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NHTSA said it has an “active investigation” of Autopilot. “NHTSA generally does not comment on matters related to open investigations,” NHTSA spokeswoman Veronica Morales said in a statement. In 2021, the agency adopted a rule requiring carmakers such as Tesla to report crashes involving their driver-assistance systems.Beyond the data collection, though, there are few clear legal limitations on how this type of advanced driver-assistance technology should operate and what capabilities it should have.

“Tesla has decided to take these much greater risks with the technology because they have this sense that it’s like, ‘Well, you can figure it out. You can determine for yourself what’s safe’ — without recognizing that other road users don’t have that same choice,” former NHTSA administrator Steven Cliff said in an interview.“If you’re a pedestrian, [if] you’re another vehicle on the road,” he added, “do you know that you’re unwittingly an object of an experiment that’s happening?”

Banner researched Tesla for years before buying a Model 3 in 2018, his wife, Kim, told federal investigators. Around the time of his purchase, Tesla’s website featured a video showing a Tesla navigating the curvy roads and intersections of California while a driver sits in the front seat, hands hovering beneath the wheel.The video, recorded in 2016, is still on the site today.“The person in the driver’s seat is only there for legal reasons,” the video says. “He is not doing anything. The car is driving itself.”

Musk made a similar assertion about a more sophisticated form of Autopilot called Full Self-Driving on an earnings call in July. “Now, I know I’m the boy who cried FSD,” he said. “But man, I think we’ll be better than human by the end of this year.”

While the video concerned Full Self-Driving, which operates on surface streets, the plaintiffs in the Banner case argue Tesla’s “marketing does not always distinguish between these systems.”

Not only is the marketing misleading, plaintiffs in several cases argue, the company gives drivers a long leash when deciding when and how to use the technology. Though Autopilot is supposed to be enabled in limited situations, it sometimes works on roads it’s not designed for. It also allows drivers to go short periods without touching the wheel and to set cruising speeds well above posted speed limits.

Identifying semi-trucks is a particular deficiency that engineers have struggled to solve since Banner’s death, according to a former Autopilot employee who spoke on the condition of anonymity for fear of retribution.

Tesla complicated the matter in 2021 when it eliminated radar sensors from its cars, The Post previously reported, making vehicles such as semi-trucks appear two-dimensional and harder to parse.

“If a system turns on, then at least some users will conclude it must be intended to work there,” Koopman said. “Because they think if it wasn’t intended to work there, it wouldn’t turn on.”Andrew Maynard, a professor of advanced technology transitions at Arizona State University, said customers probably just trust the technology.“Most people just don’t have the time or ability to fully understand the intricacies of it, so at the end they trust the company to protect them,” he said.

“No one believed me that working for Elon was the way it was until they saw how he operated Twitter,” Bernal said, calling Twitter “just the tip of the iceberg on how he operates Tesla.”

In April 2019, at a showcase dubbed “Autonomy Investor Day,” Musk made perhaps his boldest prediction as Tesla’s chief executive. “By the middle of next year, we’ll have over a million Tesla cars on the road with full self-driving hardware,” Musk told a roomful of investors. The software updates automatically over the air, and Full Self-Driving would be so reliable, he said, the driver “could go to sleep.”

Investors were sold. The following year, Tesla’s stock price soared, making it the most valuable automaker and helping Musk become the world’s richest person

To deliver on his promise, Musk assembled a star team of engineers willing to work long hours and problem solve deep into the night. Musk would test the latest software on his own car, then he and other executives would compile “fix-it” requests for their engineers.

Those patchwork fixes gave the illusion of relentless progress but masked the lack of a coherent development strategy, former employees said. While competitors such as Alphabet-owned Waymo adopted strict testing protocols that limited where self-driving software could operate, Tesla eventually pushed Full Self-Driving out to 360,000 owners — who paid up to $15,000 to be eligible for the features — and let them activate it at their own discretion.

Tesla’s philosophy is simple: The more data (in this case driving) the artificial intelligence guiding the car is exposed to, the faster it learns. But that crude model also means there is a lighter safety net. Tesla has chosen to effectively allow the software to learn on its own, developing sensibilities akin to a brain via technology dubbed “neural nets” with fewer rules, the former employees said. While this has the potential to speed the process, it boils down to essentially a trial and error method of training.

Radar originally played a major role in the design of the Tesla vehicles and software, supplementing the cameras by offering a reality check of what was around, particularly if vision might be obscured. Tesla also used ultrasonic sensors, shorter-range devices that detect obstructions within inches of the car. (The company announced last year it was eliminating those as well.)

Musk, as the chief tester, also asked for frequent bug fixes to the software, requiring engineers to go in and adjust code. “Nobody comes up with a good idea while being chased by a tiger,” a former senior executive recalled an engineer on the project telling him

Toward the end of 2020, Autopilot employees turned on their computers to find in-house workplace monitoring software installed, former employees said. It monitored keystrokes and mouse clicks, and kept track of their image labeling. If the mouse did not move for a period of time, a timer started — and employees could be reprimanded, up to being fired, for periods of inactivity, the former employees said.

