Proxpert Legal

AI For Her: Beyond The Algorithm

Leveraging Artificial Intelligence (AI) For Gender Justice In Uganda

Introduction
For all the hype about Airtificial Intellgence, most of the conversation remains confined to boardrooms, startups and productivity hacks. It rarely appears in conversations about the widow in Kayunga being evicted from her late husband's land. Or the market vendor in Owino locked out of a business loan because she has no credit history. Or the survivor of domestic violence in Gulu with no safe, accessible way to report her abuser. This is not just a failure of imagination. It is a failure of policy, of design, and of whose lives we decide technology should serve.

Artificial intelligence, deployed deliberately and designed inclusively, is one of the most scalable tools available to dismantle the structural inequalities that have kept Ugandan women on the margins of land ownership, economic participation, and legal protection. This article examines three of the most critical areas; land and property rights, economic rights, and gender-based violence, and makes the case for why AI must become a central part of Uganda's gender justice conversation.

The Legal Landscape: Rights on Paper, Gaps in Practice
Uganda's legal framework contains meaningful protections for women;
- Article 33 of the Constitution guarantees equality and mandates the state to protect women from all forms of discrimination.
- Uganda has ratified the Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW), committing - to address both legal and practical barriers to women's equality.
- The Domestic Violence Act of 2010 criminalises violence within the home.
- The Land Act recognises women's rights to own and co-own land.

Yet the distance between law on paper and justice in practice remains vast, and for millions of Ugandan women, it is that distance that shapes the course of their lives. Implementation is weak, enforcement is inconsistent, access to courts is geographically and financially prohibitive, and awareness of rights is low. Technology alone cannot close this gap, but it can make the gap significantly harder to maintain.

Land and Property Rights: The Dispossession Problem
Land is power. In Uganda, where agriculture underpins the livelihoods of most households, control over land is inseparable from economic security, social standing, and the accumulation of generational wealth. Despite women constituting approximately 80% of Uganda's agricultural labour force, they own less than 20% of land. When a spouse dies, widows routinely face eviction by in-laws, fraudulent transfers of property, and manipulation of customary processes they have no legal standing to contest. Formal documentation of ownership is sparse, court processes are slow and costly, and legal literacy remains critically low.

‍What AI Can Do
i) Digital land registry systems powered by AI can dramatically reduce fraud, close documentation gaps, and create verifiable ownership records that are harder to manipulate. Rwanda's nationally implemented Land Administration Information System (LAIS), one of Africa's most cited land governance reforms, demonstrates what systematic, technology-backed land regularisation can achieve on the continent. A comparable AI-assisted system in Uganda could map customary land holdings, flag suspicious transactions on estates of the recently deceased, and generate alerts when land linked to an unresolved succession is being transacted without court authorisation.

ii) Tools like Meridia, piloted in Ghana and Nigeria, use mobile technology and satellite imagery to help smallholder farmers formally document their land claims, a model directly adaptable to Uganda's rural women farmers.

iii) Voice-enabled interfaces in Luganda, Acholi, Runyankole, and other local languages could extend these tools to users with limited literacy.

iv) AI-powered document assistants could walk women through their rights under the Land Act in plain, accessible language without requiring them to hire a lawyer they cannot afford.

Economic Rights: The Invisible Borrower
Uganda's women are among Africa's most entrepreneurially active. They dominate informal trade, run household enterprises, and form the financial backbone of many communities. Yet they are systematically excluded from the formal financial systems that could allow those enterprises to grow. Traditional credit scoring relies on formal employment records, registered business histories, and tangible collateral; criteria that most Ugandan women in informal trade and smallholder agriculture cannot meet. No payslip. No credit history. No land title to pledge as security. The result is that women remain invisible to banks, shut out from growth capital, and often pushed into cycles of predatory informal lending that extract more than they offer.

