The annual report of the World Economic Forum on parity warns that the Covid-19 pandemic has slowed down the progression of parity by several decades. Instead of 99.5 years, it will now take 135.6 years.
The report questions the economic impact of lockdowns around the world, which has affected sectors employing large numbers of women, as well as the additional care to be provided to family members, which is the responsibility of women.
The tech sector has made some progress, however, but more can be done, the Forum leaders recognize. Tech companies have indeed published annual reports on the diversity of their workforce, and while progress has been made, it is not enough.
End the prejudices of qualified candidates
Sheila Warren, head of blockchain and data policy at the World Economic Forum, tackles a common myth that diversity in the tech industry is hampered by a lack of qualified candidates. “In most fields, it’s not real – 42% of STEM (science, technology, engineering and math) doctoral applicants are women – in any industry, that’s no excuse . By developing comprehensive inclusion pathways, rather than focusing narrowly on hiring, companies can tackle the underlying systems that drive 50% of women in tech to leave the industry before the age of 35. years. “
Women employed in data and artificial intelligence (AI) industries now represent 32%, an increase of 10 percentage points from 22% in the previous gender gap report.
Kay Firth-Butterfield, head of artificial intelligence and machine learning at the Forum, says it’s especially important in AI that more women are employed. “Suppose only men create algorithms. In this case, they bring their biases and their way of seeing the world into the way they code, which increases the biases. “
Parity for responsible development of AI algorithms
According to Kay Firth-Butterfield, it is important that women are employed in all aspects of AI and across an organization to ensure the responsible development of AI algorithms that include many people and do not not just represent engineers.
There is a very real danger that AI systems assume that the lack of women in their training data is a result of them not having the right qualities and then this gender bias becomes encoded and amplified. in the development of AI.
The World Economic Forum will present this week the Global Technology Governance Summit, which will discuss the responsible design and use of emerging technologies.