Proliferation of cutting-edge technologies
According to a study conducted by the Oxford Internet Institute and the Center for Social Data Science at the University of Copenhagen, workers with expertise in artificial intelligence are “particularly valuable,” and command salaries 21% higher than average, but potentially up to 40% higher.
The worldwide group discovered that the value of workers’ AI abilities was boosted in large part due to the extremely ‘complementary’ character of AI talents (they may be coupled with a broad range of other, frequently valued, skills). The economic worth of talent is defined by its complementarity, or how effectively it may be integrated with other worker competencies, according to a study of 962 skills and 25,000 people.
It was discovered that the proliferation of cutting-edge technologies, especially AI, significantly affects the monetary worth of expertise. The most beneficial were those relating to computer programming and data science.
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AI talents
The following five AI talents were deemed to be the most economically valuable to workers (as measured by the percentage increase in hourly wages):
- Learning Machines (up by 40%)
- Tensor Flow soared by 38%
- Plus-27% in Accuracy using Deep Learning
- Processing of Natural Language (up 19%)
- Science of Data Added 17%
The results indicate that a skill’s worth increases in proportion to the number of other skills it may be coupled with. Data analytics and other similar abilities are significant because of the value they add when paired with other talents. In contrast, the value of abilities like picture retouching was determined to be lower since they can only be paired with a limited range of other skills.
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What is the Price of a Skill?
The research, titled “What is the Price of a Skill?,” appeared in the journal Research Policy. Data from approximately 50,000 freelance jobs placed on online labor marketplaces in the US between 2014 and 2022 was utilized in the study, titled “The Value of Complementarity.” They created a network depicting the monetary and relational worth of the talents by mapping them against finished projects.
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