To know, within an hour or two of an event, that someone is safe: It’s so valuable, so emotionally practical, as to be almost priceless. It is anti-terror, in a way: It says, be not afraid. And in the three places where it was first deployed—Afghanistan, Chile, and Nepal, all three after major earthquakes—its activation made a lot of sense, because earthquakes are events which by their nature can affect millions over huge swaths of territory.
But earthquakes and cyclones are not themselves public-facing events. Terrorist attacks are. As Brian Jenkins, a terrorism scholar at the RAND Corporation, writes, “terrorism is aimed at the people watching.” Terrorism is a public-relations campaign with guns and bombs. It weaponizes culture, and it exploits journalistic concern for heinous violence to grab media attention and get pathology taken instead as politics.
There are two conferences happening in NYC this weekend that I’m planning on going to. Platform Cooperativism just got started this morning and runs through tomorrow at The New School. The Creative Time Summit is happening Saturday/Sunday, at a high school in Bedford-Stuyvesant. I’m not sure how I’ll juggle both events tomorrow, but Platform Cooperativism has a livestream going if you want to follow along from home.
The Uberpeople forum exists in a state of quivering rage I usually associate with cable-news talk shows. Drivers are furious about everything. Spoiled passengers. Fare cuts. Living in fear of arbitrary ratings. The dumb Spotify thing streaming over the driver’s data plan rather than the passenger’s. A bunch of drivers are even using the forum as a home base to try to unionize in several cities.
But I also find some useful numbers to fill in the vagaries of the training video. For example, I should accept 90% of pings to avoid trouble. I’m also surprised to learn that Uber’s cutoff for driver ratings “below rider expectations” is generally agreed to be only 4.6 stars—I’d had no idea when using Uber as a passenger that rating someone four stars was kind of a big deal.
(photo by Jessica Kourkounis)
So what does a 4-star ride look like?
I’ve had a perfect rating for almost a week when I get a ride that I can tell is going to screw it up. I pull up, blocking a one-way street, and throw on my blinkers. After waiting the requisite few minutes, I text the guy. He opens the front door, makes a “one minute!” gesture, then shuts it again. Several more minutes tick by. I finally call, and the guy picks up, giggling. “We’ll be right out!”
When the couple finally gets in, nearly 10 unpaid minutes after I showed up, a cloud of weed stank follows them into my car. I try to hide my irritation. They’re headed to a restaurant in Chinatown I’ve been to a bunch of times, so we chat about that as I drive. Despite this, the stoned guy insists on giving me inefficient directions. When he directs me to turn the wrong way down a one-way street, I tell him not to worry, I’ve got this, and just drive them to the restaurant. The guy sulks.
The next day, my five-star rating has updated to a 4.8.
It’s a good article, and I’m slightly worried that it’s published in a publication that’s been shut down recently.
The website remains accessible for now, but if it were to go offline archive.org won’t have a copy: “Page cannot be crawled or displayed due to robots.txt.”
The Verge’s Josh Dzieza on how Uber and its peers “turned us into horrible bosses.”
The rating systems used by these companies have turned customers into unwitting and sometimes unwittingly ruthless middle managers, more efficient than any boss a company could hope to hire. They’re always there, working for free, hypersensitive to the smallest error. All the algorithm has to do is tally up their judgments and deactivate accordingly.
Ratings help these companies to achieve enormous scale, managing large pools of untrained contract workers without having to hire supervisors. It’s a nice arrangement for customers too, who get cheap service with a smile—even if it’s an anxious one. But for the workers, already in the precarious position of contract labor, making every customer a boss is a terrifying prospect. After all, they—we—can be entitled jerks.
One question—maybe the most pressing question—is how the public feels about that brutal ratio of one targeted death to five or six unintended. The evidence so far is that the public is more or less okay with it.
Behold: an amazing cultural artifact drawn by R. Sikoryak, each page in the style of a different comics artist. On page 12 we learn that underage users must be read the Terms and Conditions by a parent or guardian, in the style of R. Crumb.
Ellie wrote an essay that was recently published in the Brooklyn Rail. She makes a case for weeds, in urban spaces that are lacking in green spaces.
Based on growing evidence for the role of greenspace in mental health and the importance of plant life for a slew of environmental services (including temperature regulation, air quality improvement, and soil stabilization), the plant community I work with is beneficial and should be embraced. A small but growing cadre of defenders respectfully refer to these plants as “spontaneous urban plants” that inhabit “novel ecosystems” which are in urgent need of further study.
Forest Enclosure, Johnson Avenue. [Feral Landscape Typologies](http://ellieirons.com/projects/feral-typologies/)
To the average city-dweller, and compared to their cultivated counterparts, the species I advocate for can appear “messy” and unrefined: flowers that are too small, seed pods that are too big, thorns that tear clothing, roots that reach into brick and asphalt. They may seem indicative of disrepair, of indolence, of a community down on its luck or still climbing towards peak gentrification. It is perhaps this sensibility that drives building superintendents and maintenance crews out into the streets to “clean up” (massacre) these plants on a regular basis.
Robinson Meyer wrote a great essay in The Atlantic about the difference between saying and writing on Twitter:
On Twitter, people say things that they think of as ephemeral and chatty. Their utterances are then treated as unequivocal political statements by people outside the conversation. Because there’s a kind of sensationalistic value in interpreting someone’s chattiness in partisan terms, tweets “are taken up as magnum opi to be leapt upon and eviscerated, not only by ideological opponents or threatened employers but by in-network peers.”
Anthropologists who study digital spaces have diagnosed that a common problem of online communication is “context collapse.” This plays with the oral-literate distinction: When you speak face-to-face, you’re always judging what you’re saying by the reaction of the person you’re speaking to. But when you write (or make a video or a podcast) online, what you’re saying can go anywhere, get read by anyone, and suddenly your words are finding audiences you never imagined you were speaking to.
Honan talked to a woman from the parrot-renting company, Happy Birds, about what it’s like to receive a request from M. Turns out it’s just a person with a phone.
“She said, ‘I’m doing it for someone else.’ She said ‘well, it’s for my boss’ friend.’”
There was another indicator, however, that this was a legitimate request. Just after the woman claiming to be M called Happy Birds, the company received an identical request through GigSalad — an online platform where performers and event services can connect with interested clients.
This wasn’t the only time I saw evidence of M turning to independent contractors on other platforms to execute requests. When I tried to get it to send a Minion to my colleague Katie Notopolous (she loves Minions) it helpfully offered that “I am able to set up a Tasker with Task Rabbit to go purchase a minion costume and can come interact and entertain for 20-30 min at a rate of $150 for the hour.” (I deemed this too expensive.)
In fact, much of M’s real-word efforts seem to run on contractors. Facebook confirmed to BuzzFeed News that the trainers are all independent contractors. Which to some extent answers the question of how Facebook can scale this up, before M becomes fully automated. It will take an army of humans, each doing small tasks. Simply put, before Facebook can make its robot act like lots of humans, it needs a lot of humans to act like robots.
