The gender pay gap, a longstanding topic of contention, has gone on so long that human hands may not be able to solve the issue. Since the post-Civil War days of the Reconstruction Era, various complications have contributed to the disparity in pay between men and women. Resolutions to the identified problems have been kicked back and forth between C-suites, but there has not been a clear-cut fix to correct the imbalance.
The pay gap has narrowed since 1980, but it hasn’t decreased in the past 15 years.
In 2018, women earned 85 percent of their male counterparts’ salaries, according to a Pew Research Center analysis of median hourly earnings of full and part-time workers in the United States. Based on this estimate, it would’ve taken an extra 39 days of work to match the earnings of men in 2018.
Authors at the Harvard Business Review analyzed this problem in a recent article. They wrote that closing the gap, without considerations of fairness and equity, can lead to more problems than it solves, potentially creating new legal liabilities and corrupting incentives. In the end, women will not be more well off than they were beforehand.
A report from the World Economic Forum revealed that at the current rate, it may take another 202 years to close the economic gender gap globally. That is where a helping hand, whether artificial or human, will help most.
The Technology is Here
Gapsquare, a software service that aims to close the gender pay gaps in companies, is using the power of artificial intelligence and machine learning technology to aid the change. Zara Nanu, CEO of Gapsquare, has said, “We need to help companies understand how the discrepancies can be covered in a more sustainable way that doesn’t disadvantage either gender. It’s not about stealing a slice of the pie; it’s about building the pie together equally.” Gapsquare’s technology will allow companies to run their payroll and HR data through one system.
Using AI and machine learning technology, they’re able to merge and analyze the data together, providing expertise in three key areas:
• Identifying any existing pay discrepancies based on gender but also ethnicity, disability, or any other employee characteristics
• Providing insights into why these gaps exist based on a combination of data and academic expertise from the backend. This will give more opportunities to make precise data-driven decisions to narrow these gaps
• Opportunities to take more data-driven decisions to narrow these gaps
With software like Gapsquare and others on the horizon, companies can zero in on salary-based inequalities on a company’s organizational chart to make data-driven decisions and create real, sustainable change. The gender pay gap is a looming issue for executives as they manage businesses from the top down. As time progresses, it would be much more beneficial to be a part of the solution as opposed to the problem.