Across the Global South, most people now rely on data-driven systems for welfare, banking, and healthcare. Yet not all data systems are designed with justice in mind. As emerging economies undergo rapid digitization, data justice is becoming a critical lens for evaluating how data directly affects people’s lives. Beyond privacy and accuracy, the central question is whether data systems actively promote equity, inclusion, and dignity.

Where complex social hierarchies intersect with accelerating technological adoption, data justice becomes not only desirable — but urgent.

From privacy to data justice

Data justice highlights the use of data to promote equity, dignity, and inclusion. It extends beyond debates about privacy and algorithmic accuracy. While privacy frameworks focus on protecting individuals, data justice emphasizes protecting communities, ensuring they are neither excluded nor misrepresented in datafied systems.

Data justice is emerging as a crucial framework for the Global South.

As Dencik, Hintz, and Cable (2016) note, data justice brings together diverse approaches and concerns in response to a dominant discourse that centers either efficiency and security or privacy and data protection. By contrast, data justice looks holistically at whose needs are reflected, whose rights are upheld, and whose harms are addressed.

Why the Global South?

Data justice is particularly urgent for marginalized groups across gender, disability, and socio-economic lines. While countries such as India, Nepal, and Bhutan have made substantial legislative progress, effective implementation remains uneven.

Photo Courtesy of Ghana Social Opportunities Project

South Asia is actively shaping its own approaches to data governance, influenced by shared colonial histories, cultural ties, and related policy environments. Europe’s comprehensive frameworks are often treated as reference points, but South Asian models reflect distinct social and economic realities.

• India: After recognizing privacy as a fundamental right, India introduced a draft data protection bill and invited public consultation via the Telecom Regulatory Authority of India (TRAI), engaging civil society, industry, and legal experts.
• Nepal: Its RTI laws and the Privacy Act of 2018 provide rights of access, correction, and protection against unauthorized use, positioning Nepal as a regional leader.
• Bangladesh: The Digital Security Act of 2018 emphasizes consent and privacy.
• Pakistan: The 2018 Draft Personal Data Protection Bill proposed the creation of a National Commission for Personal Data Protection.
• Bhutan and Maldives: Recent legislation and master plans indicate growing attention to data governance.

Despite promising steps, regional challenges persist: limited digital access, weak infrastructure, and a tendency to prioritize national security over human security. High-profile breaches, such as those associated with India’s Aadhaar biometric system, underscore the need for stronger safeguards.

Data justice highlights the use of data to promote equity, dignity, and inclusion.

While SAARC lacks a cohesive data protection agenda, national laws and constitutional guarantees suggest a slow but deliberate shift toward a rights-based approach.

Core pillars of data justice

Data justice emphasizes:

• Making community needs visible
• Recognizing community strengths
• Ensuring representation in data
• Supporting community self-determination

Its concerns include:

• Participation — Who is represented in datasets?
• Power — Who decides what data is collected?
• Distribution — Who benefits, and who is harmed?

Redress is essential: what happens when harm occurs, and how are remedies offered?

Digitizing social protection: Promise and peril

The rapid digitization of social protection systems offers both opportunity and risk. Governments such as Brazil and Kenya are deploying algorithms and digital IDs to streamline access to welfare benefits. While these systems can improve reach and efficiency, they also risk reinforcing existing inequalities.

Image Courtesy of Agência Senado

Digital platforms often simplify complex social realities into narrow data models. In Brazil, the Cadastro Único enabled more than millions of people to receive COVID-19 emergency support through an AI-enabled platform. Yet automated systems such as Bolsa Família often treat poverty as gender-neutral, overlooking caregiving burdens disproportionately carried by women — and thus potentially obscuring differentiated vulnerability.

Similarly, many social protection systems increasingly rely on data infrastructures developed or maintained by private technology companies, raising concerns about:

• Transparency
• Accountability
• Ownership and purpose
• Commodification of personal data

Women in Bolsa Família, for example, face a privacy paradox: they must disclose intimate personal data to access benefits, yet that data may later be used to surveil or penalize them.

Photo Courtesy of Huduma Kenya

In Ghana, the e-Zwich credit-scoring tool has expanded financial access but has faced criticism for its lack of transparency — particularly affecting women, who comprise much of the unbanked population.

Photo by Maria Schiffer, Courtesy of KfW

In Kenya, the biometric ID system Huduma Namba excluded a huge percentage  of rural residents due to structural and logistical barriers. Many digital systems prioritize administrative efficiency over equity, centralizing control in opaque algorithmic architectures.

