Leveraging technology to minimise the gender pay gap

By John Cleary

Leveraging technology to minimise the gender pay gap

Technology has undoubtedly been the driving force behind many major changes to society in the last century. By harnessing the power of data, it can also tackle some of the many challenges surrounding inequality in today’s world. Including the gender pay gap.

Despite huge progress, the gender pay gap, amongst other barriers for women, still stifle any progress in the workplace. The developing world faces even greater problems, including a lack of access to education, work, and technology. Activists and employers alike are searching for solutions by leveraging analytics to increase visibility, reduce bias, and change behaviour in workplace processes for women around the world.

Barriers and biases in the tech sector

Tech-related jobs are still male-dominated all over the world. In some countries, women have been shown to be eight times less likely than men to work in information and communication technology (ICT) roles.

Technology has to address these barriers and biases when it comes to recruitment and the gender pay gap. There is research into the development of tech-enabled sponsorship that bridges the diversity and inclusion gaps.

The premise of a sponsor is to actively support a woman’s career by advocating her to senior leaders. There is already a mountain of data available for employers to implement this. However, tech-enabled sponsorship can harness meaningful data points, such as networking analytics, to accelerate women’s career development and contribute to closing the gender pay gap.

In the workplace, it can reduce the barriers and biases in place by matching the expertise of sponsors with the skill gaps of women in middle management using self-created profiles. Technology can schedule network meetings, map milestones, prompt for ratings, and integrate active sponsorship into everyday work practices.

Does artificial intelligence have a part to play in diversity?

HR departments have been trying to utilise artificial intelligence to help breakdown the biases involved in the hiring process.

What large companies, such as Amazon, actually discovered was that this entirely depends on the historical data that fuels this technology. If implemented incorrectly, it is capable of reproducing the exact same biases it is trying to resolve. This is because an algorithm has a tendency to teach itself to prefer men’s resumes over women’s.

Only the future will tell if these programs become more effective at reducing bias in the hiring process. To be truly successful, we need to think more about technology’s ability to leverage data before we integrate it to minimise the gender pay gap.

What we require today is a combination of technology and human input. We are in a position to recognise the gender biases that surround us. And if we can do that then we can action a solution to solve the problem. It isn’t an issue that will disappear overnight, but it is our duty to do what we can to lay the groundwork for future development.

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