‍What AI Can Do
i) Alternative credit scoring models use non-traditional data like mobile money transaction histories, utility payment records, savings behaviour, and airtime purchase patterns to build financial profiles for people who have never held a bank account.Tala and Branch, both active in Uganda, already use machine learning to extend credit to underserved borrowers based on these signals. The opportunity now is to design these systems with gender-disaggregated data from the outset, ensuring that the economic behaviours unique to women-led informal enterprises are recognised and rewarded rather than overlooked.

ii) AI-powered market linkage platforms can connect women producers directly to institutional buyers and processors, bypassing the layers of middlemen who disproportionately extract value from female-led supply chains. Ensibuuko, a Ugandan fintech serving rural savings and credit cooperatives (SACCOs), offers a local example of what digital financial infrastructure for grassroots communities can look like. Building AI decision-support layers on top of such platforms; tools that learn from women's financial patterns, surface relevant products, and reduce bureaucratic barriers, is a practical and achievable next step.

Gender-Based Violence: The Reporting Crisis
The statistics on gender-based violence in Uganda are both well-documented and deeply alarming. The Uganda Demographic and Health Survey consistently finds that a significant proportion of women have experienced physical or sexual violence, with rates markedly higher in rural areas and among women with lower education levels and limited economic autonomy.

The Domestic Violence Act of 2010 was a hard-won legislative achievement. But a law cannot serve a woman who has no transport to the nearest police station, no phone credit to call a helpline, and no confidence that reporting will lead to anything other than retaliation or community stigma. Geography, cost, institutional distrust, and fear create a wall between survivors and the legal protections nominally available to them.

‍What AI Can Do
i) AI-powered, anonymous reporting platforms accessible via basic feature phones and USSD technology with no internet connection required can allow survivors to report incidents, access information about nearby services, and receive guided safety planning support. Viamo, which already operates in Uganda and across sub-Saharan Africa, provides a working model for how voice-based AI tools can reach rural and low-literacy populations in their own languages.

ii) Natural language processing tools trained on Ugandan languages can power chatbots that walk survivors through their legal options in plain, accessible terms, explaining the process of obtaining a police bond, what a court protection order means in practice, and where the nearest legal aid clinic or safe house is located.

ii) For civil society organisations managing high volumes of GBV cases, AI case management tools can reduce the administrative burden on overstretched frontline workers, improve follow-up rates, and ensure no case falls through the cracks.

iii) Ethically designed predictive analytics developed with community input and approval can help organisations and local governments identify geographic hotspots and high-risk periods, enabling targeted, proactive prevention rather than reactive response alone.

Confronting the Bias in the Machine
None of this is straightforward. It must be stated clearly; AI systems reflect the data they are trained on, and that data reflects the world as it is, not as it should be. Globally, AI has demonstrated the capacity to replicate and amplify existing inequalities. Credit algorithms trained on historically male-dominated datasets have disadvantaged women applicants. Facial recognition tools have shown higher error rates for darker-skinned women. Language models trained predominantly on English exclude the vast majority of Uganda's population from meaningful use.

If AI tools for women's rights in Uganda are built on biased, incomplete, or non-representative data, they will not be neutral. They will cause active harm and they will do so with the additional authority that technology often confers. Building AI that serves Ugandan women requires deliberate, non-negotiable choices;
- Training datasets that include women's voices, experiences, and economic realities.
- Development teams that include women, particularly those from the communities being served, not as afterthoughts but as architects.
- User testing that centres the most marginalised rather than the most convenient.
- Governance frameworks that allow communities to contest, correct, and reject AI decisions that affect their lives.

Inclusive AI is not a feel-good add-on. It is the minimum standard for AI that claims to be just.

AI as a Justice Tool: Changing the Conversation
The conversation about AI in Uganda and across Africa broadly has been dominated by economic growth narratives; AI for agricultural productivity, AI for fintech scale, AI for smart cities. These are legitimate conversations worth having, but they consistently leave out a dimension that is equally urgent: AI as a tool for justice. Uganda's women do not need AI to be perfect. They need it to be purposeful. They need legal tech innovators, civil society organisations, government institutions, and development partners to ask, from the very first design stage, whether this tool will work for a widow in Kayunga, a market vendor in Owino or a survivor in Gulu.

AI need not belong only to those who already have power. Designed with intention, deployed with accountability, and built in partnership with the communities it is intended to serve, it can be a tool that changes the status quo persistently, consistently and at scale.

Uganda's legal and policy framework has made its promises to women. Technology, built with honesty and purpose, has a role to play in keeping them.


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