Contrary to popular anxieties, a recent MIT study reveals that large-scale job displacement by AI is currently unrealistic due to prohibitive implementation costs. Only a small fraction of tasks involving computer vision, for example, can be automated in a cost-effective manner.
In an in-depth study examining the potential for AI to replace human workers, researchers delved into the cost-efficiency of automating tasks involving computer vision across various US occupations. To their surprise, they discovered that AI could only realistically substitute for 23% of work hours, measured by the value they generate. The high cost of implementing and maintaining AI-powered visual recognition systems often rendered human employees a more economical choice, even in fields like education and property valuation.
Fueled by the capabilities showcased by OpenAI’s ChatGPT and other generative tools, AI adoption in 2023 was nothing short of explosive. Tech titans from Microsoft and Alphabet to Baidu and Alibaba raced to unveil new AI offerings and intensify development initiatives, a pace some industry leaders deemed dangerously rapid. However, long-standing anxieties about AI’s potential job displacement continue to linger.
Funded by the MIT-IBM Watson AI Lab, a recent study delved into the automation potential of visually-assisted tasks across 800 occupations. The study, based on data from online surveys of 1,000 tasks, found that only 3% can be economically automated currently. However, the researchers predict a significant increase to 40% by 2030, contingent on lower data costs and improvements in AI accuracy.
The emergence of highly capable language models like ChatGPT and Google’s Bard has reopened the critical discussion on AI’s role in the workplace. These technological advancements blur the lines between human and machine capabilities, prompting anxieties about AI displacing workers. The International Monetary Fund’s recent report highlighting the potential impact on 40% of global jobs reinforces the need for careful policy considerations to mitigate potential negative consequences while maximizing AI’s benefits.
