Gender equality has stalled in the Artificial Intelligence (AI) sector, a critical “in-demand skillset of the future” says World Economic Forum (WEF) report highlighting a 72% Artificial Intelligence skills gender gap.

 
The recent WEF report highlights that:

• Only 22% of AI professionals globally are female, compared to 78% who are male
• This accounts for a gender gap of 72%
• WEF estimates that it will take 202 years for economic equality between men and women to be achieved around the world

Based on collaboration with LinkedIn, WEF found that only 22% of AI professionals globally are female, compared to 78% who are male.

This accounts for a gender gap of 72%, which has remained constant over the last years and does not look likely to improve.

This worrying trend may, in fact, exacerbate gender gaps in economic participation and opportunity in the future as AI encompasses an increasingly in-demand skillset, says the WEF.

The AI skills gender gap also implies that the use of this general-purpose technology across many fields is being developed without diverse talent, limiting its innovative and inclusive capacity; and that the low integration of women into the field is a significant missed opportunity in a profession where there is already a lack of adequately qualified labour.

>See also: Six ways to improve diversity in the technology workforce

AI technology that works for everyone

Commenting on the AI skills gender gap element of the report, Ben Lorica, Chief Data Scientist at O’Reilly Media says that if businesses want to create AI technologies that work for everyone, they need to be representative of all races and gender.

“Given that we know AI and automation technologies are continuing to grow, it’s important that the people who build them reflect the broader population. Currently, many AI products and applications are not fully autonomous and still involve humans. This means it is vital that developers are aware of the issues that are relevant to the diverse set of users we can expect to interact with these systems.

“If we want to create AI technologies that work for everyone – they need to be representative of all races and gender.

 “One of the striking findings from the report is that gender disparity in AI varies across industries, with health care and education sectors leading the way in terms of gender balance. Crucially, the software and IT sectors account for a big share of AI professionals. This is, therefore, an important sector to be aware of the importance of gender diversity within AI. As we move into the new year, we will see best practices for increasing diversity within AI emerge and shared across a wide range of industries. For example, past attempts at using machine learning for recruiting have proven to be counterproductive – with bias falling against women.

 “We need to raise awareness of the need to recruit more women into the AI sector. In doing so, the community can begin to mobilise and share strategies. Whilst the level of awareness is high amongst academic and industrial researchers, we still have a long way to go.

“As we are entering the implementation phase for AI technologies, more training and education platforms are becoming available in the sector. These new training platforms are vital if we are to begin to narrow the gender gap over the next year. The talent pool is only set to grow, yet – the challenge remains to ensure it becomes even more diverse”.

Representation makes better business sense

Jennifer Major, head of IoT at analytics leader at SAS UK & Ireland stresses that the need for more representation of women and other groups across the board makes business sense and is not about being “politically correct”.

“These stats from the World Economic Forum are indicative of a wider problem with equal representation in tech. Women and other groups are under-represented across the board. That has to change and it makes business sense that it does.

“A homogenous group might not consciously discriminate against those who are different to itself – but it is more likely to privilege similar ideas and perspectives. As AI moves ever further into the mainstream, the industry must take steps to ensure that it is truly for all – not just a privileged few. As wide a range of viewpoints as possible must be fed into the development of AI. Only then can it fulfil its potential as a force for good.

“Let’s be clear about one thing – this is not about “political correctness”! This is about making decisions that make business sense. The contribution that these groups can make to AI is enormous and their skills will often complement those of the existing workforce. That any are prevented or deterred from working in this field is a huge waste of potential.

“AI will not be gender-biased unless the industry makes it so. Steps must be taken to educate people from the earliest stages about the opportunities available to them, and they must be encouraged to follow up on this throughout their careers.”

>See also: Data analytics: Harnessing the potential of a more diverse workforce