In The Age Of Artificial Intelligence, Why Are Businesses Prioritising Female Decision-Makers?

37% of businesses say that employing women in AI leadership roles is a top priority, according to IBM.

IBM’s study, titled ‘Female Leadership in the Age of AI: United Kingdom’, found that as the meteoric rise of AI continues, the tech teams creating AI systems and platforms are becoming increasingly in need of women in both leadership and technical positions.

According to Forbes, by 2030 AI will be in every aspect of our lives, both personal and professional. This means that the teams developing AI and the leaders directing deployments need to reflect the population at large to remove chances of bias within these systems, and for the benefits of AI to be fully felt throughout society.

Women in business statistics

We should first give more context as to why more needs to be done to employ women in the tech industry and senior leadership positions, before exploring why gender diverse teams are important to AI in particular.

In tech roles

In general, the number of women in tech roles is on the rise, but sadly, the ratio of women to men is still considerably low. 26% of IT professionals are women, and only make up 22% of professionals working in AI.

Barriers that women in tech face include discrimination, lack of inclusive and family friendly policies, return to the office mandates, reduced career opportunities, and more. These issues within the industry at large mean that there are significant challenges with attracting and retaining female tech professionals, including in AI.

In leadership

Only 32% of senior leadership positions are filled by women. This number is rising but slowly. The CIO found that in the tech industry, for every 100 men who are promoted, only 87 women get the same treatment.

There are a number of reasons why women hit a glass ceiling when trying to reach leadership positions within tech companies. A recent survey found that 76% of women in the tech industry have faced discrimination. Combined with inflexible opportunities from some organisations, these have been cited as contributing factors as to why 50% of women leave the tech sector before the age of 35. This exodus of female employees inevitably means there are fewer women with enough experience to reach senior leadership positions.

Why are women important to AI?

According to recent statistics, 69% of businesses believe that having women in key decision making roles will greatly benefit the development and deployment of AI. Apart from the clear benefit of greater equality, why is it that women are specifically needed in AI teams?

Gender bias

Many thought leaders in the industry have highlighted the need for gender diverse AI teams. Currently, the number of women in these teams is low which can inadvertently lead to a bias within AI systems.

AI is trained on the information it has been fed and makes decisions based on that data. Humans are generally the ones who generate, collect, and label data sets which are then processed by AI. If there is gender bias within the information the platform is given, then the information that is outputted will include bias.

A study by the Berkeley Haas Centre for Equality found that 44% of AI systems showed gender bias and 25% exhibited both gender and racial bias. Some of the evidence cited included voice recognition systems run by AI performing worse for female voices, and a facial recognition system that misclassified women more than men, particularly women from minority ethnic groups. This was due to data sets that lacked diverse samples.

Machine learning in AI is led by humans, so more women in development teams choosing which data sets to use, correcting biased results and information, and supervising the AI learning process, can help to reduce gender bias within AI systems.

Different perspectives

AI is quickly becoming part of everyone’s lives. It is being used in recruitment processes, business operations, healthcare, and customer service. There are very few industries that aren’t looking to use AI within their practices. With women making up roughly half of the population, their need and reliance on AI will increase accordingly. AI needs to be programmed to reflect the population as is and provide accurate information for everyone.

In a UN interview with Natacha Sangwa, who is part of the African Girls Can Code programme, Natacha suggested that when women use AI to help diagnose illnesses, they receive inaccurate answers, “because AI is not aware of symptoms that may present differently in women…”. If the system is not aware of other people’s experiences, it cannot give an accurate or nuanced answer. This shows how crucial it is to focus on how an AI system is being taught.

Strategic roll out

Women, in particular, are needed in strategic and top-level positions to direct the purpose and deployment of AI technologies. The IBM study found that 74% of businesses see female leadership as important for ensuring the economic benefits of AI are felt throughout society. Having a diverse leadership team means that the deployment of this technology can be marketed to a wide range of people. Employing women in both junior and senior leadership roles can ensure that the advantages of having a diverse team throughout all levels of the business can be fully realised.

How should businesses attract women?

If an organisation isn’t actively working to improve their recruitment processes to attract women, they may struggle to hire great female IT professionals. Some of the main ways businesses can attract more female professionals into junior and senior roles include:

• Considering the company’s EVP (employee value proposition) and how it might be used to attract more women
• Creating a diverse recruitment campaign that focuses on the removal of unconscious bias throughout the process
• Considering approaching a recruitment specialist agency to help support key D&I goals
• Using mentorship programmes to encourage junior female tech employees to rise through the business and limit the chances of them leaving
• Conducting employee surveys for junior members to report any issues they may be facing and address them, limiting chances of a high female turnover
• Using training programmes to upskill employees they already have

If you need support in finding fantastic AI professionals for your tech team, or you want to improve your recruitment processes to limit unconscious bias, consider getting in touch with VIQU’s award-winning IT recruitment professionals.