Artificial Intelligence and Women’s Empowerment

Women and Labour 

The state of women in labour is fraught with challenges. Although women have always participated in domestic labour, jobs outside the household were largely inaccessible to women until recently. Consequently, women remain financially dependent on men and face impedance of self actualisation. To combat this, women’s groups across the globe have steadily struggled for the rights of women to work outside the home and in previously male-dominated industries. However, women continue to suffer discrimination during hiring and promotion, pay inequality and an increased risk of harassment in the workplace. 

According to the ILO, it is more difficult for women to find paid employment and when they do, they tend to work lower quality jobs in vulnerable conditions. In 2021, the World Economic Forum predicted that it would take the world 135.6 years to close the gender gap. Current statistics show that:

i. The current global labour force participation is just under 47% for women as opposed to 72% for men. In regions such as North Africa and the Middle East where women face even more obstacles, the gap may be as wide as 50%, with unemployment rates for women exceeding 20%. 

ii. Globally, women are paid about 77% of what men receive for equal work. The gender pay gap is further worsened by the segregation of women to less lucrative industries and lower paying roles. 

iii. Extra time spent on domestic labour, which may be up to three times higher than for men, reduces the available time for paid work by women. 

iv. Although most countries claim to provide maternity coverage, 60% of women have no statutory right to maternity leave and 66% are not entitled to pay during maternity leave. In addition, women are more likely to be set back when they start families due to lack of affordable childcare options. Thus, women are forced to work fewer hours than men, leading to rates of ‘time related unemployment’ of up to 46% in developing countries 

v. Women’s entitlements are less protected and the number of women above retirement age who receive a pension is 11% less than that of men.

vi. About 16% of women, compared to only 6% of men, are self employed in businesses owned by the family leading to little or no pay and reduced access to workers’ protection rights.

vii. Sexual harassment in the workplace is widespread with between 25%-80% of women reporting verbal and physical harassment in the workplace. Such events may force women out of work and result in reduced levels of interest and productivity. 

Several factors contribute to the various obstacles faced by women in labour. Because of gender roles and stereotypes, women receive reduced opportunities for education and training to prepare them to join the workforce. Coupled with the outlined problems of employment faced when women eventually enter the workforce, this results in reduced participation and representation of women in labour. Thus, women become more vulnerable to poverty, are unable to make financial decisions for themselves and find it difficult to attain self-fulfillment.

AI and Women’s Empowerment

Some concern has been shown that automation of skilled labour available to women may increase unemployment. The IMF has reported that about 11% of jobs held by women are at risk of automation. Currently, about 22% of AI professionals are women and only 12% of lead researchers in machine learning are women. This increases the susceptibility of AI systems to biases held by developers and further promotes discrimination of women. 

Nevertheless, AI systems may be equally useful to the improvement of working conditions for women if efforts are made to program equality, rather than bias into the society. The search for solutions to the problems of protecting women’s rights at work have led to the creation of programs aimed at achieving gender parity in the workplace:

i. AI-powered tools can be employed during the hiring process to recruit female workers and point out geographical areas of untapped talent to employers.

ii. Women’s perception and underestimation of their own abilities sometimes affect job application rates. If AI algorithms are used to create job descriptions, more inclusive language can be used to encourage more women to apply for jobs. 

iii. Because AI is efficient at identifying patterns, it can be used to highlight links between harmful policies and reduced participation of women in the workforce.

iv. AI based systems for evaluating workers can also prevent bias during appraisals and ensure there are no obstacles to granting women pay raises and promotions.

v. Application of AI in the home may reduce the burden of domestic labour on women, leaving more time to engage in paid work. 

vi. AI systems can encourage the rise of remote work leading to more flexible work hours for working mothers. Indeed, automation may change the current conditions of work and provide more free hours for all workers. More time off work for everyone could make more men available to share the burden of domestic labour.

vii. Anonymised systems are being created to collect reports of sexual harassment in the workplace. Firms have also developed bots that can recognize and flag inappropriate comments on company networks.

If the potential gains of AI in this regard are to be realised, it must be remembered that AI systems remain susceptible to bias if developers are prejudicial to women. 

For AI to become a truly effective solution, we must avoid recreating the existing challenges in the workplace by prioritising the inclusion of women in AI development and emphasising responsible and ethical use of AI. Gender gaps in digital inclusion must be addressed in order to ensure that women are provided equal access to technological tools and can benefit from these advancements. If properly applied, AI can transform the reality of women in labour and contribute to fairer working conditions, leading to great strides in personal and societal development. 


Resources 

https://www.ilo.org/infostories/en-GB/Stories/Employment/barriers-women#bridging-gap

https://www.unwomen.org/en/news/in-focus/csw61/equal-pay

https://www.thecontinentalapproach.com/january/can-ai-bridge-the-gender-gap-in-the-workplace

https://financialpost.com/fp-work/can-artificial-intelligence-help-close-gender-gaps-at-work

https://seepnetwork.org/Blog-Post/Using-Artificial-Intelligence-and-Technology-for-Women-s-Economic-Empowerment-Can-It-Work

https://www.bcg.com/publications/2019/artificial-intelligence-ai-help-hinder-women-workforce

https://publications.iadb.org/en/publications/english/document/The-Effects-of-AI-on-the-Working-Lives-of-Women.pdf



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