search, should they:
a good search result for an ambiguous query will often be a bit of a buffet, pulling a mix of search results from different topical domains. When I say, for example, “why do people like pancakes but hate waffles” I’m going to get two sorts of results. First, I’ll get a long string of conversations where the internet debates the virtues of pancakes vs. waffles. Second, I’ll get links and discussion about a famous Twitter post about the the hopelessness of conversation on Twitter […] For an ambiguous query, this is a good result set. If you see a bit of each in the first 10 blue links you can choose your own adventure here. It’s hard for Google to know what matches your intent, but it’s trivially easy for you to spot things that match your intent. In fact, the wider apart the nature of the items, the easier it is to spot the context that applies to you. So a good result set will have a majority of results for what you’re probably asking and a couple results for things you might be asking, and you get to choose your path.You cannot combine this intentionally diverse array of results into a single coherent “answer,” and, it’s worth saying again, this is a strength of the Google search product. It is possible I am in a minority here, but speaking for myself I want to see a selection of different possible results and use the brain my ancestors spent hundreds of millions of years evolving to determine the context, tone, and intent.
Likewise, when you put in terms about cheese sliding off pizza, Google could restrict the returned results to recipe sites, advice which would be relatively glue-free. But maybe you want advice, or maybe you want to see discussion. Maybe you want to see jokes. Maybe you are looking for a very specific post you read, and not looking to solve an issue at all, in which case you just want relevance completely determined by closeness of word match. Maybe you’re looking for a movie scene you remember about cheese sliding off pizza.
LLMs vs. Platforms
Google’s response to complaints about AI Overview errors has been to dismiss the examples as “uncommon queries.” That’s probably true, not just in the specific (it is uncommon to Google “how many rocks should I eat”) but in the general sense that most Google searches are essentially navigational (i.e., looking for a specific official website you want to visit) or for pretty straightforward factual questions like “what time is the Super Bowl,” where a user probably doesn’t actually want or need domain diversity in their results. But the addition of the AI Overview module at the top of the results isn’t merely a problem in the case of those “uncommon queries” where it produces implausible “facts” based on shitposts. It’s a problem everywhere, because it fundamentally changes what Google presents itself as.
by Max Read, Read Max | Read more:
Images: Twitter/Bluesky
Unlike conventional cannabis packaging, Miami’s Creative Partners Studio has designed a more experiential, stunning system for Mother Concentrates. The packaging introduces a vibrant color palette of orange, purple, light pink, green, and light sage hues, creating a visually dynamic line of products.
Images: MCPS
~ Mother Concentrates Comes Full Circle With Creative Partners Studio (Dieline)
[ed. Like expensive cosmetics. Weed's come a long way.]
[ed. Like expensive cosmetics. Weed's come a long way.]
Nuts!
via:
[ed. See also: How Actors Remember Their Lines (Nautilus)
Actors face the demanding task of learning their lines with great precision, but they rarely do so by rote repetition. They did not, they said, sit down with a script and recite their lines until they knew them by heart. Repeating items over and over, called maintenance rehearsal, is not the most effective strategy for remembering. Instead, actors engage in elaborative rehearsal, focusing their attention on the meaning of the material and associating it with information they already know. Actors study the script, trying to understand their character and seeing how their lines relate to that character. (...)
Actors face the demanding task of learning their lines with great precision, but they rarely do so by rote repetition. They did not, they said, sit down with a script and recite their lines until they knew them by heart. Repeating items over and over, called maintenance rehearsal, is not the most effective strategy for remembering. Instead, actors engage in elaborative rehearsal, focusing their attention on the meaning of the material and associating it with information they already know. Actors study the script, trying to understand their character and seeing how their lines relate to that character. (...)
Similarly, when psychologists Helga and Tony Noice surveyed actors on how they learn their lines, they found that actors search for meaning in the script, rather than memorizing lines. The actors imagine the character in each scene, adopt the character’s perspective, relate new material to the character’s background, and try to match the character’s mood. Script lines are carefully analyzed to understand the character’s motivation. This deep understanding of a script is achieved by actors asking goal-directed questions, such as “Am I angry with her when I say this?” Later, during a performance, this deep understanding provides the context for the lines to be recalled naturally, rather than recited from a memorized text. In his book Acting in Film, actor Michael Caine described this process well:
You must be able to stand there not thinking of that line. You take it off the other actor’s face. Otherwise, for your next line, you’re not listening and not free to respond naturally, to act spontaneously. (...)In describing how they remember their lines, actors are telling us an important truth about memory—deep understanding promotes long-lasting memories.
