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Last Thursday and Friday, the Dallas Fed held a terrifically interesting conference on the massive, long-term disruption flowing from the technological revolution. I packed as much of the best stuff as I could in today's newsletter.
I'd love to hear your ideas of what we ought to cover, are getting wrong, or anything else you care to share. Just hit reply to this email or shoot me a message at firstname.lastname@example.org. Let's start with ...
Illustration: Rebecca Zisser/Axios
For decades, U.S. tech startups have been the beating heart of Silicon Valley. But almost unnoticed by economists, they are now in the same funk dogging some other sectors of the American economy.
Quick take: American startups are in a 13-year slump, their numbers shrunken from their heyday and, with a few conspicuous exceptions, their inventions not the financial world-killers of prior kin, according to new research.
Why it matters: In the booming 1980s and 1990s, much of U.S. job and productivity growth was the handiwork of a few young startups and their hit innovations. But the decline, which began in 2005, has stripped the economy of one of its most vibrant engines of wage and productivity growth, says John Haltiwanger, an economist at the University of Maryland.
The background: For years, economists have been trying to figure out why productivity growth in major western economies has been flat despite soaring corporate profit, low joblessness and low inflation. Among the reasons they have come up with:
Haltiwanger dismisses neither of those reasons, but tells Axios that the loss of the propulsion of startups is a primary reason for the current malaise. He speculates that Big Tech companies may be buying up a lot of them before they make their big splash, thus smothering their potential.
Illustration: Rebecca Zisser/Axios
A group of economists say they have an answer to why, besides a spurt during the dotcom boom, productivity growth has been under half the historical trend since 1970.
Quick take: As discussed briefly above, Chad Syverson, an economics professor at U Chicago, said technological history has been one of lag-times between the launch of new technologies and their visibility in productivity numbers. In work he did with MIT's Erik Brynjolfsson and Daniel Rock, Syverson said advances in artificial intelligence in particular simply have not worked their way through the economy and into complementary products.
He cited analogies:
Syverson and his co-authors call this "diffusion" — when a big invention like electricity and internal combustion comes into its own and spawns hundreds or thousands of devices that themselves are also huge but could not otherwise exist.
Around the world, an Apple store is a sign of retail health. Here, in Palo Alto, CA. Photo: Photo: Smith Collection/Gado/Getty Images
The death of the U.S. retail mall will be worse than forecast — with just a quarter of the current 1,200 or so surviving, says former J.C. Penney CEO Mike Ullman.
Quick take: Until now, most experts have said that a quarter of the malls will close. But, speaking on a panel, Ullman reversed the numbers, estimating that only about 300 malls will make it. The rest will close over the next five years, becoming victims of decades-long changes in consumer taste, including the recent impact of Amazonization.
The background: Rockport is the latest U.S. retail chain to file for bankruptcy, on top of 11 others this year, and Sears is closing another 40 stores, Business Insider reports. That is leaving gaping holes in malls.
How and why the survivors will make it: Ullman said malls must have adequate cash or access to financing to make the transition to a new style of retail, in addition to a location catering to the top income quartile.
Call center workers are targeted for automation. Here, in Lakewood, CO. Photo: Michael Reaves/Denver Post/Getty Images
Few Americans have enjoyed steadily rising pay after inflation over the last couple of decades, a shift from prior years when the working and middle classes enjoyed broad-based wage gains as the economy expanded.
Why it matters: Now, executives of big U.S. companies suggest that the days of most people getting a pay raise are over, and that they also plan to reduce their work forces further.
Quick take: This was rare, candid and bracing talk from executives atop corporate America. The message is that Americans should stop waiting for across-the-board pay hikes coinciding with higher corporate profit; to cash in, workers will need to shift to higher-skilled jobs that command more income.
Troy Taylor, CEO of the Coke franchise for Florida, said he is currently adding employees with the idea of later reducing the staff over time "as we invest in automation." Those being hired: technically-skilled people. "It's highly technical just being a driver," he said.
Because of the changes coming, AT&T is pushing employees to take nano-degree programs to prepare them for other jobs — either at AT&T or elsewhere.
Illustration: Sarah Grillo/Axios
Banks are cut out of China's shopping juggernaut (Jennifer Surane and Christopher Cannon — Bloomberg) [h/t Azeem Azhar]
Getting into position for 6G (Michael Koziol — IEEE Spectrum) [h/t Rahim Hirji]
The new era in data privacy (Sara Fischer and Kim Hart — Axios)
Trump proposes axing Foreign Entrepreneur Rule (Stef Kight — Axios)
China has been beating the West at infrastructure for two decades (Bushra Bataineh, Michael Bennon, and Francis Fukuyama — Foreign Affairs)
Liberal arts versus practical skills (Frank Bruni — NYT)
Photo: William Lovelace/Daily Express/Hulton Archive/Getty Images
Among efforts to make social media a more congenial place, researchers at Cornell are working on artificial intelligence that detects nasty online conversations when they are only starting to take that turn.
What's going on: Most studies of online conversation look for phrases such as, "What the hell is wrong with you.” But, by then, it's too late. In their new paper, Justine Zhang, Jonathan Chang and Cristian Danescu-Niculescu-Mizil say they aim to ferret out anti-social clues "when the conversation is still salvageable."
How they did it: The Cornell team studied some 1,200 conversations on Wikipedia Talk pages, reports MIT Tech Review, in a collaboration with researchers from Jigsaw and Wikimedia.
Among their findings:
That won't surprise many of us: The researchers found that humans are still better at this than AI — a control group of humans detected a bad conversation in advance 72% of the time, compared with 61.6% for the AI.
One bit of good news: In some of the conversations their AI had flagged, the humans eventually self-corrected.