Healthcare workers continue to face unacceptable levels of violence and harassment, with gender‑based harm woven deeply into these experiences. As AI tools rapidly enter this space, we urgently need to ask: Are these technologies helping us tackle the real problem — or reinforcing a narrow, incomplete view of it?
A new scoping review of 19 studies (2020–2025) was done by the Universitat de Barcelona. It shows a clear pattern. Current AI systems focus heavily on prediction, monitoring, and incident detection. They treat violence as something that can be neatly measured and categorised.
But gender — a core driver of workplace violence — is largely absent from these models. When it appears at all, it’s usually reduced to a demographic checkbox rather than recognised as a structural force shaping risk, power, and harm.
This gap isn’t just academic. It has consequences.
! When AI overlooks gendered dynamics, it risks reproducing the very inequities it’s meant to address.
! When violence is framed only as a technical problem, we lose sight of the organisational, cultural, and structural conditions that enable it.
! When healthcare workers — especially women and marginalised groups — aren’t part of the design process, their realities remain invisible.
If we want AI to contribute to safer, more equitable healthcare workplaces, we need to push for:
• Gender‑sensitive theoretical frameworks
• Ethical and jurisdictional governance
• Participatory, worker‑centred design
• A shift from technical fixes to structural understanding
This is a pivotal moment. AI is reshaping workplace safety — but it’s up to us to ensure it does so in ways that recognise and challenge gender‑based violence, rather than sideline it.
If you’re working at the intersection of healthcare, gender equity, and technology, let’s connect and keep driving this conversation forward.