Machine learning might exacerbate workforce inequities: Study

New research has found that women and those in low-income professions are more likely to be employed in jobs that have a high degree of exposure to machine learning – and, therefore, risk being automated. 

Research conducted by the Institute for Work & Health, the Future Skills Centre, and The Dais divided jobs into two categories based on high and low exposure to machine learning. They found that about 12 per cent of the total workforce were completing tasks that may be suitable for machine learning. 

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