Sitting in a conference room at Mercor’s office in San Francisco’s South of Market district, CEO Brendan Foody recalls the day in June that changed everything. Meta had announced it was buying almost half of data labeling giant Scale AI for $14 billion and poaching its star CEO Alexandr Wang. Mercor, a smaller rival that recruits PhDs and other experts to train models for AI labs, saw an immediate opening. “I was initially surprised,” Foody tells Forbes. “Then it slowly transitioned from surprise to excitement and enthusiasm around the future.”………..Continue reading…..
Source: AI’s Next Job? Recruiting People To Train More AI
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Critics:
Increased automation often causes workers to feel anxious about losing their jobs as technology renders their skills or experience unnecessary. Early in the Industrial Revolution, when inventions like the steam engine were making some job categories expendable, workers forcefully resisted these changes. Luddites, for instance, were English textile workers who protested the introduction of weaving machines by destroying them.
More recently, some residents of Chandler, Arizona, have slashed tires and pelted rocks at self-driving car, in protest over the cars’ perceived threat to human safety and job prospects. The relative anxiety about automation reflected in opinion polls seems to correlate closely with the strength of organized labor in that region or nation.
For example, while a study by the Pew Research Center indicated that 72% of Americans are worried about increasing automation in the workplace, 80% of Swedes see automation and artificial intelligence (AI) as a good thing, due to the country’s still-powerful unions and a more robust national safety net. According to one estimate, 47% of all current jobs in the US have the potential to be fully automated by 2033.
Furthermore, wages and educational attainment appear to be strongly negatively correlated with an occupation’s risk of being automated. Erik Brynjolfsson and Andrew McAfee argue that “there’s never been a better time to be a worker with special skills or the right education, because these people can use technology to create and capture value. However, there’s never been a worse time to be a worker with only ‘ordinary’ skills and abilities to offer, because computers, robots, and other digital technologies are acquiring these skills and abilities at an extraordinary rate.”
Others however argue that highly skilled professional jobs like a lawyer, doctor, engineer, journalist are also at risk of automation. According to a 2020 study in the Journal of Political Economy, automation has robust negative effects on employment and wages: “One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%.”
A 2025 study in the American Economic Journal found that the introduction of industrial robots reduced 1993 and 2014 led to reduced employment of men and women by 3.7 and 1.6 percentage points. Research by Carl Benedikt Frey and Michael Osborne of the Oxford Martin School argued that employees engaged in “tasks following well-defined procedures that can easily be performed by sophisticated algorithms” are at risk of displacement, and 47% of jobs in the US were at risk.
The study, released as a working paper in 2013 and published in 2017, predicted that automation would put low-paid physical occupations most at risk, by surveying a group of colleagues on their opinions. However, according to a study published in McKinsey Quarterly in 2015 the impact of computerization in most cases is not the replacement of employees but the automation of portions of the tasks they perform. The methodology of the McKinsey study has been heavily criticized for being intransparent and relying on subjective assessments.
The methodology of Frey and Osborne has been subjected to criticism, as lacking evidence, historical awareness, or credible methodology. Additionally, the Organisation for Economic Co-operation and Development (OECD) found that across the 21 OECD countries, 9% of jobs are automatable. Based on a formula by Gilles Saint-Paul, an economist at Toulouse 1 University, the demand for unskilled human capital declines at a slower rate than the demand for skilled human capital increases.
In the long run and for society as a whole it has led to cheaper products, lower average work hours, and new industries forming (i.e., robotics industries, computer industries, design industries). These new industries provide many high salary skill-based jobs to the economy. By 2030, between 3 and 14 percent of the global workforce will be forced to switch job categories due to automation eliminating jobs in an entire sector.
While the number of jobs lost to automation is often offset by jobs gained from technological advances, the same type of job loss is not the same one replaced and that leading to increasing unemployment in the lower-middle class. This occurs largely in the US and developed countries where technological advances contribute to higher demand for highly skilled labor but demand for middle-wage labor continues to fall.
Economists call this trend “income polarization” where unskilled labor wages are driven down and skilled labor is driven up and it is predicted to continue in developed economies. Lights-out manufacturing is a production system with no human workers, to eliminate labor costs. It grew in popularity in the U.S. when General Motors in 1982 implemented humans “hands-off” manufacturing to “replace risk-averse bureaucracy with automation and robots”. However, the factory never reached full “lights out” status.
The expansion of lights out manufacturing requires:
- Long-term mechanic capabilities
- Planned preventive maintenance
- Commitment from the staff
Engineers can now have numerical control over automated devices. The result has been a rapidly expanding range of applications and human activities. Computer-aided technologies (or CAx) now serve as the basis for mathematical and organizational tools used to create complex systems. Notable examples of CAx include computer-aided design (CAD software) and computer-aided manufacturing (CAM software). The improved design, analysis, and manufacture of products enabled by CAx has been beneficial for industry.
Information technology, together with industrial machinery and processes, can assist in the design, implementation, and monitoring of control systems. One example of an industrial control system is a programmable logic controller (PLC). PLCs are specialized hardened computers which are frequently used to synchronize the flow of inputs from (physical) sensors and events with the flow of outputs to actuators and events.
Human-machine interfaces (HMI) or computer human interfaces (CHI), formerly known as man-machine interfaces, are usually employed to communicate with PLCs and other computers. Service personnel who monitor and control through HMIs can be called by different names. In the industrial process and manufacturing environments, they are called operators or something similar. In boiler houses and central utility departments, they are called stationary engineers.
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