Good, Cheap Dogs Buy Loyalty
Fear not, hot dog fans: Costco doesn’t plan to raise the price of its beloved franks anytime soon.
The retailer has been hawking its hot-dog-and-soda combo for a smooth $1.50 since it first hit menus in the mid-1980s.
The price tag has held steady over the years despite inflation — otherwise it would be closer to $4.40 these days.
Speculation that the cost of the famed combo might be changing began to heat up in March after Richard Galanti, the company’s then-chief financial officer, told Bloomberg that it’s “probably safe for a while” — not necessarily the guarantee that every hungry Costco member wanted to hear.
His successor, Gary Millerchip, cleared things up in his first quarterly earnings call on Thursday.
“To clear up some recent media speculation, I also want to confirm the $1.50 hot dog price is safe,” Millerchip said.
That sound bite has since made the rounds on social media, providing welcome relief to the chain’s many hot dog devotees.
Loftus says, "It's a good PR move for Costco to not change this price," adding that it has a humanizing effect on the company. (...)
The lore of the hot dog combo, explained
The company said earlier this year that it sold nearly 200 million hot-dog-and-soda combos in the 2023 fiscal year alone.
The low cost of Costco’s quarter-pound dogs — as well as the chain’s oft-discussed commitment to keeping it that way — has earned them a cult following over the decades, spawning memes and fan-made merch.
The tale of the Costco dog dates back to around 1984, when Hebrew National — Costco’s original hot dog supplier — sold hot dogs from a cart outside one of its stores in San Diego. (The company began operating its own hot dog factories in 2008, to cut down on supply chain costs.) (...)
Witcher says that this part of the experience has basically enabled Costco to establish its own form of consumer culture.
“No one is buying that hot dog and soda and putting it in with their grocery bags to eat tomorrow,” he said. “The quick-serve restaurant is part of the culture of adventure that Costco has created, much like you'd buy food and a drink at a movie theater, an amusement park, or a concert.”
He doesn’t see a reason why Costco would risk losing customers who partake in that tradition by “removing that cultural connection simply to make an extra fifty cents.”
by Rachel Treisman, NPR | Read more:
Image: Patrick T. Fallon/AFP via Getty Images
[ed. See also: Everything You Need To Know About Costco Hot Dogs (Delish - first excerpt, below); and, In Costco We Trust (Dirt - second excerpt):]
The $1.50 Combo Is To Die For—Literally
The inflation-defying price point for Costco's hot dog combo was first set in 1985 by the vendor who started selling them out of a cart in Portland, Oregon. And since then, the prices haven't changed at all. Costco is committed to keeping their inventory affordable in general, but especially when it comes to the hot dog.
In fact, the price of the food court hot dog is a literal life and death situation. When W. Craig Jelinek joined the leadership team in 2010, he complained to Costco co-founder and CEO, Jim Sinegal, that the combo was losing the company money. Sinegal's response was one for the history books: "If you raise the effing hot dog, I will kill you. Figure it out."
[ed. See also: Everything You Need To Know About Costco Hot Dogs (Delish - first excerpt, below); and, In Costco We Trust (Dirt - second excerpt):]
The $1.50 Combo Is To Die For—Literally
The inflation-defying price point for Costco's hot dog combo was first set in 1985 by the vendor who started selling them out of a cart in Portland, Oregon. And since then, the prices haven't changed at all. Costco is committed to keeping their inventory affordable in general, but especially when it comes to the hot dog.
In fact, the price of the food court hot dog is a literal life and death situation. When W. Craig Jelinek joined the leadership team in 2010, he complained to Costco co-founder and CEO, Jim Sinegal, that the combo was losing the company money. Sinegal's response was one for the history books: "If you raise the effing hot dog, I will kill you. Figure it out."
