What I’m reading
A few reads from the weekend.
Where did all the affordable cars go?
What started in 1964 as a retaliatory strike against European duties on American poultry grew over time into an impenetrable shield to safeguard domestic automakers’ sales of light trucks and United Auto Workers’ jobs from a rising tide of foreign imports. Both political parties participated; in 1981 the Reagan administration pressured the Japanese government to cap vehicle exports, leading the Japanese to shift to more expensive vehicles that would increase profit. Detroit, naturally, raised prices as well.
Even during the free trade era of NAFTA — initially proposed by President Ronald Reagan, negotiated by President George H.W. Bush and ultimately pushed through by President Bill Clinton — the United States maintained a tariff on passenger cars from outside North America. During this period, lawmakers set fuel economy standards for trucks and S.U.V.s that were roughly six to eight miles per gallon less stringent than those for cars. They’d hoped the change would keep costs low for farmers and tradespeople who needed larger engines for heavy work, but it ultimately helped drive Detroit to dump the fuel-efficient sedan for the large, high-profit-margin S.U.V.
Decades of protectionism shielded Detroit from the robust global competition that would have forced it to match the quality, fuel efficiency and pricing of its foreign rivals — and had the unintended consequence of forcing millions of Americans to pay well above market prices elsewhere in the world.
Looking back at an old Kurzweil post on personal AI companions
There have been other attempts to show AIs as humans (albeit not biological) that you can have a relationship with; for example, Steven Spielberg’s 2001 film AI. That movie suffered from an all-too-common flaw of science futurism movies: it introduced a single futuristic technology — human-level cyborgs — onto an otherwise unchanged world. Her is better in this dimension, although not completely successful. It does portray a somewhat futuristic world in which the leap to human-level AIs is not so implausible.
I would place some of the elements in Jonze’s depiction at around 2020, give or take a couple of years, such as the diffident and insulting videogame character he interacts with, and the pin-sized cameras that one can place like a freckle on one’s face. Other elements seem more like 2014, such as the flat-panel displays, notebooks and mobile devices.
Samantha herself I would place at 2029, when the leap to human-level AI would be reasonably believable.
Paying to get into college – but also paying to get your kids a job after
Career coaching for college students can cost a few hundred dollars an hour for interview rehearsals and application strategies, with more comprehensive packages typically ranging from $3,000 to $10,000. But New York City-based Priority Candidates says some parents are paying upwards of $30,000 for intensive support and subject-matter experts to prepare their children for entry-level jobs in finance and similarly ultra-competitive industries; the price tags at other companies go up from there.
People are paying more and getting less. This is what I call the upper middle class trap.
Right now, the upper middle class is in fierce competition for a marginal improvement in lifestyle. They’re working more and relaxing less to purchase products and services with clearly declining quality. It’s a financial arms race that doesn’t make any sense.
You have people making six-figure incomes going into a frenzy for nicer homes, better schools, and more luxurious travel experiences. What’s the end result of this status contest? Overpaying, and by a lot.
This same competitiveness partially explains why college tuition and private school costs have grown twice as fast as overall inflation over the past few decades. With more students applying to roughly the same number of spots, you can keep raising prices.
This is especially true at the top universities. Since 2015, the number of college applicants has gone up 78% while acceptance rates at elite colleges have plummeted:
This increasing struggle for scarce positional goods keeps the upper middle class overworked and trapped in the rat race.
The study by Ataman, Beyersmann, Castles, and Wegener, explores a simple question; when we hear a new word, do we start forming a guess about how it is spelled before we ever see it written down? The authors call these guesses “orthographic skeletons”.
The concept, first proposed by Wegener and colleagues in 2018, is based on a deceptively simple insight: when a child learns a new word orally, hearing it spoken, understanding its meaning, using it in conversation, their knowledge of how sounds map onto letters (phoneme-grapheme correspondences) allows them to generate an expectation about how that word might be spelled. Not a complete, fully formed spelling, but a partial sketch; a skeleton.
To test this, researchers use invented nonsense words like “vish” or “jayf,” words that no participant has ever encountered before, so the experimenters can be certain that any spelling expectations were formed purely from oral training rather than prior reading experience. So take a reader who has been taught the spoken word “vish,” its meaning and its use in sentences, but has never seen it written down. Their knowledge of English spelling patterns tells them that the /v/ sound is typically written as “v,” the /ɪ/ sound as “i,” and the /ʃ/ sound as “sh.” Without ever seeing the word in print, they have already begun to assemble its orthographic form.
When that reader later encounters “vish” written on a page, the word is not entirely novel. It arrives into a cognitive space that has been prepared for it, a space where expectation meets confirmation. The result, demonstrated across multiple studies using both lexical recognition tasks and eye-tracking, is faster processing, shorter fixation times, and more efficient reading. The skeleton has done its invisible work.