inserting a needle for a cancer biopsy or burning into the brain to remove a tumor.

“It is like a car where the lane-following is autonomous but you still control the gas and the brake,” said Greg Fischer, one of the Worcester researchers.

Many obstacles lie ahead, scientists note. Moving plastic pegs is one thing; cutting, moving and suturing flesh is another. “What happens when the camera angle changes?” said Ann Majewicz Fey, an associate professor at the University of Texas, Austin. “What happens when smoke gets in the way?”

For the foreseeable future, automation will be something that works alongside surgeons rather than replaces them. But even that could have profound effects, Dr. Fer said. For instance, doctors could perform surgery across distances far greater than the width of the operating room — from miles or more away, perhaps, helping wounded soldiers on distant battlefields.

The signal lag is too great to make that possible currently. But if a robot could handle at least some of the tasks on its own, long-distance surgery could become viable, Dr. Fer said: “You could send a high-level plan and then the robot could carry it out.”

The same technology would be essential to remote surgery across even longer distances. “When we start operating on people on the moon,” he said, “surgeons will need entirely new tools.”

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Arrival Developing Electric Vehicles Without Assembly Line

“This is about getting the best, optimal delivery vehicle for us,” Mr. Wake said.

Globally, UPS operates a fleet of about 120,000 vehicles, and around 13,000 of them use alternatives to diesel engines such as batteries.

In addition to UPS, BlackRock and the South Korean automakers Hyundai and Kia have invested in Arrival.

Electric vehicle companies have attracted frenzied interest from investors, who hope to find the next Tesla, which is valued at more than $650 billion, more than G.M., Ford Motor, Toyota Motor and Volkswagen combined. Wall Street’s interest has encouraged a parade of fledgling companies — some, including Arrival, that are not yet selling vehicles, let alone making a profit — to list their shares on the stock exchange.

A few have already disappointed investors. The stock of Nikola, which is trying to develop heavy trucks powered by batteries and hydrogen fuel cells, plunged after a small investment firm, Hindenburg Research, said the company had exaggerated its technological abilities. Nikola denied wrongdoing but acknowledged in a February securities filing that some of what it had previously said about its vehicles and technology was inaccurate.

The Securities and Exchange Commission is investigating Nikola and another company, Lordstown Motors, which aims to make electric pickup trucks. Hindenburg also published a report about Lordstown, accusing it of exaggerating interest in its trucks and its production abilities. Lordstown denies Hindenburg’s claims.

Many E.V. start-ups have acquired stock listings by merging with special purpose acquisition companies, or SPACs — businesses set up with a pot of cash and a stock listing. Such mergers allow start-ups to join the stock market without the scrutiny of an initial public offering of stock.

Arrival completed its merger with a SPAC in March. But it remains a long way from turning its vision into a viable business. It has assembled a few prototype vans but has not yet begun testing them on public roads. The company’s shares started trading on March 25 at $22.40 but have since fallen to about $14.

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The Robots Are Coming for Phil in Accounting

The robots are coming. Not to kill you with lasers, or beat you in chess, or even to ferry you around town in a driverless Uber.

These robots are here to merge purchase orders into columns J and K of next quarter’s revenue forecast, and transfer customer data from the invoicing software to the Oracle database. They are unassuming software programs with names like “Auxiliobits — DataTable To Json String,” and they are becoming the star employees at many American companies.

Some of these tools are simple apps, downloaded from online stores and installed by corporate I.T. departments, that do the dull-but-critical tasks that someone named Phil in Accounting used to do: reconciling bank statements, approving expense reports, reviewing tax forms. Others are expensive, custom-built software packages, armed with more sophisticated types of artificial intelligence, that are capable of doing the kinds of cognitive work that once required teams of highly-paid humans.

White-collar workers, armed with college degrees and specialized training, once felt relatively safe from automation. But recent advances in A.I. and machine learning have created algorithms capable of outperforming doctors, lawyers and bankers at certain parts of their jobs. And as bots learn to do higher-value tasks, they are climbing the corporate ladder.

quietly building for years, but accelerating to warp speed since the pandemic — goes by the sleepy moniker “robotic process automation.” And it is transforming workplaces at a pace that few outsiders appreciate. Nearly 8 in 10 corporate executives surveyed by Deloitte last year said they had implemented some form of R.P.A. Another 16 percent said they planned to do so within three years.

