The Greater Orlando Aviation Authority on Wednesday took steps toward that future by seeking partners to develop and operate a flying car landing pad — called a vertiport — at the airport. The invitation is expected to publish in March with a 2028 target for a finished product.
The airport expects to put the vertiport on land in the East Airfield region on the northeast side or land on the south side near the train station, according to a news release…
Orlando Mayor Buddy Dyer, a member of the aviation authority, said the city is a global leader in Advanced Air Mobility (AAM) — the technology behind flying cars — and having the hub at the airport makes sense…
He said vertiports may help manage the city’s growth, but that’s much farther off. He envisions starting with a four- to six-passenger vehicle operating out of the airport and eventually corridors for flying cars will follow. The small aircraft are expected to use electric power, and take off and land vertically.
Three thoughts on these plans:
It sounds like Orlando wants to pursue this to contribute to its economic growth. It could become a leader in flying cars. How big of an industry could this be? Americans like cars, Americans dislike traffic…could this be a big growth industry in the coming decades?
The connections between this and the numerous theme parks in the area are intriguing. Would visitors be willing to try these because this is an exciting place to visit? Could the flying cars be linked to Disney or Universal or other partners?
Flying car corridors will be interesting to see. How will they work and where will they be? How visible will they be from the ground? Will they also have gridlock?
Flying cars could be cool but if they lead to similar problems plaguing cars at the moment – traffic, expensive to buy a vehicle and maintain it, etc. – it may not get off the ground.
The weepy confessions are, ostensibly, gestures toward intimacy. They’re meant to inspire empathy, to reassure viewers that influencers are just like them. But in fact, they’re exercises in what I’ve come to call “McVulnerability,” a synthetic version of vulnerability akin to fast food: mass-produced, easily accessible, sometimes tasty, but lacking in sustenance. True vulnerability can foster emotional closeness. McVulnerability offers only an illusion of it. And just as choosing fast food in favor of more nutritious options can, over time, result in harmful outcomes, consuming “fast vulnerability” instead of engaging in bona fide human interaction can send people down an emotionally unhealthy path…
McVulnerability is perhaps an inevitable outcome of what the sociologist Eva Illouz identifies as a modern-day landscape of “emotional capitalism.” “Never has the private self been so publicly performed and harnessed to the discourses and values of the economic and political spheres,” Illouz writes in her book Cold Intimacies. Emotional capitalism has “realigned emotional cultures, making the economic self emotional and emotions more closely harnessed to instrumental action.” That is, not only does emotionality sell goods, but emotions themselves have also become commodities…
McVulnerability, from whichever angle you look at it, is the opposite of generous. It doesn’t require risk. It may pretend to give, but ultimately, it takes. And it leaves most of its consumers hungry for what they’re craving: human connection—the real thing.
The “Mc-” prefix makes sense given the popularity of McDonald’s. The way the term is deployed above seems similar to how the term McMansion has been used for several decades. McVulnerability is a pale substitute for true vulnerability. It is vulnerability in a popular and commodified form.
But can the term stick? It may depend on the popularity of such viral videos. Do they have staying power or will they be gone to be replaced by other trending videos? Will this pattern last for years? Or there might be other terms that describe these videos. Or the critique may not stick – what if most watchers see the emotional expressions as real and valuable? If such expressions become the new normal, perhaps McVulnerability is here to stay.
We’ll have to wait and see. McDonald’s will go on and plenty of other mass produced products and experiences will come along. Which ones will live on in “Mc-” infamy?
The temporary loss of TikTok in the United States a few days ago was a sort of natural experiment and it did make me wonder: what if social media was gone tomorrow?
Numerous areas of life would be affected. Here are just a few:
People and companies making money. Whether through ads or selling things or streaming, money flows through social media.
How people use their time. What would people do instead? Watch more TV (this was a primary activity before social media existed)? Talk to the people around them? Go outside?
Where people get information, whether about people they know or the news or the standard information people today are supposed to know (ranging from viral videos to celebrity updates to conflict on the other side of the world).
Connections to people. The easy access to people through posts and profiles and social media interactions would be gone. Could the connections happen through other mediums?
A whole set of rituals, norms, and discussions would be lost. They could not be accessed or scrolled through. All that time managing images and interactions goes away.
Even with all these changes (which would take some time to get used to), this question might be most important: would life be better?
