Gender gap question as firms rush for AI talentMonday March 13 2023
In recent years, companies have been on a drive to source and hire Artificial Intelligence (AI) talents.
A LinkedIn report released in 2020, for instance, showed that AI specialist is the leading emerging job in the US, with hiring growth for the role rising 74 percent annually over the preceding four years.
But in the rush to fill the talent gap, research has shown that organisations are missing one fundamental aspect; diversification of AI talent sourcing in relation to gender.
Kenya’s edutech institution Moringa School CEO Snehar Shah admits that over the years, there has been a significant gap in technology training for women.
The coding school is training a new generation keen on computer programming. “We need to admit that there is a gap and be conscious of addressing that gap,” he says.
Besides training, he notes that the gender imbalance question could also be addressed by balancing venture capital funding between both men and women-founded organisations.
Also read: The value of women on boards
“We understand from the East Africa Venture Capital Association that out of the $6 billion (Sh768 billion) of funding raised in Africa for tech start-ups, only $188 million (Sh24 million) went to women-founded organisations. At least now this data is tracked and there are purposeful efforts to increase women's participation,” says Mr Shah.
Among the Kenyan women who are in the AI space is Caroline Mukiira, the first-ever female general manager at IBM East Africa.
She works with clients in mobile, cloud, AI, blockchain, cognitive, automation, analytics, the Internet of Things, and large-scale enterprise transformational programmes.
“I believe that in this new era of cloud, quantum computing, data, and AI nearly every enterprise will become a technology company,” she says.
Ms Mukiira says what it takes to make it in such spaces are talent and integrity.
“If you learn how to take your rightful seat at the table of technology then you will succeed. Some of the challenges include pitching a business idea, making an AI design suggestion, or making a case for a promotion,” she says.
Kathleen Siminyu, an AI researcher who focuses on Natural Language Processing for African languages says for a woman to make it into the AI space, she should not walk alone.
“You cannot do it on your own, so find a community of like-minded individuals,” she says.
Ms Siminyu who works at Mozilla Foundation as a machine learning fellow to support the development of a Kiswahili Common Voice dataset and to build speech transcription models for end-use cases in the agricultural and financial domains says that her journey has not been easy but through the help of others, she was able to reach where she is today.
“I have learnt to acknowledge that feeling of inadequacy, which is sometimes irrational and to let it challenge me. Let it be a sign that it is time to stretch even further,” she adds.
Before joining Mozilla, Ms Siminyu was the regional coordinator of AI4D Africa, where she worked with machine learning and AI communities in Africa to run various programmes.
As the world races towards advanced versions of technological dawns, experts opine that organisations are losing out on massive unexploited potential by not onboarding more female AI experts.
Over the last decade, Kenya’s total value of an investment in AI is estimated at Sh13 billion, which hardly compares with South Africa’s Sh165.8 billion and Nigeria’s Sh60.3 billion, according to Microsoft’s Artificial Intelligence in the Middle East and Africa Outlook report.
Deloitte argues that the question of diversity within AI teams is directly impactful to one of the biggest challenges facing the discipline today: biases within AI systems.
Also read: Are women the future of management?
“Because of the need for AI teams to reflect the populations they intend to address, and given that half of the world’s population is female, having more gender diversity within AI is a matter of common sense,” states consultancy firm Deloitte in a topical study.
While most AI bias is unintentional and goes unnoticed if AI systems perpetuate existing forms of gender bias, they will fail to reach their fullest capacity and could ultimately hinder organisations’ progress in implementing AI effectively, the report noted.