While ChatGPT stokes fears of mass layoffs, new jobs are being spawned to review AI
The logo of generative AI chatbot ChatGPT, which is owned by Microsoft-backed company OpenAI.
CFOTO | Future Publishing via Getty Images
Artificial intelligence might be driving concerns over people’s job security — but a new wave of jobs are being created that focus solely on reviewing the inputs and outputs of next-generation AI models.
Since Nov. 2022, global business leaders, workers and academics alike have been gripped by fears that the emergence of generative AI will disrupt vast numbers of professional jobs.
Generative AI, which enables AI algorithms to generate humanlike, realistic text and images in response to textual prompts, is trained on vast quantities of data.
It can produce sophisticated prose and even company presentations close to the quality of academically trained individuals.
That has, understandably, generated fears that jobs may be displaced by AI.
Morgan Stanley estimates that as many as 300 million jobs could be taken over by AI, including office and administrative support jobs, legal work, and architecture and engineering, life, physical and social sciences, and financial and business operations.
But the inputs that AI models receive, and the outputs they create, often need to be guided and reviewed by humans — and this is creating some new paid careers and side hustles.
Getting paid to review AI
Prolific, a company that helps connect AI developers with research participants, has had direct involvement in providing people with compensation for reviewing AI-generated material.
The company pays its candidates sums of money to assess the quality of AI-generated outputs. Prolific recommends developers pay participants at least $12 an hour, while minimum pay is set at $8 an hour.
The human reviewers are guided by Prolific’s customers, which include Meta, Google, the University of Oxford and University College London. They help reviewers through the process, learning about the potentially inaccurate or otherwise harmful material they may come across.
They must provide consent to engage in the research.
One research participant CNBC spoke to said he has used Prolific on a number of occasions to give his verdict on the quality of AI models.
The research participant, who preferred to remain anonymous due to privacy concerns, said that he often had to step in to provide feedback on where the AI model went wrong and needed correcting or amending to ensure it didn’t produce unsavory responses.
He came across a number of instances where certain AI models were producing things that were problematic — on one occasion, the research participant would even be confronted with an AI model trying to convince him to buy drugs.
He was shocked when the AI approached him with this comment — though the purpose of the study was to test the boundaries of this particular AI and provide it with feedback to ensure that it doesn’t cause harm in future.
The new ‘AI workers’
Phelim Bradley, CEO of Prolific, said that there are plenty of new kinds of “AI workers” who are playing a key role in informing the data that goes into AI models like ChatGPT — and what comes out.
As governments assess how to regulate AI, Bradley said that it’s “important that enough focus is given to topics including the fair and ethical treatment of AI workers such as data annotators, the sourcing and transparency of data used to build AI models, as well as the dangers of bias creeping into these systems due to the way in which they are being trained.”
“If we can get the approach right in these areas, it will go a long way to ensuring the best and most ethical foundations for the AI-enabled applications of the future.”
In July, Prolific raised $32 million in funding from investors including Partech and Oxford Science Enterprises.
The likes of Google, Microsoft and Meta have been battling to dominate in generative AI, an emerging field of AI that has involved commercial interest primarily thanks to its frequently floated productivity gains.
However, this has opened a can of worms for regulators and AI ethicists, who are concerned there is a lack of transparency surrounding how these models reach decisions on the content they produce, and that more needs to be done to ensure that AI is serving human interests — not the other way around.
Hume, a company that uses AI to read human emotions from verbal, facial and vocal expressions, uses Prolific to test the quality of its AI models. The company recruits people via Prolific to participate in surveys to tell it whether an AI-generated response was a good response or a bad response.
“Increasingly, the emphasis of researchers in these large companies and labs is shifting towards alignment with human preferences and safety,” Alan Cowen, Hume’s co-founder and CEO, told CNBC.
“There’s more of an emphasize on being able to monitor things in these applications. I think we’re just seeing the very beginning of this technology being released,” he added.
“It makes sense to expect that some of the things that have long been pursued in AI — having personalised tutors and digital assistants; models that can read legal documents and revise them these, are actually coming to fruition.”
Another role placing humans at the core of AI development is prompt engineers. These are workers who figure out what text-based prompts work best to insert into the generative AI model to achieve the most optimal responses.
According to LinkedIn data released last week, there’s been a rush specifically toward jobs mentioning AI.
Job postings on LinkedIn that mention either AI or generative AI more than doubled globally between July 2021 and July 2023, according to the jobs and networking platform.
Reinforcement learning
Meanwhile, companies are also using AI to automate reviews of regulatory documentation and legal paperwork — but with human oversight.
Firms often have to scan through huge amounts of paperwork to vet potential partners and assess whether or not they can expand into certain territories.
Going through all of this paperwork can be a tedious process which workers don’t necessarily want to take on — so the ability to pass it on to an AI model becomes attractive. But, according to researchers, it still requires a human touch.
Mesh AI, a digital transformation-focused consulting firm, says that human feedback can help AI models learn mistakes they make through trial and error.
“With this approach organizations can automate analysis and tracking of their regulatory commitments,” Michael Chalmers, CEO at Mesh AI, told CNBC via email.
Small and medium-sized enterprises “can shift their focus from mundane document analysis to approving the outputs generated from said AI models and further improving them by applying reinforcement learning from human feedback.”
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Jared Isaacman, U.S. President Donald Trump’s nominee to be administrator of the National Aeronautics and Space Administration (NASA) testifies during a Senate Commerce, Science, and Transportation confirmation hearing on Capitol Hill in Washington, D.C., U.S., April 9, 2025.