The Portion Sizes Used To Be Smaller
According to the warehouse's magazine, The Costco Connection, Kirkland hot dogs are 10% heavier and longer than the original quarter pound franks. They're also made from 100 percent beef that's exclusively USDA Choice or better. And on top of that, Costco has also increased the portion size of their soda from a 12 ounce can to a 20 ounce fountain drink with free refills. ~ Everything You Need To Know About Costco Hot Dogs
***
"Recently, I asked my dad why Costco still appeals to him after decades of shopping there. It would be more convenient to shop at the Safeway down the street. He likes the fact that it’s a no-frills operation: With Costco, what you see is what you get. The store subverts the carefully manicured “supermarket aesthetic”—a term used by the scholar Andrew G. Christensen in a paper on Don Delillo’s White Noise—where store environments are engineered with displays, lighting, and “cheery exteriors” complete with music. A trademark of the supermarket aesthetic is “a certain ambiguity that the viewer (or target market) may perceive as psychological manipulation—something almost sinister behind the cheery exterior.” Costco’s lack of decor leaves the products to speak for themselves. The boxes the shipments come in line its industrial shelves. The hum in the store comes from conversations and movement, instead of speakers. (...)Lange described Costco as the pinnacle of American consumerism—a big-box store that’s keeping customers satisfied. Forbes reported that Costco’s total sales in 2022 hit a record high of $227 billion, a 17 percent increase from 2021. “With the reputation that it has for how it treats its employees and the quality of what it’s achieved—to do that at the scale that it’s done is almost unthinkable in any other model,” Lange said. “Capitalism and consumerism produce a lot of crap, or a lot of luxury. But to find something in the middle that has the mass appeal that Costco has, and to do it as well as Costco has done it, few people walk away from that experience unhappy.” ~ In Costco We Trust
Monday, June 3, 2024
How Influencer Cartels Manipulate Social Media: Fraudulent Behaviour Hidden in Plain Sight
Social media influencers account for a growing share of marketing budgets worldwide. This column examines a problem within this rapidly expanding advertising market – influencer cartels, in which groups of influencers collude to increase advertising revenue by inflating each other’s engagement numbers. Influencer cartels can improve consumer welfare if they expand social media engagement to the target audience, but reduce welfare if they divert engagement to less relevant audiences. Rewarding engagement quantity encourages harmful collusion. Instead, the authors suggest, influencers should be compensated based on the actual value they provide. (...)
Distorted Incentives and Fraudulent Behaviour in Influencer Marketing
Influencer marketing has become a key part of modern advertising. In 2023, spending on influencer marketing reached $31 billion, already rivalling the entirety of print newspaper advertising. Influencer marketing allows advertisers fine targeting based on consumer interests by choosing a good product-influencer-consumer match.
Many non-celebrity influencers are not paid based on the success of their marketing campaigns. In fact, less than 20% of companies track the sales induced by their influencer marketing campaigns. Instead, influencers’ pay is based on impact measures such as the number of followers and engagement (likes and comments), furnishing an incentive for fraudulent behaviour – for inflating their influence. Inflating influence is a form of advertising fraud that causes market inefficiencies by directing ads to the wrong audience. An estimated 15% of influencer marketing spending is misused due to exaggerated influence. To address this issue, the US Federal Trade Commission proposed a rule in 2023 to ban the sale and purchase of false indicators of social media influence. Cartels provide a way of obtaining fake engagement that does not fall directly under the proposed rule – because no money changes hands – but is still in the same spirit. While there is substantial literature on fake consumer reviews (Mayzlin et al. 2014, Luca and Zervas 2016) and other forms of advertising fraud (Zinman and Zitzewitz 2016), the literature on influencer marketing has focused mostly on advertising disclosure (Ershov and Mitchell 2023, Pei and Mayzlin 2022, Mitchell 2021, Fainmesser and Galeotti 2021), leaving the fraudulent behaviour unstudied.
How Do Instagram Cartels Work?
An influencer cartel is a group of influencers who collude to boost their advertising fees by inflating engagement metrics. As in traditional industries (Steen et al. 2013), influencer cartels involve a formal agreement to manipulate the market for the members’ benefit. The cartels operate in online chatrooms. The screenshots below show how one such cartel operates in practice. The image on the left is from an online chat room, where cartel members submit links to their content for extra engagement. Before submitting a link, they must reciprocate by liking and commenting on other members’ posts. An algorithm enforces these rules. The image on the right shows these cartel-induced comments on Instagram. The cartel history and rules make it possible to observe which engagement (comments) originate from the cartel.
