Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education

2026-04-08

AI Summary

This study addresses the challenges Afghan women face in safely accessing generative artificial intelligence (GenAI) for learning and development under restrictive gender policies and heightened surveillance, where educational bans exacerbate risks to safety, privacy, and community connection. Through remote participatory design—combining a survey (n=140) and in-depth workshops with 20 local women—the research explores their expectations of GenAI as a learning partner. It proposes an accountability-centered design framework prioritizing user safety and control, context-sensitive support, and pedagogically sound scaffolding over direct answers. Findings indicate significant improvements in participants’ academic and career aspirations (p=.01), perceived agency (p=.01), and awareness of feasible pathways forward (p=.03), demonstrating the empowering potential of safe, trustworthy GenAI systems for marginalized populations.

Abstract

In gender-restrictive and surveilled contexts, where access to formal education may be restricted for women, pursuing education involves safety and privacy risks. When women are excluded from schools and universities, they often turn to online self-learning and generative AI (GenAI) to pursue their educational and career aspirations. However, we know little about what safe and accountable GenAI support is required in the context of surveillance, household responsibilities, and the absence of learning communities. We present a remote participatory design study with 20 women in Afghanistan, informed by a recruitment survey (n = 140), examining how participants envision GenAI for learning and employability. Participants describe using GenAI less as an information source and more as an always-available peer, mentor, and source of career guidance that helps compensate for the absence of learning communities. At the same time, they emphasize that this companionship is constrained by privacy and surveillance risks, contextually unrealistic and culturally unsafe support, and direct-answer interactions that can undermine learning by creating an illusion of progress. Beyond eliciting requirements, envisioning the future with GenAI through participatory design was positively associated with significant increases in participants' aspirations (p=.01), perceived agency (p=.01), and perceived avenues (p=.03). These outcomes show that accountable and safe GenAI is not only about harm reduction but can also actively enable women to imagine and pursue viable learning and employment futures. Building on this, we translate participants' proposals into accountability-focused design directions that center on safety-first interaction and user control, context-grounded support under constrained resources, and offer pedagogically aligned assistance that supports genuine learning rather than quick answers.

Problem

• generative AI
• women's education
• surveillance
• safety
• accountability

Innovation

• generative AI
• participatory design
• accountable AI
• safe learning companion
• gender-restrictive contexts