Ai can predict salaries primarily based at the text of online job postings
The process landscape in the USA is dramatically shifting: the Covid-19 pandemic has redefined important work and moved people out of the workplace. New technologies are remodelling the character of many occupations. Globalisation keeps to push jobs to new places. And climate change worries are adding jobs in the alternative power area while slicing them from the fossil gasoline industry.
Amid this place of work turmoil, workers, in addition to employers and policymakers, ought to gain from know-how which activity characteristics cause better wages and mobility, says Sarah Bana, a postdoctoral fellow at Stanford’s digital financial system lab, part of the Stanford institute for human-targeted Artificial Intelligence. And, she notes, there now exists a massive dataset that might assist offer that expertise: the textual content of millions of on line task postings.
“online data provides us with a terrific opportunity to measure what subjects,” she says.
Indeed, using Artificial Intelligence (AI) and machine mastering, Bana recently showed that the phrases utilised in a dataset of greater than 1,000,000 online job postings give an explanation for 87% of the version in salaries throughout a massive proportion of the exertions market. It’s the first paintings to apply such a massive dataset of postings and to look at the connection among postings and salaries.
Bana also experimented with injecting new text – including an ability certificate, as an example – into applicable process listings to look how these phrases changed the salary prediction.