Some of the people who spoke with The Post said that approach has introduced risks. “I just knew that putting that software out in the streets would not be safe,” said a former Tesla Autopilot engineer who spoke on the condition of anonymity for fear of retaliation. “You can’t predict what the car’s going to do.”

Some of the people who spoke with The Post attributed Tesla’s sudden uptick in “phantom braking” reports — where the cars aggressively slow down from high speeds — to the lack of radar. The Post analyzed data from the National Highway Traffic Safety Administration to show incidences surged last year, prompting a federal regulatory investigation.

The data showed reports of “phantom braking” rose to 107 complaints over three months, compared to only 34 in the preceding 22 months. After The Post highlighted the problem in a news report, NHTSA received about 250 complaints of the issue in a two-week period. The agency opened an investigation after, it said, it received 354 complaints of the problem spanning a period of nine months.

“It’s not the sole reason they’re having [trouble] but it’s big a part of it,” said Missy Cummings, a former senior safety adviser for NHTSA, who has criticized the company’s approach and recused herself on matters related to Tesla. “The radar helped detect objects in the forward field. [For] computer vision which is rife with errors, it serves as a sensor fusion way to check if there is a problem.”

Even with radar, Teslas were less sophisticated than the lidar and radar-equipped cars of competitors.“One of the key advantages of lidar is that it will never fail to see a train or truck, even if it doesn’t know what it is,” said Brad Templeton, a longtime self-driving car developer and consultant who worked on Google’s self-driving car. “It knows there is an object in front and the vehicle can stop without knowing more than that.”

Musk’s resistance to suggestions led to a culture of deference, former employees said. Tesla fired employees who pushed back on his approach. The company was also pushing out so many updates to its software that in late 2021, NHTSA publicly admonished Tesla for issuing fixes without a formal recall notice.

Tesla engineers have been burning out, quitting and looking for opportunities elsewhere. Andrej Karpathy, Tesla’s director of artificial intelligence, took a months-long sabbatical last year before leaving Tesla and taking a position this year at OpenAI, the company behind language-modeling software ChatGPT.

One of the former employees said that he left for Waymo. “They weren’t really wondering if their car’s going to run the stop sign,” the engineer said. “They’re just focusing on making the whole thing achievable in the long term, as opposed to hurrying it up.”

Indexing has gone big, very big. For nine in 10 companies on the S&P 500, their largest single shareholder is one of the Big Three. For many, the big indexers control 20 percent or more of their shares. Index funds now control 20 to 30 percent of the American equities market, if not more.

The problem is that the public markets have been cornered by a group of investment managers small enough to fit at a lunch counter, dedicated to quiescence and inertia.

Passively managed investment options do not just outperform actively managed ones in terms of both better returns and lower fees. They eat their lunch.

Let’s imagine that a decade ago you invested $100 in an index fund charging a 0.04 percent fee and $100 in a traditional mutual fund charging a 1.5 percent fee. Let’s also imagine that the index fund tracked the S&P 500, and that the mutual fund ended up returning what the S&P 500 returned. Your passively invested $100 would have turned into $356.66 in 10 years. Your traditionally invested $100 would have turned into $313.37.

Actively managed investment options could make up for their higher fees with higher returns. And some do, some of the time. Yet scores of industry and academic studies stretching over decades show that trying to beat the market tends to result in lower returns than just buying the market. Only a quarter of actively managed mutual funds exceeded the returns of their passively managed cousins in the decade leading up to 2019,

What might be good for retail investors might not be good for the financial markets, public companies, or the American economy writ large, and the passive revolution’s scope has raised all sorts of hand-wringing and red-flagging. Analysts at Bernstein have called passive investing “worse than Marxism.” The investor Michael Burry, of The Big Short fame, has called it a “bubble,” and a co-head of Goldman Sachs’s investment-management division has warned about froth too. Shortly before his death in 2019, Bogle himself warned that index funds’ dominance might not “serve the national interest.”

One primary concern comes from the analysts at Bernstein: “A supposedly capitalist economy where the only investment is passive is worse than either a centrally planned economy or an economy with active, market-led capital management.”

Active managers direct investment dollars to companies on the basis of those companies’ research-and-development prospects, human capital, regulatory outlook, and so on. They take new information and price it into a company’s stock when buying and selling shares.

Passive investors, by contrast, ignore annual reports and market rumors. They do nothing with trading-floor gossip. They make no attempt to research what to invest in and what to skip. Whether holding international or domestic assets, holding stocks or bonds, or using a mutual-fund structure or an ETF structure, they just mirror the market. Big U.S.-stock index funds buy big U.S. stocks just because they’re big U.S. stocks.

At least in a Soviet-type centrally planned economy, apparatchiks would be making some attempt to allocate resources efficiently.

Passive management is merely a giant phenomenon, not an all-encompassing one. Hundreds of actively managed mutual funds are still out there, as are legions of day traders, hedge funds, and private offices buying and selling and buying and selling. Stock prices still move around, sometimes dramatically, on the basis of new data and new ideas.

