NEW DELHI: Artificial intelligence is quietly shaping everyday decisions — from who gets hired and promoted to who receives a loan or a medical diagnosis. But as AI becomes more embedded in daily life, a troubling reality is emerging: when trained on biased data, technology can reproduce the very gender inequalities women have fought for decades to overcome.
“AI systems, learning from data filled with stereotypes, often reflect and reinforce gender biases,” says Zinnya del Villar, a leading expert in responsible AI, in a recent conversation with UN Women. “These biases can limit opportunities and diversity, especially in decision-making, hiring, loan approvals and even legal judgments.”
At the heart of AI lies data. Algorithms learn from past patterns — and when those patterns reflect a world where men dominated leadership roles and women were confined to caregiving professions, AI can absorb and repeat those assumptions. A hiring tool trained on such data, for instance, may unknowingly favour male candidates, pushing qualified women out of the race before a human ever sees their application.
This phenomenon, known as AI gender bias, occurs when machines treat people differently based on gender because bias was built into the data they learned from.
WHEN BIAS TURNS HARMFUL
The impact of biased AI extends far beyond recruitment. In healthcare, AI systems have been found to focus more heavily on male symptoms, leading to misdiagnosis or delayed treatment for women. Digital voice assistants defaulting to female voices reinforce outdated stereotypes that associate women with servitude and compliance. Language models often link words like “nurse” to women and “scientist” or “leader” to men — subtle cues that shape perception.
Some of these failures are well documented. In 2018, Amazon shut down an AI recruitment tool after discovering it systematically favoured male resumes. Image recognition systems have also struggled to correctly identify women, particularly women of colour — a flaw with serious consequences in policing and surveillance.
WHY INCLUSION MUST START AT THE DESIGN STAGE
“Artificial Intelligence mirrors the inequalities present in society,” del Villar explains. Addressing gender bias, she says, begins with fixing what AI learns from.
Training data must be diverse and representative of different genders, communities and lived realities. Equally important is who builds these systems. When AI teams lack gender and cultural diversity, blind spots multiply. Public awareness and education are also crucial — empowering users to question AI-driven decisions and demand human oversight where it matters most.
CAN AI HELP CLOSE GENDER GAPS?
Despite the risks, AI also holds promise as a tool for gender equality. It has already been used to uncover gender pay gaps across industries, analyse bias in textbooks and highlight disparities in online education enrolment. In finance, AI-powered tools are helping reduce bias in credit scoring, expanding access to loans for women entrepreneurs, particularly in underserved regions.
“AI is also tracking gender representation in leadership roles and supporting gender-sensitive policymaking,” del Villar notes. In the future, such tools could help governments assess how laws impact women before they are implemented.
MAKING DIGITAL SPACES SAFER FOR WOMEN
As online harassment and technology-facilitated violence rise, AI is also being used to protect women. Safety apps like bSafe offer emergency alerts, while platforms like Botler.ai help survivors understand their legal options. AI-powered chatbots now provide anonymous emotional support, legal guidance and referrals, making help more accessible.
“AI can play a powerful role in detecting and removing harmful content, including non-consensual intimate images,” del Villar says.
FIVE STEPS TOWARDS GENDER-INCLUSIVE AI
To ensure technology works for women, not against them, experts recommend:
- Using diverse and representative data
- Making AI systems more transparent
- Building inclusive AI development teams
- Adopting strong ethical frameworks
- Integrating gender-responsive policies from the start
As AI shapes the future, the choices made today will determine whether it reinforces old hierarchies — or helps women finally dismantle them.