Most of this automation is being done by companies you’ve probably never heard of. UiPath, the largest stand-alone automation firm, is valued at $35 billion — roughly the size of eBay — and is slated to go public later this year. Other companies like Automation Anywhere and Blue Prism, which have Fortune 500 companies like Coca-Cola and Walgreens Boots Alliance as clients, are also enjoying breakneck growth, and tech giants like Microsoft have recently introduced their own automation products to get in on the action.

Executives generally spin these bots as being good for everyone, “streamlining operations” while “liberating workers” from mundane and repetitive tasks. But they are also liberating plenty of people from their jobs. Independent experts say that major corporate R.P.A. initiatives have been followed by rounds of layoffs, and that cutting costs, not improving workplace conditions, is usually the driving factor behind the decision to automate.

Craig Le Clair, an analyst with Forrester Research who studies the corporate automation market, said that for executives, much of the appeal of R.P.A. bots is that they are cheap, easy to use and compatible with their existing back-end systems. He said that companies often rely on them to juice short-term profits, rather than embarking on more expensive tech upgrades that might take years to pay for themselves.

“It’s not a moonshot project like a lot of A.I., so companies are doing it like crazy,” Mr. Le Clair said. “With R.P.A., you can build a bot that costs $10,000 a year and take out two to four humans.”

led some companies to turn to automation to deal with growing demand, closed offices, or budget constraints. But for other companies, the pandemic has provided cover for executives to implement ambitious automation plans they dreamed up long ago.

“Automation is more politically acceptable now,” said Raul Vega, the chief executive of Auxis, a firm that helps companies automate their operations.

Before the pandemic, Mr. Vega said, some executives turned down offers to automate their call centers, or shrink their finance departments, because they worried about scaring their remaining workers or provoking a backlash like the one that followed the outsourcing boom of the 1990s, when C.E.O.s became villains for sending jobs to Bangalore and Shenzhen.

But those concerns matter less now, with millions of people already out of work and many businesses struggling to stay afloat.

Now, Mr. Vega said, “they don’t really care, they’re just going to do what’s right for their business,” Mr. Vega said.

Sales of automation software are expected to rise by 20 percent this year, after increasing by 12 percent last year, according to the research firm Gartner. And the consulting firm McKinsey, which predicted before the pandemic that 37 million U.S. workers would be displaced by automation by 2030, recently increased its projection to 45 million.

Recent studies by researchers at Stanford University and the Brookings Institution compared the text of job listings with the wording of A.I.-related patents, looking for phrases like “make prediction” and “generate recommendation” that appeared in both. They found that the groups with the highest exposure to A.I. were better-paid, better-educated workers in technical and supervisory roles, with men, white and Asian-American workers, and midcareer professionals being some of the most endangered. Workers with bachelor’s or graduate degrees were nearly four times as exposed to A.I. risk as those with just a high school degree, the researchers found, and residents of high-tech cities like Seattle and Salt Lake City were more vulnerable than workers in smaller, more rural communities.

“A lot of professional work combines some element of routine information processing with an element of judgment and discretion,” said David Autor, an economist at M.I.T. who studies the labor effects of automation. “That’s where software has always fallen short. But with A.I., that type of work is much more in the kill path.”

Many of those vulnerable workers don’t see this coming, in part because the effects of white-collar automation are often couched in jargon and euphemism. On their websites, R.P.A. firms promote glowing testimonials from their customers, often glossing over the parts that involve actual humans.

“Sprint Automates 50 Business Processes In Just Six Months.” (Possible translation: Sprint replaced 300 people in the billing department.)

found that for most of the 20th century, the optimistic take on automation prevailed — on average, in industries that implemented automation, new tasks were created faster than old ones were destroyed.

rejected calls to fund federal worker retraining programs for years, and while some of the money in the $1.9 trillion Covid-19 relief bill Democrats hope to pass this week will go to laid-off and furloughed workers, none of it is specifically earmarked for job training programs that could help displaced workers get back on their feet.

Another key difference is that in the past, automation arrived gradually, factory machine by factory machine. But today’s white-collar automation is so sudden — and often, so deliberately obscured by management — that few workers have time to prepare.

“Futureproof: 9 Rules for Humans in the Age of Automation,” from which this essay is adapted.

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