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

Fuente: arXiv
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Main Authors: Behmanush, Hamayoon, Akhtari, Freshta, Weber, Ingmar, Cannanure, Vikram Kamath
Format: Preprint
Published: 2026
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author Behmanush, Hamayoon
Akhtari, Freshta
Weber, Ingmar
Cannanure, Vikram Kamath
author_facet Behmanush, Hamayoon
Akhtari, Freshta
Weber, Ingmar
Cannanure, Vikram Kamath
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2604_07253
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education
Behmanush, Hamayoon
Akhtari, Freshta
Weber, Ingmar
Cannanure, Vikram Kamath
Computers and Society
Artificial Intelligence
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.
title Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education
topic Computers and Society
Artificial Intelligence
url https://arxiv.org/abs/2604.07253