Encouraging women in AI has never been more urgent. A study by the World Economic Forum noted a gender disparity of 78 per cent male versus 22 per cent female in AI and data science.
This disparity isn’t just a challenge within the workforce.
It reflects a highly nuanced issue that goes beyond any single workplace and if not addressed will have highly negative implications for society.
We have seen a lot of work to encourage girls and women to become interested in STEM and address gaps in digital skills at an earlier age than in the past.
Yet now, there appears to be less effort to support women as they transition from higher education into a sustainable career in tech.
This is a challenge for the industry.
But the real problem is that as AI becomes ubiquitous in daily life, without a technology workforce that accurately reflects the structure of society, AI-based decisions are constrained by the limited societal and cultural biases of their designers.
The impact of such homogeneity in AI decisions and bias has already been seen in examples such as the automation of credit card and mortgage applications, to resume screening and other areas.
The industry challenge is not due to a lack of skills.
Continue reading: https://psnews.com.au/2022/04/25/battle-ai-bias-more-women-in-tech/
This disparity isn’t just a challenge within the workforce.
It reflects a highly nuanced issue that goes beyond any single workplace and if not addressed will have highly negative implications for society.
We have seen a lot of work to encourage girls and women to become interested in STEM and address gaps in digital skills at an earlier age than in the past.
Yet now, there appears to be less effort to support women as they transition from higher education into a sustainable career in tech.
This is a challenge for the industry.
But the real problem is that as AI becomes ubiquitous in daily life, without a technology workforce that accurately reflects the structure of society, AI-based decisions are constrained by the limited societal and cultural biases of their designers.
The impact of such homogeneity in AI decisions and bias has already been seen in examples such as the automation of credit card and mortgage applications, to resume screening and other areas.
The industry challenge is not due to a lack of skills.
Continue reading: https://psnews.com.au/2022/04/25/battle-ai-bias-more-women-in-tech/