All said, it is a relatively small segment of the population that is “very online” with respect to social media, or that regularly consumes jouranalistic media in virtually any format (TV, online, print, podcasts) – let alone engaging with research by think tanks, nonprofits, activists, or academics. Mostly, it’s people like us. Virtually the entire political and cultural melodrama carried out in academia, policymaking spaces, media outlets, and social networking sites it carried out among symbolic capitalists. The views and priorities of most others are simply unrepresented in these spaces. And for their part, most of those who are not symbolic capitalists are not particularly interested in the highly idiosyncratic struggles we invest so much of ourselves into. (195)
This seems consistent with earlier reports I’ve seen. Social media activity is driven by a small set of users who are not representative of the American population at large.
This could be helpful to keep in mind when wondering if social media is fragmented or how widespread a trend is or whether algorithms could be driving people to different corners of the Internet. These features might be true AND social media as a whole might be driven by a small set of people who share particular positions and practices.
(Read more about the definition of symbolic capitalists here.)
Just how accurate are those numbers, though? Until the house actually trades hands, it’s impossible to say. Zillow’s own explanation of the methodology, and its outcomes, can be misleading. The model, the company says, is based on thousands of data points from public sources like county records, tax documents, and multiple listing services — local databases used by real-estate agents where most homes are advertised for sale. Zillow’s formula also incorporates user-submitted info: If you get a fancy new kitchen, for example, your Zestimate might see a nice bump if you let the company know. Zillow makes sure to note that the Zestimate can’t replace an actual appraisal, but articles on its website also hail the tool as a “powerful starting point in determining a home’s value” and “generally quite accurate.” The median error rate for on-market homes is just 2.4%, per the company’s website, while the median error rate for off-market homes is 7.49%. Not bad, you might think.
But that’s where things get sticky. By definition, half of homes sell within the median error rate, e.g., within 2.4% of the Zestimate in either direction for on-market homes. But the other half don’t, and Zillow doesn’t offer many details on how bad those misses are. And while the Zestimate is appealing because it attempts to measure what a house is worth even when it’s not for sale, it becomes much more accurate when a house actually hits the market. That’s because it’s leaning on actual humans, not computers, to do a lot of the grunt work. When somebody lists their house for sale, the Zestimate will adjust to include all the new seller-provided info: new photos, details on recent renovations, and, most importantly, the list price. The Zestimate keeps adjusting until the house actually sells. At that point, the difference between the sale price and the latest Zestimate is used to calculate the on-market error rate, which, again, is pretty good: In Austin, for instance, a little more than 94% of on-market homes end up selling for within 10% of the last Zestimate before the deal goes through. But Zillow also keeps a second Zestimate humming in the background, one that never sees the light of day. This version doesn’t factor in the list price — it’s carrying on as if the house never went up for sale at all. Instead, it’s used to calculate the “off-market” error rate. When the house sells, the difference between the final price and this shadow algorithm reveals an error rate that’s much less satisfactory: In Austin, only about 66% of these “off-market Zestimates” come within 10% of the actual sale price. In Atlanta, it’s 65%; Chicago, 58%; Nashville, 63%; Seattle, 69%. At today’s median home price of $420,000, a 10% error would mean a difference of more than $40,000.
Without sellers spoonfeeding Zillow the most crucial piece of information — the list price — the Zestimate is hamstrung. It’s a lot easier to estimate what a home will sell for once the sellers broadcast, “Hey, this is the price we’re trying to sell for.” Because the vast majority of sellers work with an agent, the list price is also usually based on that agent’s knowledge of the local market, the finer details of the house, and comparable sales in the area. This September, per Zillow’s own data, the typical home sold for 99.8% of the list price — almost exactly spot on. That may not always be the case, but the list price is generally a good indicator of the sale figure down the line. For a computer model of home prices, it’s basically the prized data point. In the world of AVMs, models that achieve success by fitting their results to list prices are deemed “springy” or “bouncy” — like a ball tethered to a string, they won’t stray too far. Several people I talked to for this story say they’ve seen this in action with Zillow’s model: A seller lists a home and asks for a number significantly different from the Zestimate, and then watches as the Zestimate moves within a respectable distance of that list price anyway. Zillow itself makes no secret of the fact that it leans on the list price to arrive at its own estimate…
So the Zestimate isn’t exactly unique, and it’s far from the best. But to the average internet surfer, no AVM carries the weight, or swagger, of the original. To someone like Jonathan Miller, the president and CEO of the appraisal and consulting company Miller Samuel, the enduring appeal of the Zestimate is maddening. “When you think of the Zestimate, for many, it gives a false anchor for what the value actually is,” Miller says.
Multiple factors are at play here. Who has what information about housing and housing values? How is the value calculated? And what is the distribution of the comparison of the estimated value to the actual sales value? Some of this involves data, some involves algorithms.