Figure 1 Left panel shows posts in online chatroom submitted for cartel engagement; right panel shows Instagram comments originating from the cartel
Source: Left panel is a screenshot of a Telegram group; right panel is a screenshot from Instagram. To preserve anonymity, account identifiers are blurred and the photo is replaced with an analogous photo by an AI image generator.
What Distinguishes ‘Bad’ from ‘Not-So-Bad’ Cartels?
Our theoretical model formalises the main trade-offs in this setting, in the spirit of the imaginary citation group discussed earlier. The model focuses on strategic engagement, a decision that affects social media content distribution and consumption (Aridor et al. 2024) but has been underexplored (with the exception of Filippas et al. 2023, who studied attention bartering in Twitter). Engaging with other influencers’ content has a positive externality, leading to too little engagement in equilibrium. Forming a cartel to reciprocally engage with each other’s content can internalise this externality and might be socially desirable. However, it can also result in low-value engagement, especially when advertisers pay based on quantity rather than quality.
The key dimension to differentiating ‘bad’ from ‘not-so-bad’ cartels is the quality of cartel engagement. By ‘high quality’, we mean engagement coming from influencers with similar interests. The idea is that influencers provide value to advertisers by promoting a product among the target audience: people with similar interests, such as vegan burgers to vegans. If a cartel generates engagement from influencers with other interests (meat lovers), this hurts consumers and advertisers. It hurts consumers because the platform will show them irrelevant content, and advertisers are hurt because their ads are shown to the wrong audience. Whether or not a particular cartel is welfare-reducing or welfare-improving is an empirical question.
by Marit Hinnosaar and Toomas Hinnosaar, VoxEU | Read more:
Distorted Incentives and Fraudulent Behaviour in Influencer Marketing
Influencer marketing has become a key part of modern advertising. In 2023, spending on influencer marketing reached $31 billion, already rivalling the entirety of print newspaper advertising. Influencer marketing allows advertisers fine targeting based on consumer interests by choosing a good product-influencer-consumer match.
Many non-celebrity influencers are not paid based on the success of their marketing campaigns. In fact, less than 20% of companies track the sales induced by their influencer marketing campaigns. Instead, influencers’ pay is based on impact measures such as the number of followers and engagement (likes and comments), furnishing an incentive for fraudulent behaviour – for inflating their influence. Inflating influence is a form of advertising fraud that causes market inefficiencies by directing ads to the wrong audience. An estimated 15% of influencer marketing spending is misused due to exaggerated influence. To address this issue, the US Federal Trade Commission proposed a rule in 2023 to ban the sale and purchase of false indicators of social media influence. Cartels provide a way of obtaining fake engagement that does not fall directly under the proposed rule – because no money changes hands – but is still in the same spirit. While there is substantial literature on fake consumer reviews (Mayzlin et al. 2014, Luca and Zervas 2016) and other forms of advertising fraud (Zinman and Zitzewitz 2016), the literature on influencer marketing has focused mostly on advertising disclosure (Ershov and Mitchell 2023, Pei and Mayzlin 2022, Mitchell 2021, Fainmesser and Galeotti 2021), leaving the fraudulent behaviour unstudied.
How Do Instagram Cartels Work?
An influencer cartel is a group of influencers who collude to boost their advertising fees by inflating engagement metrics. As in traditional industries (Steen et al. 2013), influencer cartels involve a formal agreement to manipulate the market for the members’ benefit. The cartels operate in online chatrooms. The screenshots below show how one such cartel operates in practice. The image on the left is from an online chat room, where cartel members submit links to their content for extra engagement. Before submitting a link, they must reciprocate by liking and commenting on other members’ posts. An algorithm enforces these rules. The image on the right shows these cartel-induced comments on Instagram. The cartel history and rules make it possible to observe which engagement (comments) originate from the cartel.
Figure 1 Left panel shows posts in online chatroom submitted for cartel engagement; right panel shows Instagram comments originating from the cartel
Source: Left panel is a screenshot of a Telegram group; right panel is a screenshot from Instagram. To preserve anonymity, account identifiers are blurred and the photo is replaced with an analogous photo by an AI image generator.