Still, passive investing may well be degrading the informational content of the markets, messing up price signals and making business decisions harder as a result.

When one of these commodities ends up on an index, the firms that use that commodity in their business see a 6 percent increase in costs and a 40 percent decrease in operating profits, relative to firms without exposure to the commodity, the academics found

Their theory is that ETF trading shifts prices in subtle ways, making it harder for businesses to know when to buy their gold and copper. Corporate executives “are being influenced by what happens in the futures market, and what happens in the futures market is being influenced by ETF trading,”

More broadly, the Bernstein analysts, among others, worry that index-linked investing is increasing correlation, whereby the prices of stocks, bonds, and other assets move up or down or sideways together.

the price fluctuations of a newly indexed stock “magically and quickly” change. A firm’s shares begin to move “more closely with its 499 new neighbors and less closely with the rest of the market. It is as if it has joined a new school of fish.”

A far bigger concern is that the rise of the indexers might be making American firms less competitive, through “common ownership,” in which the mega-asset managers control large stakes in multiple competitors in the same industry. The passive firms control big chunks of the airlines American, Delta, JetBlue, Southwest, and United, for instance

The rise of common ownership might be perverting corporate behavior in weird ways, academics argue. Think about the incentives like this: Let’s imagine that you are a major shareholder in a public widget company. We’d expect you to desire—insist, even—that the company fight for market share and profits. But now imagine that you are a major shareholder in all the important widget companies. You would no longer really care which one succeeded, particularly not if one company doing better meant another company doing worse. You’d just care about the widget sector’s corporate profits, which would go up if the widget companies quit competing with one another and started raising prices to pad their bottom line.

one major paper showed that common ownership of airline stocks had the effect of raising ticket prices by 3 to 7 percent.

A separate study showed that consumers are paying higher prices for prescription medicines because generic-drug makers have less incentive to compete with the companies making name-brand drugs.

Yet another study showed that common ownership is leading retail banks to charge higher prices.

Across firms, executive compensation seems to be more closely linked to a company’s performance when its shareholders are not invested in the company’s rivals, the study found. In other words, firms stop paying managers for performance when owned by the same people who own their rivals.

The market clout of the indexers raises other questions too. The actual owners of the stocks—not the index-fund managers but the people putting money into index funds—have little say over the companies they own. Vanguard, Fidelity, and State Street, not Mom and Dad, vote in shareholder elections

In fact, the Big Three cast roughly 25 percent of the votes in S&P 500 companies.

In an interview with The Wall Street Journal, the chief executive officer of State Street said he thought it was “almost inevitable, when you see this kind of concentration, that it probably will make sense to do something about it.”

But figuring out what the appropriate restrictions are depends on determining just what the problem with the indexers is—are they distorting price signals, raising the cost of consumer goods, posing financial systemic risk, or do they just have the market cornered? Then, what to do about it? Common ownership is not a problem the government is used to handling.

, thanks to the passive revolution, a broad variety and huge number of firms might have less incentive to compete. The effect on the real economy might look a lot like that of rising corporate concentration. And the two phenomena might be catalyzing one another, as index investing increases the number of mergers and makes them more lucrative.

In recent decades, the whole economy has gone on autopilot. Index-fund investment is hyperconcentrated. So is online retail. So are pharmaceuticals. So is broadband. Name an industry, and it is likely dominated by a handful of giant players. That has led to all sorts of deleterious downstream effects: suppressing workers’ wages, raising consumer prices, stifling innovation, stoking inequality, and suffocating business creation

The problem is not just the indexers. It is the public markets they reflect, where more chaos, more speculation, more risk, more innovation, and more competition are desperately needed.

It’s neither necessary nor possible to abolish calculators and spellcheck programs in classrooms, but periodically removing these tools can help ensure that students use technology in order to free their minds for more interesting tasks—not because they can’t spell or compute without assistance.

On failures of capability, the shutdown began at the worst possible moment for the federal workforce. Beyond the obvious short-term impairment of capabilities caused by furloughing tens of thousands of employees, December and January are crucial months to recruit entry-level employees for the coming year

The president has also undermined institutional memory with the slowest appointments process in recent history

The result is a federal bureaucracy on autopilot with limited alertness in a moment of great vulnerability.

These threats to policy, capability and management reflect a governmentwide failure of imagination. Congress and presidents have plenty of expertise in 20/20 hindsight but have shown little interest over the years in long-range planning.

Congress must own its failure to address the bureaucratic vulnerabilities that trigger failure. Congress has not enacted a significant ethics, personnel or reorganization bill since the 1970s, and it has not conducted a significant examination of the federal bureaucracy’s functioning since the 1990s

By one estimate, each one-point increase in total unemployment during the Great Recession depressed employment and wages for young college grads two to three times as much as in previous recessions.