It also sounds like part of the story is that Zillow has built one of the more effective brands in this space. Even if the estimates are not exactly right, people are drawn to Zillow. What would happen if competitors advertised that they are more accurate? Would this be enough to move people from using Zillow?
Given all of this, who can build the most accurate number might not be the “winner.” Is the goal to best model the housing market or is the goal to attract users? These two goals might go together but they might not.
Elon Musk‘s company SpaceX is looking to make Starbase, Texas, the home of its starship development and production facility, an official town.
Starbase is currently an unincorporated community within Cameron County, in the Rio Grande Valley…
“To continue growing the workforce necessary to rapidly develop and manufacture Starship, we need the ability to grow Starbase as a community. That is why we are requesting that Cameron County call an election to enable the incorporation of Starbase as the newest city in the Rio Grande Valley,” Starbase general manager Kathryn Lueders said in a letter to Cameron County Judge Eddie Trevino.
To make Starbase official, Trevino must order a special election to incorporate the community as a Type-C Municipality. Registered voters in the area must approve the change.
According to Lueders, incorporating Starbase will streamline the process to make Starbase a “world-class place to live” and enable the Starship program to “fundamentally alter humanity’s access to space.”
A few thoughts about what sounds like an interesting community:
What will make it different from other American or Texas communities? Will it have a unique physical layout? Will day-to-day life be different than other communities? Beyond the launch facilities, what might set this apart?
Is Starbase a company town or just a community dominated by one industry? These sorts of communities can have interesting histories given their reliance on the rises and falls of the local industry.
Think of the branding and merchandise potential of the community. Shirts, hats, shot glasses, and more carrying a Starbase, Texas script or logo.
Part of the fixation on cultural algorithms is a product of the insecure position in which cultural gatekeepers find themselves. Traditionally, critics have played the dual role of doorman and amplifier, deciding which literature or music or film (to name just a few media) is worthwhile, then augmenting the experience by giving audiences more context. But to a certain extent, they’ve been marginalized by user-driven communities such as BookTok and by AI-generated music playlists that provide recommendations without the complications of critical thinking. Not all that long ago, you might have paged through a music magazine’s reviews or asked a record-store owner for their suggestions; now you just press “Play” on your Spotify daylist, and let the algorithm take the wheel.
If many culture industries struggle to know what will become popular – which single, film, book, show, or product will become wildly successful and make a lot of money? – critics can be one way to try to figure this out. What will the influential critics like? Will they champion particular works (and dislike others)?
Might we get to some point where we see algorithms as critics or acting with judgment and discernment? Right now the recommendation algorithms are a “black box” that users blindly follow. But what if the algorithms “explained” their next step: “You like this song and based on this plus your past choices, I now recommend this.” Or what if you could have a “conversation” back and forth with the algorithm as you explain your interests and it leads in particular directions. Or if the algorithm mimics the idiosyncrasies a human critic would have.
I wonder about the role of friends and social contacts in what they recommend or introduce people to. At their height, could cultural critics move people away from the choices of family and friends around them? In today’s world of recommending algorithms, how often does the patterns of friends and acquaintances move people in different directions?
Widely shared on social media, the atmospheric black and white shots — a mother and her child starving in the Great Depression; an exhausted soldier in the Vietnam war — may look at first like real historic documents.
But they were created by artificial intelligence, and researchers fear they are muddying the waters of real history…
For now, Amaral and Teeuwissen believe they can still tell fake historical images from real ones just by looking at them.
AI-generated photos often have tell-tale glitches: too many fingers on a hand, missing details — such as the lack of a propeller on the Wright brothers’ plane — or, on the other hand, compositions that are too perfect.
“AI-generated pictures can recreate the look, but they miss the human element, the intent, the reason behind the photographer’s choices,” said Amaral.
With AI text and images, history could be all redone. What is available online, often the first or primary source for many, could provide different historical accounts and evidence.
Of course, history to some degree is always in flux as different actors and different contexts affect how we understand what happened in the past. There are things that happened and then perceptions and interpretations of those happenings that often take time to develop and solidify. AI joins an already existing process.
Do AI images then pose a unique threat to historical knowledge and narratives? If history is primarily created and understood through images online, perhaps. Will others find ways to demonstrate that certain images are truly from the past?
