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Building the Future—Without Half the Population?
Artificial intelligence is often portrayed as the future of work, communication, and decision-making. But as 2025 unfolds, a sobering truth remains: the future is still being coded largely by men. Despite countless equity initiatives and diversity pledges, the gender gap in AI is as real—and as invisible—as ever.
A recent Harvard Business School study found that men are 35–50% more likely than women to use generative AI tools in professional settings. This disparity widens at the development level, where female representation in AI model training, infrastructure design, and ethics committees remains stubbornly low.
The Architects of Bias
Why does this matter? Because who builds the bots shapes what the bots become. As we explored in The Silent Bias, AI models inherit the worldview of their creators. When those creators skew homogenous, the results can quietly reinforce outdated norms.
As Brookings highlights, everything from voice assistant personas to resume parsers has been caught reproducing gender stereotypes. Alexa sounds female. Developers sound male. And too often, women’s resumes are penalised for breaks in employment or certain tones of confidence.
Even well-meaning systems can skew results. In AI Guardrails, we reported on bias mitigation strategies. But mitigation is a patch, not a solution. Representation is the long-term fix.
Beyond Inclusion Panels
True equity goes beyond token hires and glossy conference panels. The OECD stresses that gender equity in AI requires systemic change: curriculum access, funding pipelines, hiring reform, and retention strategies.
Meanwhile, the World Economic Forum warns that without intervention, the gap could widen. The most in-demand AI roles—prompt engineers, ethics architects, model trainers—are growing faster than the gender distribution is catching up.
And it isn’t just about careers. The BIS found that GenAI uptake is disproportionately male, threatening to mirror the same participation gap that once defined early computing.
Coding Culture from the Ground Up
Some groups are responding. The UNESCO Women4Ethical AI program champions gender-balanced model design. The ITU/UNESCO Girls in AI framework builds digital literacy for the next generation. But these efforts need scale—and funding.
Without it, the culture of AI development risks becoming self-reinforcing. As we noted in AI in Cybersecurity, monocultures in tech lead not only to bias, but to blind spots. Diverse teams find different bugs. They ask different questions.
Who’s Missing from the Machine?
In 2025, the question isn’t just who uses AI—but who gets to shape it. When bots write poems, sort CVs, and advise patients, their worldview matters. And right now, that worldview is too narrow.
If we want AI that reflects humanity, we need to ensure humanity is reflected in AI labs, pipelines, and policies. Otherwise, the gender gap won’t just persist—it’ll be built in, line by line.
About the Author
Stuart Kerr is the Technology Correspondent at LiveAIWire. He writes about AI’s impact on infrastructure, governance, creativity, and power.
📩 Contact: liveaiwire@gmail.com | 📣 @LiveAIWire
