The IWPR found that 20.2 million women work in jobs with the highest risk of automation, compared to only 14.4 million men. In addition, out of all women workers, 28.9 per cent work in high-risk occupations, compared to 19 per cent of men.
Artificial intelligence is a constant topic and debate, and there are intense fears about what technology could have in store for future generations and job roles. AI and automation are creeping into our daily existence, but it is not all bad as technology has a record of creating more jobs than it destroys.
Women still face a pay gap, which is gradually closing, and are still underrepresented in leadership in businesses. According to IMF research there is yet more bad news for women: women are at a higher risk of losing their job to automation than men.
It was found that women perform more routine tasks than men, which machines are best at copying. Arguably, women may have been led to believe that soft skills are less important and to make your way in the world of work, hard skills are desirable.
However, what machine’s still cannot copy well are ‘soft skills’ and still require a lot of work to gain any sort of emotional intelligence. Soft skills may become even more important in automated economies, as a key differentiator from machines, and are a skill that both women and men should not overlook.
Lower level administrators, cashiers and clerks are among the most likely to be replaced by a machine, and according to another Oxford study, the list of occupations near the top for this concern are disproportionately female.
Those who are replaced however could benefit from forward-looking training programs that could lead them into higher paying jobs. The World Economic Forum actually found that with retraining, 96 per cent of at risk workers would actually end up benefiting from changes brought upon by automation.
Although it seems a worrying time for women in roles that could be automated, the long term training and repositioning of jobs means that the gender pay gap may get narrower and narrower.
