Gender and Technology

Technology isn’t neutral—it reflects and reinforces power structures. In India, gender intersects with caste, class, and geography, yet is treated as an afterthought rather than an essential component of policymaking, governance, and product design. Tech policy and governance must be gender-responsive to prevent exclusion. At Digital Futures Lab, our research reveals systemic gendered impacts, demanding deeper integration beyond tokenism or siloed approaches.

Key Learnings from Our Work

1. Access to technology has improved for women, but does not guarantee autonomy.

While more women in India can now access mobile phones, this does not always translate to digital agency. Many rely on male family members to set up accounts, make online transactions, or decide what content they can engage with. With that also comes the risks of surveillance and monitoring. Digital inclusion must go beyond device ownership to ensure meaningful participation and autonomy.

2. AI needs context to avoid reinforcing gender bias.

Our research on Indian language large language models (LLMs) found that AI systems trained on biased datasets amplify stereotypes, misrepresent gender roles, and exclude non-binary identities. Without deliberate interventions in dataset curation, model evaluation, and structural awareness, AI will continue to reproduce these biases.

3. More digital access, more digital harm.

Women—especially those in public-facing roles—face relentless harassment and deepfake abuse. Existing legal frameworks struggle to keep pace with digital harms, leaving them with little recourse. Stronger protections, platform accountability, and survivor-centred solutions are critical to moving beyond the conventional protectionist approach to safety, which often turns into another form of surveillance.

4. AI tools can help with climate action and public health but must consider gender risks.

AI is shaping climate action and public services but often ignores gendered access. Tools for conservation, disaster response, and agriculture assume a “neutral” user, overlooking vulnerabilities. For example, AI wildlife cameras have recorded women in forested areas, leading to privacy violations. Gender-aware AI design is crucial for ethical deployment.

5. AI is changing the workplace, but without intervention, it risks pushing women out.

GenAI's adoption threatens entry-level tasks like secretarial work, often held by women, risking workforce decline. Meanwhile, care and labour-intensive roles may gain value but remain undervalued and exploited. Addressing these shifts is crucial to ensuring gender equity in an evolving job market.

Here are some of the key projects that have shaped our understanding so far:

• Feminist Futures Now – Highlighting inclusive policies on privacy, AI ethics, online safety, and free expression toward gender-equitable digital futures.
• From Code to Consequence: Interrogating Gender Biases in LLMs in India – Researching gender bias in AI development and deployment, testing multiple Indian language LLMs, and developing a user-testing guide for developers.
• Responsible AI Fellowship – India’s first capacity-strengthening program on Responsible AI, mentoring social impact organizations on integrating responsible AI principles.
• AI + Climate Futures in Asia & Code Green - Cutting through the hype around AI & Climate Action in Asia, surfacing the latest scientific research & expert insights.
• Future of Work - Unpacking the impact of rapid GenAI adoption on India’s future of work to identify key levers of change and policy pathways towards inclusive labour futures.

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