Boomers presented school as an investment in ourselves, worth financing with debt because it would pay off in higher earnings later. To hear them tell it, education is the only sure investment in history. That’s now proving preposterous

The long-term problem is federal debt. Including debt owed to the Social Security trust fund, it is now around 105% of gross domestic product. Those are claims that millennials (and their descendants) will eventually have to pay, largely to fund social transfers to the boomers that they weren’t willing to pay themselves.

Worse, some 75% of federal spending over the next decade will happen on autopilot, without any intervention from elected lawmakers. Most of that is Social Security, Medicare and Medicaid, along with interest on the debt. Unless Congress finds the political will to enact a substantial overhaul of these programs, millennials will have hardly any latitude to act on their own fiscal priorities.

the tapestry that emerges depicts an enormous heist, in which boomers stole a decade from their millennial children. The boomers’ combination of naiveté, panic and negligence buried millennials in trouble. Digging our way out will be our primary economic and political challenge

Millennials seem to be intuiting that what failed most spectacularly under the boomers was the “third way,” which tried to harness the power of the market to deliver the economic security boomers thought only government could give. It sounded plausible, but the results have been one disaster after another: tech bubbles, resource misallocations that skewed the labor market, the student-loan albatross, an entitlement state that saddles us with debt while failing to deliver economic security for many recipients.

As the Democrats drift leftward, Republicans remain mesmerized by Donald Trump. Mr. Trump is a boomer through and through

2020 could become a depressing slugfest between the ne plus ultra boomer and an opponent peddling century-old socialism, neither of whom offers millennials much of a solution to our urgent problems.

Lately, it has also become one of the most controversial. The algorithm has been found to be promoting conspiracy theories about the Las Vegas mass shooting and incentivising, through recommendations, a thriving subculture that targets children with disturbing content

One YouTube creator who was banned from making advertising revenues from his strange videos – which featured his children receiving flu shots, removing earwax, and crying over dead pets – told a reporter he had only been responding to the demands of Google’s algorithm. “That’s what got us out there and popular,” he said. “We learned to fuel it and do whatever it took to please the algorithm.”

academics have speculated that YouTube’s algorithms may have been instrumental in fuelling disinformation during the 2016 presidential election. “YouTube is the most overlooked story of 2016,” Zeynep Tufekci, a widely respected sociologist and technology critic, tweeted back in October. “Its search and recommender algorithms are misinformation engines.”

Those are not easy questions to answer. Like all big tech companies, YouTube does not allow us to see the algorithms that shape our lives. They are secret formulas, proprietary software, and only select engineers are entrusted to work on the algorithm

Guillaume Chaslot, a 36-year-old French computer programmer with a PhD in artificial intelligence, was one of those engineers.

The experience led him to conclude that the priorities YouTube gives its algorithms are dangerously skewed.

Chaslot said none of his proposed fixes were taken up by his managers. “There are many ways YouTube can change its algorithms to suppress fake news and improve the quality and diversity of videos people see,” he says. “I tried to change YouTube from the inside but it didn’t work.”

Chaslot explains that the algorithm never stays the same. It is constantly changing the weight it gives to different signals: the viewing patterns of a user, for example, or the length of time a video is watched before someone clicks away.

The engineers he worked with were responsible for continuously experimenting with new formulas that would increase advertising revenues by extending the amount of time people watched videos. “Watch time was the priority,” he recalls. “Everything else was considered a distraction.”

Chaslot was fired by Google in 2013, ostensibly over performance issues. He insists he was let go after agitating for change within the company, using his personal time to team up with like-minded engineers to propose changes that could diversify the content people see.

He was especially worried about the distortions that might result from a simplistic focus on showing people videos they found irresistible, creating filter bubbles, for example, that only show people content that reinforces their existing view of the world.

“YouTube is something that looks like reality, but it is distorted to make you spend more time online,” he tells me when we meet in Berkeley, California. “The recommendation algorithm is not optimising for what is truthful, or balanced, or healthy for democracy.”

YouTube told me that its recommendation system had evolved since Chaslot worked at the company and now “goes beyond optimising for watchtime”.

It did not say why Google, which acquired YouTube in 2006, waited over a decade to make those changes

Chaslot believes such changes are mostly cosmetic, and have failed to fundamentally alter some disturbing biases that have evolved in the algorithm

It finds videos through a word search, selecting a “seed” video to begin with, and recording several layers of videos that YouTube recommends in the “up next” column. It does so with no viewing history, ensuring the videos being detected are YouTube’s generic recommendations, rather than videos personalised to a user. And it repeats the process thousands of times, accumulating layers of data about YouTube recommendations to build up a picture of the algorithm’s preferences.

Each study finds something different, but the research suggests YouTube systematically amplifies videos that are divisive, sensational and conspiratorial.

When his program found a seed video by searching the query “who is Michelle Obama?” and then followed the chain of “up next” suggestions, for example, most of the recommended videos said she “is a man”

He believes one of the most shocking examples was detected by his program in the run-up to the 2016 presidential election. As he observed in a short, largely unnoticed blogpost published after Donald Trump was elected, the impact of YouTube’s recommendation algorithm was not neutral during the presidential race: it was pushing videos that were, in the main, helpful to Trump and damaging to Hillary Clinton.

