This issue of the blog examines the gendered dimensions of digital technologies, showing how biases and inequalities are not just technical flaws but reflections of broader social and power structures.

From AI in healthcare to algorithmic management at work, digital technologies frequently mirror and amplify social inequalities, reinforcing existing power imbalances. Biased datasets, opaque algorithms, and digitally mediated environments disproportionately affect marginalised groups—women, Black communities, LGBTQIA+ communities, and transgender individuals—through misdiagnoses, unfair workplace decisions, online harassment, and discriminatory surveillance. Embedded in both physical and digital realms, these sociotechnical systems not only reflect power structures but also reveal the societal inequalities and biases they reproduce.

The first article shows how biased datasets in obstetric AI put marginalised patients at risk. It highlights clinical errors, systemic medical racism, and flawed risk modelling, while emphasising the urgent implications for maternal health, ethical practice, and the future of healthcare.

The second article looks at gendered differences in recognising and disputing bias, showing how people analytics can entrench inequality when workers—especially women—feel unable or unwilling to contest unjust outcomes.

The third article reveals how communication platforms can enable harassment, misogyny, and covert surveillance. 

The fourth article looks at public-space surveillance, unpacking racial bias in live facial recognition systems.  She situates real-time biometric monitoring within broader debates on policing, legality, and individual rights, raising questions about whose safety is prioritised and who benefits from these systems.