Aggregator
Dolly Parton’s niece confirms star’s burial: ‘Laid to rest yesterday’
Jalisco Cartel kingpin’s secret California ranch in Riverside County revealed
Cowboys acquire former first-round draft pick Broderick Jones to beef up offensive line
Shameful: Republicans help SEIU defy Gavin Newsom’s return to work order
Jets once introduced a bizarre fight song into the mix — it offers an important reminder
What Happened To The So-Called AI Job Apocalypse?
Authored by Joe Bertolami via RealClearMarkets,
A recent report from Stanford reviewed the latest employment data and found that, so far, AI has not resulted in large scale job destruction. Meanwhile, new hiring data from the Economic Times reveals that AI is actively fueling unprecedented job creation, with AI skills now powering nearly two-thirds of new Global Capability Center hiring. Together, these recent dispatches from the front lines of the labor market point to a calming reality: the much-dreaded AI job apocalypse hasn't materialized as a sudden extinction event.
The (sometimes buried) lede: AI is delivering real impact, and it is broadly changing the nature of work. But disruption is not a new phenomenon. The economy has always dismantled old work to build new work. What determines whether this evolution feels like progress or collapse isn't just the number of jobs lost, it's the speed at which that loss hits the labor market.
In 1995, Bill Gates circulated a memo titled "The Internet Tidal Wave," calling the web the most important computing development since the IBM PC. If the internet was a tidal wave, artificial intelligence is a tsunami. It is arguably the biggest advancement in computing since the Turing machine. Yet, from a distance, it's difficult to appreciate the speed of this wave, leading many to wonder when the broader economy will truly feel its impact.
To put this in context, we must understand the historical pattern already visible in the labor market. Combining decades of data from the U.S. Bureau of Labor Statistics and the Federal Reserve yields a remarkably consistent story of overlapping curves: job loss and job creation. Over the last two decades, nearly 20 million U.S. jobs vanished in disrupted sectors. Over the same period, total payrolls grew by 25.7 million. That equates to roughly 1.3 new jobs for every one destroyed. Classic examples include jobs in video rentals (-98.9%) and word processing (-83%) which largely vanished, but new work sprung up at the same time in areas like data processing (+54%) and warehousing (+260%) to support the digital economy.
The data also reveals an early signal that separates an absorbable decline from a brutal collapse: the disruption half-life, or how long an occupation takes to lose half its peak employment. Across the largest technological disruptions of the last few decades, the median half-life is about 10 years. Fast disruptions, like photo processing, take one to five years. Typical disruptions take eight to 13 years. And time is the ultimate shock absorber. When the economy transitions over ten years it feels like progress rather than a fast collapse, because it gives older workers time to retire and younger workers time to prepare.
If we track the most AI-exposed occupations-customer-service reps, IT support, telemarketers-since modern LLMs arrived in 2022, the early data is measured. After three years the current disruption looks closer to "typical" than a fast collapse, even before discounting the effects of offshoring, automation, and post-COVID corrections. This is Amara's Law playing out in real time: we tend to overestimate the effect of technology in the short run and underestimate it in the long run. The dire early warnings have given way to more cautious rhetoric. In 2025, Anthropic's Dario Amodei warned AI could erase half of entry-level white-collar jobs within five years. By 2026, he and OpenAI's Sam Altman are emphasizing productivity, economic growth, and the continued demand for human labor.
However, looking solely at total employment numbers masks a dangerous structural threat. Current evidence does not foretell the end of human labor, but AI is quietly breaking the mechanism by which we create experienced workers.
Software engineering is the canary in the coal mine. By most aggregate measures, employment looks stable; unemployment held at 4.2% in June 2026, and groups like the Yale Budget Lab find no clear AI effect yet on exposed occupations' absolute job totals. But the composition is shifting underneath our feet. Per AP and Oxford Economics, junior developer postings are down roughly 40% in four years. Employment for 22-to-27-year-old computer and math grads has fallen 8% since 2022, even as older grads in the same fields have edged up. This same erosion is surfacing wherever entry-level work once meant routine tasks: paralegals, junior analysts, and first-line support.
The paradox is that these industries keep growing even as their entry-level doors narrow. The BLS still projects software developers and QA analysts to grow 15% through 2034. But that projection relies on a pipeline that turns juniors into senior talent-precisely the pipeline now being choked off.