“It was strange,” he explains to me. “Wherever you started, whether it was from a Trump search or a Clinton search, the recommendation algorithm was much more likely to push you in a pro-Trump direction.”

Trump won the electoral college as a result of 80,000 votes spread across three swing states. There were more than 150 million YouTube users in the US. The videos contained in Chaslot’s database of YouTube-recommended election videos were watched, in total, more than 3bn times before the vote in November 2016.

“Algorithms that shape the content we see can have a lot of impact, particularly on people who have not made up their mind,”

“Gentle, implicit, quiet nudging can over time edge us toward choices we might not have otherwise made.”

But what was most compelling was how often Chaslot’s software detected anti-Clinton conspiracy videos appearing “up next” beside other videos.

I spent weeks watching, sorting and categorising the trove of videos with Erin McCormick, an investigative reporter and expert in database analysis. From the start, we were stunned by how many extreme and conspiratorial videos had been recommended, and the fact that almost all of them appeared to be directed against Clinton.

“This research captured the apparent direction of YouTube’s political ecosystem,” he says. “That has not been done before.”

There were too many videos in the database for us to watch them all, so we focused on 1,000 of the top-recommended videos. We sifted through them one by one to determine whether the content was likely to have benefited Trump or Clinton. Just over a third of the videos were either unrelated to the election or contained content that was broadly neutral or even-handed. Of the remaining 643 videos, 551 were videos favouring Trump, while only only 92 favoured the Clinton campaign.

The sample we had looked at suggested Chaslot’s conclusion was correct: YouTube was six times more likely to recommend videos that aided Trump than his adversary.

The spokesperson added: “Our search and recommendation systems reflect what people search for, the number of videos available, and the videos people choose to watch on YouTube. That’s not a bias towards any particular candidate; that is a reflection of viewer interest.”

YouTube seemed to be saying that its algorithm was a neutral mirror of the desires of the people who use it – if we don’t like what it does, we have ourselves to blame. How does YouTube interpret “viewer interest” – and aren’t “the videos people choose to watch” influenced by what the company shows them?

Offered the choice, we may instinctively click on a video of a dead man in a Japanese forest, or a fake news clip claiming Bill Clinton raped a 13-year-old. But are those in-the-moment impulses really a reflect of the content we want to be fed?

YouTube’s recommendation system has probably figured out that edgy and hateful content is engaging. “This is a bit like an autopilot cafeteria in a school that has figured out children have sweet teeth, and also like fatty and salty foods,” she says. “So you make a line offering such food, automatically loading the next plate as soon as the bag of chips or candy in front of the young person has been consumed.”

Once that gets normalised, however, what is fractionally more edgy or bizarre becomes, Tufekci says, novel and interesting. “So the food gets higher and higher in sugar, fat and salt – natural human cravings – while the videos recommended and auto-played by YouTube get more and more bizarre or hateful.”

“This is important research because it seems to be the first systematic look into how YouTube may have been manipulated,” he says, raising the possibility that the algorithm was gamed as part of the same propaganda campaigns that flourished on Twitter and Facebook.

“We believe that the activity we found was limited because of various safeguards that we had in place in advance of the 2016 election, and the fact that Google’s products didn’t lend themselves to the kind of micro-targeting or viral dissemination that these actors seemed to prefer.”

Senator Mark Warner, the ranking Democrat on the intelligence committee, later wrote to the company about the algorithm, which he said seemed “particularly susceptible to foreign influence”. The senator demanded to know what the company was specifically doing to prevent a “malign incursion” of YouTube’s recommendation system. Walker, in his written reply, offered few specifics

Tristan Harris, a former Google insider turned tech whistleblower, likes to describe Facebook as a “living, breathing crime scene for what happened in the 2016 election” that federal investigators have no access to. The same might be said of YouTube. About half the videos Chaslot’s program detected being recommended during the election have now vanished from YouTube – many of them taken down by their creators. Chaslot has always thought this suspicious. These were videos with titles such as “Must Watch!! Hillary Clinton tried to ban this video”, watched millions of times before they disappeared. “Why would someone take down a video that has been viewed millions of times?” he asks

I shared the entire database of 8,000 YouTube-recommended videos with John Kelly, the chief executive of the commercial analytics firm Graphika, which has been tracking political disinformation campaigns. He ran the list against his own database of Twitter accounts active during the election, and concluded many of the videos appeared to have been pushed by networks of Twitter sock puppets and bots controlled by pro-Trump digital consultants with “a presumably unsolicited assist” from Russia.

“I don’t have smoking-gun proof of who logged in to control those accounts,” he says. “But judging from the history of what we’ve seen those accounts doing before, and the characteristics of how they tweet and interconnect, they are assembled and controlled by someone – someone whose job was to elect Trump.”

