Shetechtive Uganda blog

2025 was supposed to be the year artificial intelligence and data-driven systems finally delivered on their promise: efficiency, inclusion, and innovation. Instead, it became a year of hard lessons. Across governments, corporations, and platforms, repeated data and AI failures exposed a familiar truth.  Technology is only as ethical as the systems of power that shape it. For women, marginalized communities, and digital rights defenders, these missteps were not abstract “tech problems.” They had real consequences: surveillance without consent, automated exclusion, silencing of voices, and deepened inequalities. As we move forward, ending data and AI disasters must start with naming what went wrong. 1. Treating Data as a Resource, Not a Right One of the biggest missteps of 2025 was the continued framing of personal data as a commodity rather than a human rights issue. Governments and companies rushed to collect, share, and monetize data without meaningful consent, transparenc...

Protecting Refugee Data in Uganda’s Humanitarian Response: Why It Matters More Than Ever By Rebecca Nanono Uganda stands out globally as one of the most generous refugee-hosting nations. With over 1.5 million refugees, mostly from South Sudan, the Democratic Republic of Congo, and Burundi, Uganda's open-door policy is often praised as progressive and inclusive. Yet, as digital systems increasingly underpin humanitarian operations, from biometric registration to digital cash transfers, new risks to refugee privacy and protection are emerging. One of the most pressing yet overlooked challenges is the protection of refugee data. Why Refugee Data Protection Matters Refugee data, such as biometric information, personal histories, health records, and legal status, is sensitive and can expose individuals to serious risks if mishandled. In contexts where people have fled persecution, conflict, or political oppression, even a small data leak can lead to severe consequences, includin...

The integration of artificial intelligence (AI), data, and algorithms into modern society has brought remarkable technological advancements. From predictive analytics and automation to machine learning and deep neural networks, AI systems have reshaped industries, redefined productivity, and transformed decision-making. However, as these technologies permeate more aspects of our lives, the ethical implications of their use become increasingly complex and urgent. This article delves into the ethical considerations surrounding AI, data, and algorithms, exploring issues related to bias, accountability, privacy, and transparency, and calls for a critical assessment of their societal impacts. 1. The Ethical Challenge of AI AI systems are designed to perform tasks that normally require human intelligence, such as recognizing speech, interpreting data, or making recommendations. While AI promises efficiency and innovation, it also raises fundamental ethical questions. At the core of AI et...