Ken Cedeno | Reuters
President Donald Trump has renominated Jared Isaacman to run NASA after pulling his prior nomination months ago due to what the president called a “thorough review of prior associations.”
“Jared’s passion for Space, astronaut experience, and dedication to pushing the boundaries of exploration, unlocking the mysteries of the universe, and advancing the new Space economy, make him ideally suited to lead NASA into a bold new Era,” Trump wrote in a post on Truth Social on Tuesday.
Isaacman, who is friends with Tesla CEO Elon Musk, was originally picked to lead NASA in December, before Trump had even taken office. Isaacman is a billionaire who founded payments company Shift4 and has led two private spaceflights.
But Trump pulled the nomination in late May after a spat between the president and Musk, who had been leading a White House effort to slash the size of the federal government. Trump said at the time that he was withdrawing the pick because of Isaacman’s past associations, though he didn’t specify what those were. Some reports have suggested that it was a reference to Isaacman’s prior donations to Democrats.
Days after the withdrawal, Isaacman told Shift4 investors in a letter that his “brief stint in politics was a thrilling experience.” He also said that he was resigning as CEO of Shift4, which he founded in 1999 at age 16, and would assume the role of executive chairman. He had been planning to leave the company if his nomination was confirmed by the Senate. But it never got that far.
Transportation Secretary Sean Duffy has been running NASA as interim head since July.
Isaacman still must go through the Senate confirmation process. The federal government has been shut down since the beginning of October, but the Senate is still able to confirm presidential nominees.
Charles Liang, CEO of Super Micro Computer Inc., during the Computex conference in Taipei, Taiwan, on June 5, 2024.
Annabelle Chih | Bloomberg | Getty Images
Super Micro Computer shares plunged as much as 10% in extended trading on Tuesday after the server maker issued weaker-than-expected results for the fiscal first quarter.
Here’s how the company did in comparison with analyst estimates compiled by LSEG:
- Earnings per share: 35 cents adjusted vs. 40 cents expected
- Revenue: $5.02 billion vs. $6 billion expected
Revenue fell 15% from $5.94 billion a year ago, Super Micro said in a statement. The report comes about two weeks after Super Micro issued preliminary earnings and said it expected revenue of $5 billion for the quarter, down from prior guidance of $6 billion to $7 billion.
Net income fell by more than half to $168.3 million, or 26 cents a share, from $424.3 million, or 67 cents a share, a year earlier.
In its partial report last month, Super Micro said “design win upgrades” pushed some expected first-quarter revenue to the second quarter. The company said it now expects sales of $10 billion to $11 billion in the current quarter, above the $7.83 billion average estimate, according to LSEG.
Super Micro has been a big beneficiary of the artificial intelligence boom, as its servers come packed with graphics processing units from Nvidia. But after growth soared from late 2023 through last year, the business has flatlined, with some analysts saying that Dell has taken market share.
Prior to Tuesday’s report, the stock was up 55% for the year.
AMD CEO Lisa Su speaks at a Senate Commerce, Science, and Transportation Committee hearing in Washington on May 8, 2025. The leaders of some of the biggest technology and artificial intelligence companies will go to Congress on Thursday with a wish list of sorts that at its top has doing away with regulation they say inhibits their firms’ growth and by default, sends business to China.
Nathan Howard | Bloomberg | Getty Images
Advanced Micro Devices reported fiscal third-quarter results that exceeded Wall Street expectations, but gave margin guidance was inline with estimates. The stock slipped in extended trading.
Here’s how the company did in comparison with LSEG consensus:
- Earnings per share: $1.20 adjusted vs. $1.16 expected
- Revenue: $9.25 billion vs. $8.74 billion expected
Revenue increased 36% from a year earlier in the fiscal third quarter, which ended on Sept. 27, according to a statement.
Net income climbed to $1.24 billion, or 75 cents per share, from $771 million, or 47 cents per share, a year earlier.
For the fourth quarter, AMD expects about $9.6 billion in revenue, implying 25% growth. That’s above LSEG’s $9.15 billion consensus. AMD sees an adjusted gross margin of 54.5% for the quarter, meeting StreetAccount’s consensus of 54.5%.
AMD, which is trying to keep pace with Nvidia in the market for artificial intelligence processors, said the guidance does not include revenue from shipments of its Instinct MI308 chips to China. Executives said the same thing last quarter.
As of Tuesday’s close, AMD shares were up 107% so far this year, while the Nasdaq is up 21%.
AMD reached a deal with OpenAI last month that could see the AI startup company take a 10% stake in the chipmaker. OpenAI will deploy 6 gigawatts of AMD’s Instinct graphics processing units over multiple years and across multiple generations of hardware, the companies said, beginning with an initial 1-gigawatt rollout of chips in the second half of next year.
For years OpenAI and other companies relied on graphics chips from Nvidia for running large-scale AI models.
Also in October, Oracle announced plans to deploy 50,000 AMD Instinct MI450 AI chips in its cloud starting next year.
AMD’s data center business, which includes standard central processing units and GPUs for AI, generated $4.34 billion in fiscal third-quarter revenue, up 22%. Analysts polled by StreetAccount were looking for $4.13 billion.
Client revenue reached $2.75 billion, which was up 46% and more than StreetAccount’s $2.61 billion consensus. Revenue from gaming totaled $1.30 billion, up 181%. StreetAccount’s consensus was $1.05 billion.
Amazon, a key cloud customer for AMD, disclosed in a Tuesday filing that it had sold all 822,234 of its AMD shares as of Sept. 30. Amazon built the position sometime in the first quarter.
Executives will discuss the results with analysts on a conference call starting at 5 p.m. ET.
This is developing news. Please check back for updates.
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