After the Senate’s correspondence with Google over possible Russian interference with YouTube’s recommendation algorithm was made public last week, YouTube sent me a new statement. It emphasised changes it made in 2017 to discourage the recommendation system from promoting some types of problematic content. “We appreciate the Guardian’s work to shine a spotlight on this challenging issue,” it added. “We know there is more to do here and we’re looking forward to making more announcements in the months ahead.”

In the months leading up to the election, the Next News Network turned into a factory of anti-Clinton news and opinion, producing dozens of videos a day and reaching an audience comparable to that of MSNBC’s YouTube channel. Chaslot’s research indicated Franchi’s success could largely be credited to YouTube’s algorithms, which consistently amplified his videos to be played “up next”. YouTube had sharply dismissed Chaslot’s research.

I contacted Franchi to see who was right. He sent me screen grabs of the private data given to people who upload YouTube videos, including a breakdown of how their audiences found their clips. The largest source of traffic to the Bill Clinton rape video, which was viewed 2.4m times in the month leading up to the election, was YouTube recommendations.

The same was true of all but one of the videos Franchi sent me data for. A typical example was a Next News Network video entitled “WHOA! HILLARY THINKS CAMERA’S OFF… SENDS SHOCK MESSAGE TO TRUMP” in which Franchi, pointing to a tiny movement of Clinton’s lips during a TV debate, claims she says “fuck you” to her presidential rival. The data Franchi shared revealed in the month leading up to the election, 73% of the traffic to the video – amounting to 1.2m of its views – was due to YouTube recommendations. External traffic accounted for only 3% of the views.

many of the other creators of anti-Clinton videos I spoke to were amateur sleuths or part-time conspiracy theorists. Typically, they might receive a few hundred views on their videos, so they were shocked when their anti-Clinton videos started to receive millions of views, as if they were being pushed by an invisible force.

In every case, the largest source of traffic – the invisible force – came from the clips appearing in the “up next” column. William Ramsey, an occult investigator from southern California who made “Irrefutable Proof: Hillary Clinton Has a Seizure Disorder!”, shared screen grabs that showed the recommendation algorithm pushed his video even after YouTube had emailed him to say it violated its guidelines. Ramsey’s data showed the video was watched 2.4m times by US-based users before election day. “For a nobody like me, that’s a lot,” he says. “Enough to sway the election, right?”

Daniel Alexander Cannon, a conspiracy theorist from South Carolina, tells me: “Every video I put out about the Clintons, YouTube would push it through the roof.” His best-performing clip was a video titled “Hillary and Bill Clinton ‘The 10 Photos You Must See’”, essentially a slideshow of appalling (and seemingly doctored) images of the Clintons with voiceover in which Cannon speculates on their health. It has been seen 3.7m times on YouTube, and 2.9m of those views, Cannon said, came from “up next” recommendations.

his research also does something more important: revealing how thoroughly our lives are now mediated by artificial intelligence.

Less than a generation ago, the way voters viewed their politicians was largely shaped by tens of thousands of newspaper editors, journalists and TV executives. Today, the invisible codes behind the big technology platforms have become the new kingmakers.

They pluck from obscurity people like Dave Todeschini, a retired IBM engineer who, “let off steam” during the election by recording himself opining on Clinton’s supposed involvement in paedophilia, child sacrifice and cannibalism. “It was crazy, it was nuts,” he said of the avalanche of traffic to his YouTube channel, which by election day had more than 2m views

For 40 years, Cowen believes, “we have been building toward stasis” with a diminishing “sense of urgency.

Declining labor mobility is partly the result of the domestic protectionism of occupational licensing. “In the 1950s,” Cowen writes, “only about 5 percent of workers required a government-issued license to do their jobs, but by 2008, that figure had risen to about 29 percent.”

There is “more pairing of like with like” (assortative mating, economically homogenous neighborhoods, segregation by educational status), and the nation is losing the capacity and will “to regenerate itself.”

In the 19th century and much of the 20th century, travel speeds increased dramatically; since the 1970s, ground and air congestion has slowed travel.

The Steuerle-Roeper Fiscal Democracy Index measures how much of the allocation of government revenue is determined by current democratic processes and how much by prior decisions establishing permanent programs running on autopilot. The portion of the federal budget automatically spent by choices made years ago is approaching 90 percent

An aging population is devouring an increasing portion of national resources — federal revenue disbursed by the entitlement state to provide Social Security and Medicare to the elderly, the nation’s past. This will worsen. Because government is more important to its elderly beneficiaries than to any other age cohort, the elderly vote at a higher rate than any younger group.

In 2014, Officer Jason Shuck shot a man who ran away from the police when they approached him as he was panhandling outside a Walmart in Springfield, Mo. Officer Shuck later told an investigator his “brain was saying Taser” but his “body moved faster” and he drew his pistol.Local prosecutors allowed the officer to plead guilty to a misdemeanor assault charge. As part of the plea deal, Mr. Shuck, who quit the police department, agreed to never work again in a job that required him to carry a firearm.

Mr. Weisberg said that cases in which officers say they mistook which weapon they were using are rare. He said they are legally different from the majority of police shootings, where officers concede they used deadly force but argue they were justified in doing so.