As more actors express concerns about how social media use affecting the mental health of “children and teens,” this article suggests it can be hard to directly measure this link:
It doesn’t help that mental health is influenced by many factors, and no single treatment works for every person. “It’s not as straightforward as: What is the right antibiotic for that ear infection?” said Megan Moreno, a scientist and pediatrician at the University of Wisconsin-Madison, and co-director of the Center of Excellence on Social Media and Youth Mental Health at the American Academy of Pediatrics…
Among the reasons that make it difficult to isolate the role of social media in kids’ mental health is that the relationship between mental health and tech use is a two-way street, the panel from the National Academies of Sciences, Engineering, and Medicine said. A person’s mental state might influence how he or she uses the platform, which in turn affects his or her state of mind.
Randomized, controlled studies on whether social media caused the mental-health crisis are impractical because exposure to social media is now everywhere, researchers say. In addition, platforms are constantly changing their features, hobbling efforts to run long-term studies, they say.
A decade ago, Munmun De Choudhury, a computer scientist at Georgia Tech, was part of a team that showed that groups promoting disordered eating were skirting Instagram’s moderation efforts. De Choudhury says that such studies probably would be impossible today because social-media companies no longer allow access to public data, or charge hefty fees for it…
Research into the roots of distress in young people has found that other factors—bullying, or lack of family support—have stronger associations with mental-health outcomes, compared with social-media use.
These are different issues. This includes having access to data from platforms as well as data over time. Additionally, it takes work to separate out different influences on mental health. Randomized controlled trials that could help with this are difficult to put together in this situation. Other factors are shown to influence mental health.
Some think there is enough data to make the argument about social media use influencing mental health. For example, social psychologist Jonathan Haidt puts together evidence in his latest book The Anxious Generation. His approach is one that social scientists can take: there seem to be consistent patterns over time and other factors do not seem to account as well for the outcomes observed. And if there is a growing consensus across studies and scholars, this is another way for scientific findings to advance.
This is an ongoing situation as policy efforts and research efforts follow sometimes intertwining paths. If a state restricts social media use for teenagers and then mental health issues drop, would this count as evidence for social media causing mental health distress?
Instead of getting together with your rivals and agreeing not to compete on price, you can all independently rely on a third party to set your prices for you. Property owners feed RealPage’s “property management software” their data, including unit prices and vacancy rates, and the algorithm—which also knows what competitors are charging—spits out a rent recommendation. If enough landlords use it, the result could look the same as a traditional price-fixing cartel: lockstep price increases instead of price competition, no secret handshake or clandestine meeting needed…
According to the lawsuits, RealPage’s clients act more like collaborators than competitors. Landlords hand over highly confidential information to RealPage, and many of them recruit their rivals to use the service. “Those kinds of behaviors raise a big red flag,” Maurice Stucke, a law professor at the University of Tennessee and a former antitrust attorney at the Department of Justice, told me. When companies are operating in a highly competitive market, he said, they typically go to great lengths to protect any sensitive information that could give their rivals an edge.
The lawsuits also argue that RealPage pressures landlords to comply with its pricing suggestions—something that would make no sense if the company were merely being paid to offer individualized advice. In an interview with ProPublica, Jeffrey Roper, who helped develop one of RealPage’s main software tools, acknowledged that one of the greatest threats to a landlord’s profits is when nearby properties set prices too low. “If you have idiots undervaluing, it costs the whole system,” he said. RealPage thus makes it hard for customers to override its recommendations, according to the lawsuits, allegedly even requiring a written justification and explicit approval from RealPage staff. Former employees have said that failure to comply with the company’s recommendations could result in clients being kicked off the service. “This, to me, is the biggest giveaway,” Lee Hepner, an antitrust lawyer at the American Economic Liberties Project, an anti-monopoly organization, told me. “Enforced compliance is the hallmark feature of any cartel.”
The company disputes this description, claiming that it simply offers “bespoke pricing recommendations” and lacks “any power” to set prices. “RealPage customers make their own pricing decisions, and acceptance rates of RealPage’s pricing recommendations have been greatly exaggerated,” the company says.
It will be interesting to see how the courts decide in this area.
I would be curious to hear how this process differs from the way housing prices are determined. The “correct price” does not just emerge. There are a set of actors – such as realtors, appraisers, and websites – that contribute. There are local histories that inform current and future prices. The housing market follows particular patterns and I recommend reading sociologist Elizabeth Korver-Glenn’s 2021 book Race Brokers: Housing Markets and Segregation in 21st Century Urban Americaon this topic.
Is the primary difference that there is not a centralized tech source for housing prices? (But maybe there is – how much has Zillow and its Zestimate changed the game?) Or are the new actors viewed with more suspicion than others (tech sector versus realtors)? Or are we in a particular social moment where high costs of housing prompt more questions and thoughts about alternative?
Legally Sociable 