What Distinguishes ‘Bad’ from ‘Not-So-Bad’ Cartels?
Our theoretical model formalises the main trade-offs in this setting, in the spirit of the imaginary citation group discussed earlier. The model focuses on strategic engagement, a decision that affects social media content distribution and consumption (Aridor et al. 2024) but has been underexplored (with the exception of Filippas et al. 2023, who studied attention bartering in Twitter). Engaging with other influencers’ content has a positive externality, leading to too little engagement in equilibrium. Forming a cartel to reciprocally engage with each other’s content can internalise this externality and might be socially desirable. However, it can also result in low-value engagement, especially when advertisers pay based on quantity rather than quality.
The key dimension to differentiating ‘bad’ from ‘not-so-bad’ cartels is the quality of cartel engagement. By ‘high quality’, we mean engagement coming from influencers with similar interests. The idea is that influencers provide value to advertisers by promoting a product among the target audience: people with similar interests, such as vegan burgers to vegans. If a cartel generates engagement from influencers with other interests (meat lovers), this hurts consumers and advertisers. It hurts consumers because the platform will show them irrelevant content, and advertisers are hurt because their ads are shown to the wrong audience. Whether or not a particular cartel is welfare-reducing or welfare-improving is an empirical question.
by Marit Hinnosaar and Toomas Hinnosaar, VoxEU | Read more:
Image: VoxEU
Touch-Me-Not
[ed. Seen this before but never fails to impress.]
Operation Bottleneck: DEA versus FDA in a Regulatory War
A record number of drugs are in shortage across the United States. In any particular case, it’s difficult to trace out the exact causes of the shortage but health care is the US’s most highly regulated, socialist industry and shortages are endemic under socialism so the pattern fits. The shortage of Adderall and other ADHD medications is a case in point. Adderall is a Schedule II controlled substance which means that in addition to the FDA and other health agencies the production of Adderall is also regulated, monitored and controlled by the U.S. Drug Enforcement Administration (DEA).
The DEA aims to “combat criminal drug networks that bring harm, violence, overdoses, and poisonings to the United States.” Its homepage displays stories of record drug seizures, pictures of “most wanted” criminal fugitives, and heroic armed agents conducting drug raids. With this culture, do you think the DEA is the right agency to ensure that Americans are also well supplied with legally prescribed amphetamines?
Indeed, there is a large factory in the United States capable of producing 600 million doses of Adderall annually that has been shut down by the DEA for over a year because of trivial paperwork violations. The New York Magazine article on the DEA created shortage has to be read to be believed.
To be sure, the opioid epidemic is a problem but the big, multi-national plants are not responsible for fentanyl on the streets and even in the early years the opioid epidemic was a prescription problem (with some theft from pharmacies) not a factory theft problem (see figure at left). Maybe you think Adderall is overprescribed. Could be but the DEA is supposed to be enforcing laws not making drug policy. The one thing one can say for certain is that Operation Bottleneck has surely been a success in creating shortages of Adderall.
The DEA’s contradictory role in both combating the illegal drug trade and regulating the supply of legal, prescription drugs is highlighted by the fact that at the same as the DEA was raiding and shutting down Ascent, the FDA was pleading with them to increase production!
by Alex Tabarrok, Marginal Revolution | Read more:
Image: Ascent drug vault. Thomas Prior
Indeed, there is a large factory in the United States capable of producing 600 million doses of Adderall annually that has been shut down by the DEA for over a year because of trivial paperwork violations. The New York Magazine article on the DEA created shortage has to be read to be believed.
Inside Ascent’s 320,000-square-foot factory in Central Islip, a labyrinth of sterile white hallways connects 105 manufacturing rooms, some of them containing large, intricate machines capable of producing 400,000 tablets per hour. In one of these rooms, Ascent’s founder and CEO — Sudhakar Vidiyala, Meghana’s father — points to a hulking unit that he says is worth $1.5 million. It’s used to produce time-release Concerta tablets with three colored layers, each dispensing the drug’s active ingredient at a different point in the tablet’s journey through the body. “About 25 percent of the generic market would pass through this machine,” he says. “But we didn’t make a single pill in 2023.” (...)The causes of the DEA’s crackdown appears to be precisely the contradiction in its dueling missions. Ascent also produces opioids and the DEA crackdown was part of what it calls Operation Bottleneck, a series of raids on a variety of companies to demand that they account for every pill produced.
