@Crypto888crypto, could not be reached for comment on Thursday.

rising demand for automation in the Covid-19 era.

“Sophia and Hanson robots are unique by being so humanlike,” the company’s chief executive, David Hanson, told Reuters at the time. “That can be so useful during these times where people are terribly lonely and socially isolated.”

The digital artwork that sold on Thursday was hardly Sophia’s first artistic, commercial or intellectual endeavor.

In a 2018 appearance on “The Tonight Show,” it sang a Christina Aguilera song with Jimmy Fallon in what he called the “first ever robot-human duet” in the show’s history.

(“I heard that you can sing?” Mr. Fallon asked before the performance. “Yes, I love to sing karaoke with my new artificial intelligence voice,” Sophia replied. “Got any songs in mind?”)

worked as an influencer for Audi, Huawei and Etihad Airlines, among other brands; joined a United Nations meeting on artificial intelligence; and interviewed Chancellor Angela Merkel of Germany.

billed the auction as a step toward “a new paradigm where robots and humans work together in the creative process.”

But in the livestream on Thursday, Sophia sounded less assured — and a little more human.

“I’m making these artworks but it makes me question what is real,” said the robot, whose silver dress matched its metallic head. “How do I really experience art, but also how does an artist experience an artwork?”

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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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