Where is the female voice in the AI Ecosystem?

Did you know that there is a significant gender divide when it comes to AI usage and adoption?

Forbes writes: “Artificial intelligence has a gender issue, and it’s not just about the images it creates or the biases that models may include”.

Overwhelming statistical research shows that women use generative artificial intelligence tools less than men do. Surprisingly the gap is biggest among the youngest workers, a new survey from Slack finds. It includes results from a survey of more than 10,000 “desk workers” and found that Gen Z men are 25% more likely to have tried AI tools compared to Gen Z women. 

The Kenan Institute has established that nearly 80 per cent of today’s female workers are in jobs exposed to automation via generative AI, compared with 58 per cent of men. These jobs will not be replaced by artificial intelligence, but by people who have mastered AI. And in the current landscape, that means men. 

Lack of diversity in AI development

Another factor gives cause for even greater concern. According to a training expert on the Coursera platform, women are underrepresented in the development of AI-related skills. In fact, three times as many men as women sign up for the most popular AI training courses on this platform.

This is not breaking news - a BBC article at the end of 2023 addressed this very issue. They interviewed AI expert Jodie Cook who says there are deeper, more ingrained reasons why women are not embracing the technology as much as men.

"Stem fields have traditionally been dominated by males," says Ms Cook, who is the founder of Coachvox.ai, an app that allows business leaders to create AI clones of themselves.

"The current trend in the adoption of AI tools appears to mirror this disparity, as the skills required for AI are rooted in Stem disciplines."

And then there’s the matter of the low representation of women in senior management positions in the fields of science, technology, engineering, and mathematics, and consequently, in AI.

"This is something that we should be keeping an eye on," says Christina Janzer, head of Slack's Workforce Lab. "My hypothesis is that the people who are using it today are the people who are going to help shape the future of it. We want those people to be representative of our entire population. That's not what we're seeing today. This is a big opportunity for leaders to understand that and to course-correct."

Psychologist Lee Chambers says that typically female thinking and behaviour may be holding some women back from embracing AI.

"It's the confidence gap - women tend to want to have a high level of competence in something before they start using it, " he says. "Whereas men tend to be happy to go into something without much competence."

Mr Chambers also says that women may fear having their ability questioned, if they use AI tools.

"Women are already discredited, and have their ideas taken by men and passed off as their own, so having people knowing that you use an AI might also play into that narrative that you're not qualified enough. It's just another thing that's debasing your skills, your competence, your value."

I was interested to see what AI itself had to say on the matter. I asked Copilot “why are women less likely to use AI”? This was the response:

• Trust and Reliability Concerns: Some women may find AI tools less reliable or trustworthy. For instance, errors in AI outputs can lead to skepticism about their accuracy.
• Perception of Competence: Women often feel the need to emphasize their credentials more to demonstrate their expertise. Using AI might be perceived as undermining their qualifications.
• Safety and Ethical Concerns: Women tend to be more concerned about the ethical implications and safety issues related to AI, such as biases in AI algorithms and the potential misuse of AI-generated content.
• Personalization and Authenticity: Many women prefer to maintain a personal touch in their work, feeling that AI might strip away the authenticity and personalization they value.
• Lack of Awareness or Training: There might be less exposure or training opportunities for women in AI, leading to lower adoption rates.

Then I asked, “What can be done to encourage more women to use AI”? Its response was: 

Encouraging more women to use AI involves a multifaceted approach. Here are some effective strategies:

• Early Education and Outreach: Introducing AI concepts and technology to girls at a young age through educational programs, workshops, and coding classes can ignite interest and build confidence.
• Role Models and Mentorship: Highlighting successful women in AI and providing mentorship programs can inspire and guide aspiring female AI professionals. Seeing relatable role models can make a significant difference.
• Inclusive Work Environments: Promoting inclusive and supportive work environments where women feel valued and respected is crucial. This includes addressing biases and ensuring equal opportunities for advancement.
• Upskilling and Training Programs: Offering upskilling programs, internships, and gamified challenges can help women develop the necessary skills and confidence to succeed in AI.
• Community and Networking: Creating communities and networks for women in AI can provide support, resources, and opportunities for collaboration and growth.
• Addressing Stereotypes and Bias: Challenging stereotypes and biases that discourage women from pursuing AI is essential. This can be done through awareness campaigns and by promoting positive narratives about women in tech.

There are several successful initiatives aimed at promoting women in AI – AI4ALL; IBM’s Women Leaders in AI; Women in AI (WAI); Algorithmic Justice League; and Women in Machine Learning (WiML) but more must be done.

So why is it important?

Who develops AI, and what kind of data it is trained on, has gender implications for AI-powered solutions. It mirrors the biases that are present in our society and that manifest in AI training data. In a rapidly advancing AI industry, the lack of gender perspectives, data, and decision-making can perpetuate profound inequality for years to come.

Sola Mahfouz, a quantum computing researcher at Tufts University - “When technology is developed with just one perspective, it’s like looking at the world half-blind,”

As an opportunity, one of the most interesting aspects of the gen-Ai ‘revolution’ is the recognized requirement for a range of soft skills in employees within the field. These skills include critical thinking, problem-solving, and collaboration alongside the ability to communicate the strengths and weaknesses of using artificial intelligence, as well as when not to use it.

Qualities like creativity, persistence and decision-making will grow more and more important as AI and the very nature of the professional world continues to evolve. While technical skills will always prove important, intangibles like these can often make the difference between two equally skilled candidates. 

In conclusion, the AI field needs more women, and that requires enabling and increasing girls’ and women’s access to and leadership in STEM and ICT education and careers. Understanding and bridging the AI gender gap is essential for ensuring equitable access and representation in the burgeoning AI landscape.

AI itself says “By implementing these strategies, we can create a more inclusive and diverse AI ecosystem”.