To be sure, the opioid epidemic is a problem but the big, multi-national plants are not responsible for fentanyl on the streets and even in the early years the opioid epidemic was a prescription problem (with some theft from pharmacies) not a factory theft problem (see figure at left). Maybe you think Adderall is overprescribed. Could be but the DEA is supposed to be enforcing laws not making drug policy. The one thing one can say for certain is that Operation Bottleneck has surely been a success in creating shortages of Adderall.
The DEA’s contradictory role in both combating the illegal drug trade and regulating the supply of legal, prescription drugs is highlighted by the fact that at the same as the DEA was raiding and shutting down Ascent, the FDA was pleading with them to increase production!
by Alex Tabarrok, Marginal Revolution | Read more:
Image: Ascent drug vault. Thomas Prior
Same Old Story
Image:via
"I see the show downs, slow downs, lost and found, turn arounds.
The boys in the military shirts.
I keep my eyes on the prize, on the long fallen skies.
And I don't let my friends get hurt.
All you back room schemers, small trip dreamers.
Better find something new to say.
Cause you're the same old story.
It's the same old crime.
And you got some heavy dues to pay."
~ Steve Miller, Space Cowboy
Sunday, June 2, 2024
Welcome to the Millennial Midlife Crisis
In the movies and TV I grew up watching, a midlife crisis was born out of a complacent sense of security; life was maybe going too well, and people just wanted a chance to flex their youth one more time. They bought a sports car, pierced something, got a weird tattoo. In the extreme, maybe they ditched their entire old lives and started fresh, did something that their kids are still in therapy about now.
For most millennials, the old material markers of midlife, like owning a home or spending 20-plus years at one job, are a nostalgic fantasy. Something we miss but never had. Even as we negotiate gray hairs, crow’s-feet, and a changing body, for many of us, little has changed in our career, home, and money prospects. Growing up, even though our family didn’t have a lot of money — my parents were refugees who moved from Pakistan to Canada without college degrees and drove taxis, waited tables, sold cars, and did whatever else they could to give us what little they could — things felt relatively fine. My parents always managed to clothe and feed us, we went out for dinner a few times a month, we always had a pretty decent roof over our heads; hell, they even managed to buy a house at one point. They had jobs, they left jobs, they got new jobs. They lived paycheck to paycheck, but they also weren’t worried about where that next check came from. I can’t imagine buying a house in downtown Toronto today on one income with less than $10,000 saved for a down payment. I actually want to cry just thinking about the prospect. Same with their ability to get a job when they needed one. I have 20 years of experience in my field at this point, and the majority of the time when I apply for a job, I never hear back.
For as long as there have been “trend stories” about millennials loving pricey avocado toast, there have been actual millennials sounding the alarm bell about how crippling student-loan debt, a punishing job market, and rapidly rising housing costs have diminished our ability to get a secure footing in our lives and actually start to plan for our futures. And now, we’re not exactly staring out the window of our country house fondly remembering our salad days. We’re still grinding it out, perennially worried about losing it all.
Any single change in our jobs, homes, or health could upend our entire lives in ways that are just financially impossible.
Two years ago, I wrote about losing my ambition, about reshaping my priorities and putting the focus back on what I really want to do. I don’t need new highlights or a sports car; I just want the ability to plan for a secure future, to have optimism about my career prospects ten or even five years from now, to be able to afford to care for my family without the constant threat of layoffs, hunger, or eviction. I want time with my kids while I’m still healthy and aware, and I want to do work that is fulfilling and meaningful. And despite divorcing myself from a specific model of success in the process of leaving ambition behind, I do work hard. I work harder than ever, because I’m terrified of what happens if I don’t. I’ve spent the last year looking into what getting a real-estate license would entail, looking up how to become a plumber’s apprentice, and Googling “best graduate degrees if you want to get a steady job that pays good and will let you retire one day with dignity.” It’s a midlife crisis, no doubt, but it’s not born out of restlessness or a rosy remembrance of things past; it’s panic that this is as good as it’s going to get and what lies ahead could be worse.