In 2019, Matthew D. Weintraub, the district attorney in Bucks County, Penn., investigated a case of weapon confusion involving an officer who yelled, “Taser!” before shooting a man in a police holding cell. Mr. Weintraub ultimately ruled out charges after finding that the shooting was “neither justified, nor criminal” and that the officer had an “honest but mistaken” belief that he had used his Taser against the victim, who was injured but survived.

Mr. Orloff said that had prosecutors known Mr. Mehserle was going to make that argument before charging him, “it would have made it more likely that a manslaughter charge was filed as opposed to a murder charge.” Mr. Mehserle was convicted of involuntary manslaughter.Mike Rains, a lawyer in California who represents law enforcement in criminal and civil cases, including Mr. Mehserle, said officers mistake firearms for stun guns because they are on “autopilot,” and the officers should not be held criminally culpable.He said many officers in such cases have been trained to draw the stun gun with the same hand as their firearm. He said they typically have fired only one shot with the firearm, indicating a mistake — if they intended to use the firearm, he said, they would likely have fired multiple shots.

this approach to emotional development neglects the full, complicated range of unhappy feelings that are just as valid a part of human life as happiness is — from sadness to frustration, from anger to fear, from guilt to disappointment, boredom or disgust.

Much research on well-being makes clear that Americans’ typical approaches to the pursuit of happiness is far from helpful to our kids. Anxiety and mental health problems in children and teens have been steadily increasing

In fact, the more we teach our kids to stay positive, at the expense of helping them accept occasional difficult feelings, the less we equip them with tools to manage such feelings when life inevitably gets hard

We tend to have a similar disdain for negative thoughts. Americans like to believe that our thoughts define us: that we need to control that running commentary, shape it and aggressively avoid the “bad” thoughts that supposedly doom us to unhappiness

Research into mindfulness and acceptance and commitment therapy reveals that it’s not negative thoughts that cause depression, anxiety, amotivation or any other mental rut we’re afraid of. It is when negative thoughts become sticky that we are more prone to those problems.

The more we fight with our thoughts, the more we give them the power to stick.

Being fixated on having only the “right” kind of thoughts breeds the cognitive rigidity that creates tunnel vision, locks us into unhelpful patterns, increases our risk of rumination, obsessions and compulsions, and decreases our ability to adapt to setbacks.

Commit to teaching and practicing the pause.

forced happiness, happiness as a sole goal without a deeper sense of meaning or purpose, or the pretense of happiness that stems from the expectation that anything less is toxic, can turn such “happiness” harmful in its own right.

If you can help your child develop meta-cognition — the ability to think about their thoughts and keep from getting stuck within them — and mindfulness, which helps them become a gentle, nonjudgmental observer of their thoughts and feelings, attuned in the moment to their experience, then you are giving them psychological tools to help them for a lifetime.

ADEncourage turning anxious thought patterns into characters.

What better time to begin teaching our kids that unhappiness has a rightful place in a full and — yes — truly happy life? It is often the difficult emotions that have the most to teach us about ourselves, and that give us the opportunity to find meaning and connect with others.

Encourage labeling distressing thoughts like “I’m having the thought no one likes me” rather than “No one likes me,” which helps your child separate from them.

a child with social anxiety may call their negative self-talk “The Stage-Fright Bully” and decide that it has nothing important to say — and that the show can go on.

Take the stance that feelings, even big ones, are always okay.

Emphasize that it’s how we handle emotions that matters most, and we can choose those actions mindfully

Teach your kids that their thoughts don’t define them. Encourage your children to observe their thoughts with curiosity rather than fear, in a nonjudgmental way rather than with shame.

teach them that the anger is okay, but we must think through our actions carefully, noticing our thoughts and bodily sensations without launching into autopilot.

Every time they fully engage with a feeling and choose functional behavior, they strengthen their emotional intelligence and make it more likely that that feeling won’t impel them toward unhealthy habits in the future.

Enlarge your vocabulary about emotions

From “I” statements (“I was sad when you said that to me” rather than “You are being mean!”) to encouraging your kids to write or draw their feelings in a journal, research shows that the mere act of labeling a feeling can help us feel more in control and allow it to pass more quickly.

Observe and adjust your own habits of talking about feelings.

Pay particular attention to the times you invalidate your child’s emotions or try to force a different internal reaction: “You’re okay,”

Instead, choose empathy: “Sounds like that’s really upsetting; let’s think about how we can work through this.”

Talk about true happiness as more than just pleasure or ease.

We all want our kids to be happy. But what they absorb about what that means is crucial. By opening them up to the idea of a sense of purpose, finding meaning in their life, or defining the values important to them, they will have a better understanding of how even challenging, difficult times can cultivate happiness.

And so, for the sake of flag and faith, millions of decent conservative Americans countenanced scandals, wrongs, disloyalty, and crime.

The Trump years demonstrated the very great extent to which presidential cooperation with the law is voluntary, especially if he retains a loyal attorney general, and a sufficient blocking vote in Congress.

