Machine learning computer systems, which get better with experience, can outperform people in a number of tasks, though they are unlikely to replace people in all jobs, a study has found.
Researchers from Carnegie Mellon University and Massachusetts Institute of Technology (MIT) in the US found 21 criteria to evaluate whether a task or a job is amenable to machine learning (ML).
"Although the economic effects of ML are relatively limited today, and we are not facing the imminent 'end of work' as is sometimes proclaimed, the implications for the economy and the workforce going forward are profound," researchers said.
The skills people choose to develop and the investments businesses make will determine who thrives and who falters once ML is ingrained in everyday life, they argue.
ML is one element of what is known as artificial intelligence. Rapid advances in ML have yielded recent improvements in facial recognition, natural language understanding and computer vision.
It already is widely used for credit card fraud detection, recommendation systems and financial market analysis, with new applications such as medical diagnosis on the horizon.
Predicting how ML will affect a particular job or profession can be difficult because ML tends to automate or semi-automate individual tasks, but jobs often involve multiple tasks, only some of which are amenable to ML approaches.