I’m not just worried about myself — I have young kids, and my parents are getting old. Can I care for everyone and myself? I have a parent who will likely require some financial assistance as they age, and I don’t know if I have those funds. (A third of Americans happen to feel the same way, and just over half plan to assist their parents financially in their retirement years. For me and many of my friends, our current retirement plan is to drop dead at work.)
Almost all of my friends are in the middle of a job crisis, either looking for work or trying to figure out how to pivot to something else. I have a friend in her late 30s who has not been unemployed a day in her adult life. She’s the most organized, impressively career-focused person I know — she just got laid off from her job at a big tech company. Her most generous assessment of the landscape is that she probably won’t find another job for a year and may have to reconsider her career path entirely and start from scratch. She and her partner were seemingly financially secure and debating whether it makes sense to have a baby, but this has thrown everything off. Another friend in his mid-40s is worried it’s too late for him to have a baby and is also reconsidering what it is he should do with his life, but has no idea where to start. He’s been a steadily working creative who was one of the lucky ones to have bought a house 15 years ago, but he just sold it to give himself some wiggle room as he starts looking for steadier employment.
I keep waiting for the dam to break for something to happen that fixes the housing bubble, our debt crisis, or the job market, but that alarm’s been ringing and no one who can do anything about it seems to be interested in answering.
Today, the real crisis isn’t about mortality; it’s that our lives and stations are unchanged from when we were 30 — or, hell, even 20. It’s about a distinct lack of comfort, of resources. My dad was trying to escape the doldrums of midlife with blond hair; meanwhile, I have friends who can’t even escape a bad marriage because they can’t afford the rent in a new place by themselves, especially if they want to keep their kids in the same school.
Any single change in our jobs, homes, or health could upend our entire lives in ways that are just financially impossible.
Two years ago, I wrote about losing my ambition, about reshaping my priorities and putting the focus back on what I really want to do. I don’t need new highlights or a sports car; I just want the ability to plan for a secure future, to have optimism about my career prospects ten or even five years from now, to be able to afford to care for my family without the constant threat of layoffs, hunger, or eviction. I want time with my kids while I’m still healthy and aware, and I want to do work that is fulfilling and meaningful. And despite divorcing myself from a specific model of success in the process of leaving ambition behind, I do work hard. I work harder than ever, because I’m terrified of what happens if I don’t. I’ve spent the last year looking into what getting a real-estate license would entail, looking up how to become a plumber’s apprentice, and Googling “best graduate degrees if you want to get a steady job that pays good and will let you retire one day with dignity.” It’s a midlife crisis, no doubt, but it’s not born out of restlessness or a rosy remembrance of things past; it’s panic that this is as good as it’s going to get and what lies ahead could be worse.
I’m not just worried about myself — I have young kids, and my parents are getting old. Can I care for everyone and myself? I have a parent who will likely require some financial assistance as they age, and I don’t know if I have those funds. (A third of Americans happen to feel the same way, and just over half plan to assist their parents financially in their retirement years. For me and many of my friends, our current retirement plan is to drop dead at work.)
Almost all of my friends are in the middle of a job crisis, either looking for work or trying to figure out how to pivot to something else. I have a friend in her late 30s who has not been unemployed a day in her adult life. She’s the most organized, impressively career-focused person I know — she just got laid off from her job at a big tech company. Her most generous assessment of the landscape is that she probably won’t find another job for a year and may have to reconsider her career path entirely and start from scratch. She and her partner were seemingly financially secure and debating whether it makes sense to have a baby, but this has thrown everything off. Another friend in his mid-40s is worried it’s too late for him to have a baby and is also reconsidering what it is he should do with his life, but has no idea where to start. He’s been a steadily working creative who was one of the lucky ones to have bought a house 15 years ago, but he just sold it to give himself some wiggle room as he starts looking for steadier employment.
I keep waiting for the dam to break for something to happen that fixes the housing bubble, our debt crisis, or the job market, but that alarm’s been ringing and no one who can do anything about it seems to be interested in answering.
by Amil Niazi, The Cut | Read more:
Image: The Cut; Photos: Getty
Playing Out of Divots
Whether you're new to the game or have been playing it for years, you've probably experienced the deflating feeling of hitting a great drive that splits the fairway only to find once you’ve gotten to your ball that it's sitting in a hole created by someone else's shot. Although not impossible to play out of—you can read Butch Harmon's advice on how to do it here—it's still a frustrating situation. You did everything right, yet it feels like you're being unjustly penalized.