The reason lies in the nature of the work. Software development is a process of judgement and accountability: deciding what to build, executing it, and owning the result. AI is fluent at the middle layer-the well-specified, routine coding that once served as a junior's apprenticeship. But it remains far weaker at the judgment required on either side. The tasks AI automates are precisely the ones juniors were hired to learn on.
This is not merely an academic concern; it is a capital allocation problem. Misjudge the speed of disruption and you risk premature layoffs followed by a scramble to rehire, or funding the transition years too late, leaving you with a critical talent shortage when the leadership pipeline runs dry.
The challenge of the next decade isn't surviving the end of work. It is training the next generation of experts when the traditional paths to apprenticeship no longer exist. And businesses are beginning to realize this new reality as demand for AI continues to grow. IBM is tripling its entry-level hiring, redesigning those roles around the oversight of AI and systems thinking rather than cutting them. Rebuilding the entry-level on-ramp is now a competitive imperative.
Junior roles are not charity; they are talent capex. If AI creates more work than it destroys, companies will still need people who know how to run it, judge it, and fix it. AI may be the broadest technology yet, but that breadth is its best reason for optimism. A general-purpose technology seeds new work across every sector. The firms that recognize this, protect their entry-level pipelines, and keep training now are the ones who will own the senior labor market later.
Joe Bertolami is the Co-Founder and CTO at Clifton AI, an agentic context engine for investment research. Previously at Snap, Google, and Microsoft, with a couple of startups in between. He holds an M.B.A. from the University of Washington and likes using AI to write code, stories, and music, which he posts at https://www.bertolami.com.
Tyler Durden Sat, 08/29/2026 - 19:50Socialists offer more of the same decay while LA crumbles in the dark
Bills releasing former Super Bowl champion Mecole Hardman
Jets leave onlookers horified as they nearly hit roof of South African stadium during pre-game flyover: ‘Could’ve been catastrophic’
Mets get contributions from everyone in all-around win against Astros
CDC Reports COVID-19 Activity Is Increasing Across US
The Centers for Disease Control and Prevention on Friday said COVID-19 activity is "increasing" across the United States although its levels are still considered "very low" overall.
"As of August 26, 2026, we estimate that COVID-19 infections are growing or likely growing in 48 states, declining or likely declining in zero states, and not changing in two states," the CDC said on Friday.
Overall community viral activity levels, or a measurement of the virus in wastewater levels, for COVID-19 is considered by the CDC to be "very low." Emergency department visits were also considered "very low," which is the lowest ranking on the CDC's website, with "very high" being the top.
According to a Friday update on the CDC's website, wastewater data show that COVID-19 activity is "very high" in Texas and "high" in Mississippi.
"Moderate" levels were observed in California, Florida, Hawaii, Louisiana, Nevada, South Carolina, and West Virginia.
All other states were listed as either "very low," "low," or there was limited or no data.
As Jack Phillips reports for The Epoch Times, another map provided by the CDC on Friday shows that COVID-19 levels were either "growing" or "likely growing" in every state where data was available.
Influenza levels are also growing nationwide, according to the CDC. There was no change in levels for RSV, or respiratory syncytial virus, on a week-to-week basis.
"RSV activity is very low in most areas of the country," the CDC said on a webpage broadly dedicated to respiratory viruses in the United States, adding that "seasonal influenza activity is low."
The CDC said that rhinovirus and enterovirus, which are also respiratory viruses, are increasing around the country.
Meanwhile, infections caused by the Mycoplasma pneumoniae bacteria, sometimes called "walking pneumonia," are low in most areas across the United States, and infections caused by the pertussis bacteria, known as "whooping cough," are at lower levels than seen post-pandemic, the CDC said.
The latest figures and estimations published by the CDC come as the Food and Drug Administration approved Moderna, Novavax-Sanofi, and Pfizer-BioNTech's updated COVID-19 vaccines, the companies said on Thursday, after a CDC advisory panel recommended that the shots should target the dominant XFG variant.
Uptake of COVID-19 vaccines has dropped in recent years. Just 17.5 percent of adults and 10 percent of children received a shot in late 2025 and early 2026, according to figures from the CDC.
This month, the Chinese CDC reported more than half a million COVID-19 cases in July, a sharp increase from June's figures. In July, 522,000 cases were reported, up from the 443,000 cases that were reported in the previous month.
Experts who are familiar with local conditions in China told The Epoch Times they suspect there are far more cases of the virus, which is believed to have originated in or around the Chinese city of Wuhan in late 2019 before sparking a worldwide pandemic, than the Chinese regime is reporting publicly.
Tyler Durden Sat, 08/29/2026 - 19:15