Bangladesh a2i; Photo Courtesy of UNDP

Toward responsible governance

Robust governance is needed to ensure transparency, equity, participation, and redress. Some promising South–South developments include:

• Bangladesh’s a2i (Access to Information) initiative, which has created thousands of rural digital centers and been adapted in Bhutan and the Maldives.
• India’s Unified Payments Interface (UPI), which has informed Ghana’s e-Zwich and Kenya’s M-Pesa, demonstrating how South–South cooperation can accelerate inclusive innovation.

The Indian government's IDfy platform (Indian Digital Identity Verification and Fraud Prevention) requires users to provide explicit, auditable consent prior to data verification. This ensures that users retain agency over the use of their identity and verification data, which is in line with justice-by-design by emphasizing user control over silent enrolment.

TymeBank in South Africa combines low-cost physical access points with digital banking to reach underserved and rural clients. Its hybrid approach, which combines online onboarding with in-person assistance, encourages involvement and equity among many populations.

These examples highlight why data justice is essential now: successful models can spread, but so can harmful ones.

“Persistent inequalities… still confront us — calling urgently for renewed vision and collective action.”
— Gilbert F. Houngbo, ILO Director-General

A justice-by-design blueprint

A justice-by-design approach encourages continuous improvement, especially when systems affect communities with intersectional identities.

Community Input → Design → Deploy → Audit → Redress → Iterate

A shared blueprint rooted in community experience can accelerate change that is context-responsive and equity-driven — helping individuals evolve from passive recipients of services to co-architects of inclusive growth.

Justice-by-design helps ensure that products and platforms uphold dignity, avoid replicating inequities, and strengthen long-term resilience.

“Social development and social justice are indispensable for the achievement and maintenance of peace and security.”
— Copenhagen Declaration on Social Development, 1995

Justice-by-design checklist

• Community co-design with affected groups; publish a short participation note
• Data minimization and purpose limitation; clear opt-out and redress channels
• Inclusive consent flows: low-literacy, multilingual, offline options
• Human-in-the-loop for high-stakes decisions; audit disparity metrics
• Pricing/access guardrails: essential features zero-rated; no data-for-access trade-offs
• Local data-stewardship boards, including civil society; periodic public reports
• Procurement clauses mandating fairness + independent audits
• Harm tracking: document incidents, remedies, and design changes

This checklist is particularly relevant to impact entrepreneurs, ESOs, and responsible investors who design, fund, or support data-driven solutions. Justice-by-design helps ensure that products and platforms uphold dignity, avoid replicating inequities, and strengthen long-term resilience.

Toward equitable data futures

Data justice is emerging as a crucial framework for the Global South as governments, social enterprises, and investors increasingly rely on digital systems to deliver services and expand opportunity. But without intentional design, these systems risk deepening the very inequities they aim to address.

Ensuring that data systems are representative, transparent, participatory, and accountable is not just a rights-based imperative — it is necessary for building resilient societies and inclusive economies.

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Sources

• Dencik, L., Hintz, A., Redden, J., & Treré, E. (2019). Exploring Data Justice: Conceptions, Applications and Directions. Information, Communication & Society, 22(7), 873–881. https://doi.org/10.1080/1369118X.2019.1606268
• https://ccgdelhi.s3.ap-south-1.amazonaws.com/uploads/reconfiguring-data-governance-final-525.pdf
•  https://www.ilo.org/research-and-publications/state-social-justice-2025
•  https://www.dataeconomypolicyhub.org/
• Heeks, R., & Shekhar, S. (2019). Datafication, development and marginalised urban communities: an applied data justice framework. Information, Communication & Society, 22(7), 992–1011. https://doi.org/10.1080/1369118X.2019.1599039
• Ratts, Manivong & Greenleaf, Arie. (2017). Multicultural and Social Justice Counseling Competencies: A Leadership Framework for Professional School Counselors. Professional School Counseling. https://www.researchgate.net/publication/325624425_Multicultural_and_Social_Justice_Counseling_Competencies_A_Leadership_Framework_for_Professional_School_Counselors
• Newman, N. (2015, May). Big Data Is an Economic Justice Issue, Not Just a Privacy Problem.  https://www.huffpost.com/entry/big-data-is-an-economic-j_b_6877256
• Heeks, R. & Renken, J. (2017) Data justice for development: what would it mean? Information Development, advance online publication https://www.researchgate.net/publication/309959191_Data_justice_for_development_What_would_it_mean