It's at those moments when you might wonder why the Rules of Golf doesn't allow you to take free relief. After all, Rule 16.3 allows you to remove an embedded ball anywhere in the general area of the course without penalty. How is this any different, you might wonder?
Let's have Craig Winter, Senior Director of Rules of Golf and Amateur Status for the USGA, explain:
"It's fundamental to golf to play the ball as it lies," he says. "And you don't always get a good lie."
Although the USGA and R&A, golf's governing bodies, have considered on various occasions handling divot holes in another manner, there is no "practical solution" other than to leave it as just a part of the game, Winter says. If you think about it beyond the moment you're in one, how often does it happen to you in any golf season? Probably not a lot. Furthermore, if the rules makers were to treat divot holes as, say, ground under repair, think of how many spots on the fairway would then fall into that category? They're all over the place. They take a long time to heal, and they typically are not a focus of normal golf-course maintenance.
For these reasons, don't expect the "play it as it lies" fundamental to change anytime soon, if ever. Winter says new members of the rules committee want to discuss it from time to time, but it doesn't go beyond that.
"Philosophically, it's hard to think of a different way we'd want to go," he says.
And remember the next time you're in one, things could be worse. Just ask Jordan Spieth about his Sunday round at the Sentry Tournament of Champions in January. He found his ball in a divot crater on three consecutive holes down the stretch!
"The [divots] were certainly tough breaks because they were balls that hit in the fairway and funneled into them," Spieth said. "Out here, balls funnel into the same spots a lot. It’s not uncommon to be in divots. It kind of stunk that it was three holes in a row, but I still played [them] just fine."
[ed. BS. Expect this rule to be changed in the not too distant future. If you can tamp down spike marks on greens and are awarded relief from sprinkler heads, why not this? The reasoning itself is contradictory. As noted in the article, divots are everywhere, but how often do you actually have to play out of one? Not often. That's why you also have so-called "winter rules" allowances during certain portions of the year, and lift-clean-and-place exceptions during especially rainy/water soaked conditions - simply efforts to apply consistency when inconsistent conditions exist. So, wtf?]
It's at those moments when you might wonder why the Rules of Golf doesn't allow you to take free relief. After all, Rule 16.3 allows you to remove an embedded ball anywhere in the general area of the course without penalty. How is this any different, you might wonder?
"It's fundamental to golf to play the ball as it lies," he says. "And you don't always get a good lie."
Although the USGA and R&A, golf's governing bodies, have considered on various occasions handling divot holes in another manner, there is no "practical solution" other than to leave it as just a part of the game, Winter says. If you think about it beyond the moment you're in one, how often does it happen to you in any golf season? Probably not a lot. Furthermore, if the rules makers were to treat divot holes as, say, ground under repair, think of how many spots on the fairway would then fall into that category? They're all over the place. They take a long time to heal, and they typically are not a focus of normal golf-course maintenance.
For these reasons, don't expect the "play it as it lies" fundamental to change anytime soon, if ever. Winter says new members of the rules committee want to discuss it from time to time, but it doesn't go beyond that.
"Philosophically, it's hard to think of a different way we'd want to go," he says.
And remember the next time you're in one, things could be worse. Just ask Jordan Spieth about his Sunday round at the Sentry Tournament of Champions in January. He found his ball in a divot crater on three consecutive holes down the stretch!
"The [divots] were certainly tough breaks because they were balls that hit in the fairway and funneled into them," Spieth said. "Out here, balls funnel into the same spots a lot. It’s not uncommon to be in divots. It kind of stunk that it was three holes in a row, but I still played [them] just fine."
by Ron Kaspriske, Golf Digest | Read more:
Image: Ross Kinnaird[ed. BS. Expect this rule to be changed in the not too distant future. If you can tamp down spike marks on greens and are awarded relief from sprinkler heads, why not this? The reasoning itself is contradictory. As noted in the article, divots are everywhere, but how often do you actually have to play out of one? Not often. That's why you also have so-called "winter rules" allowances during certain portions of the year, and lift-clean-and-place exceptions during especially rainy/water soaked conditions - simply efforts to apply consistency when inconsistent conditions exist. So, wtf?]
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