It’s illegal for federal employees to overspend on travel to benefit themselves or their colleagues. In 2012, a senior executive at the General Services Administration was sentenced to three months in prison, three months under house arrest, and three years’ parole for taking personal side jaunts and overspending on lavish retreats for his staff.

Yet when Vice President Pence visited Ireland in 2019, he wasted hundreds of thousands of taxpayer dollars by staying not in Dublin, the site of his meetings, but at Trump’s golf course 180 miles away, on the opposite coast of the island.

It is illegal for government employees to use their positions to engage in certain political activities. They are especially forbidden to engage directly in election campaigns while on the government payroll

Trump disregarded the recommendation. Conway mocked the finding to reporters. As one journalist read the recommendation to her, she replied: “Blah, blah, blah. If you’re trying to silence me through the Hatch Act, it’s not going to work. Let me know when the jail sentence starts.”

In other democracies, the equivalents of the AAG for the criminal division are career civil servants

in those other countries, the brute political pressure that Trump applied via Attorney General William Barr on the Department of Justice is much less likely to have an effect.

At one point in 2019, Trump simultaneously refused all cooperation with 20 distinct congressional investigations—testing whether there was much Congress could do about it. There proved to be surprisingly little. Congress’s contempt powers lag far behind those of courts

Even outright lying to Congress can prove exceptionally difficult to punish. “Almost no one is prosecuted for lying to Congress,”

“In fact, only six people have been convicted of perjury or related charges in relation to Congress in the last sixty years.”

Some wonder: Why doesn’t Congress act? But there is no “Congress.” There are only the two parties in Congress. The members of the two parties cannot even agree on methods of evidence or standards of behavior.

Republican Representative Ted Yoho from Florida spoke for troublingly many members of his caucus when he said of a fellow member of Congress that he “works for the president; he answers to the president.”

Congress as an institution cannot function on this kind of partisan mentality. There can be no meaningful oversight of the executive branch if the only standards are “Yay, team!” and “Boo, team!

The system that protects all of us has failed because the protectors of that system have failed to protect it for us.

Democracy does not fly on autopilot. If the people responsible for the institutions of democracy will not do the job, the job will not be done. While the job goes undone, the United States and the world careen toward conflict and crisis.

Then, in March 2022, the Fed changed course, first tightening the money supply by increasing the federal-funds rate and then introducing quantitative tightening. Between July 2022 and August 2023, the M2 supply contracted by 3.9%, the most extreme contraction since 1933.

The first factor contributing to the contraction of the money supply is the Fed’s quantitative tightening

Quantitative tightening has already produced a dramatic selloff in the bond market. But just as they did ahead of the September 2019 crunch in the repurchase-agreement market, Fed officials keep repeating their mistaken mantras that quantitative tightening can operate “in the background” and “on autopilot,” implying minimal market effect

But basic balance-sheet accounting shows that unless commercial banks are creating enough “new money” through their lending activity to offset the Fed’s balance-sheet shrinkage, quantitative tightening has a contractionary effect on the money supply.

The second factor contributing to shrinking M2 is the decreased availability of commercial bank credit—the sum of loans and bank holdings of securities. With the steep rise in rates, bank lending has slowed, and banks have been selling off securities.

This brings us to the stock-market crash of 1987. In that year the key 10-year bond yield rose steeply from January onward (from 7% in January to 10% by Black Monday in October) and the money supply slowed sharply.

In 1987 growth of M2 declined by almost half, from 9.7% year-on-year in January to 4.9% in September, while M3—no longer published by the Fed—slowed from 8.7% to 3.6% over the same period

A bond-market crunch and monetary squeeze together led to a sudden, drastic reassessment of equity-market valuations. The same could happen today, particularly since the current jump in bond yields and monetary squeeze are much more pronounced than in 1987.

So far, only the remaining excess money the Fed created between 2020 and 2021—the cumulative excess savings from the Covid handouts—has been keeping businesses hiring and consumers spending. The effects of the excess money are still giving the economy a lift, but that extra fuel is almost exhausted. When it dries up, the economy will run on fumes.

In all of this, an appreciation for time lags is critical. The Fed ignored the huge acceleration in the quantity of money and thus failed to anticipate the ensuing inflation. When inflation struck in early 2021, Fed officials tried to argue it was “transitory,” caused by supply-chain disruptions.

The Fed continues to ignore the money supply, and we now face the opposite problem. The money supply has been contracting for 18 months, and soon, after the overhanging extra money from 2020-21 has been used up, spending will plunge and inflation will fall, not simply to 2%, but below—and perhaps even into deflation in 2025.

Since Fed officials pay no attention to either monetary aggregates or their credit counterparts, they are overlooking these signals

Monetary analysis tells a very different story than the measures the Fed follows. The first effect of a monetary contraction is higher market interest rates for a brief period. Then comes an economic slump. The economy goes into recession and inflation falls. This results in a second and more permanent effect of subpar money growth, namely lower interest rates and a weaker currency.