Security & privacy

Here's a number that should keep every operations manager up at night (no pun intended): OSHA data shows that accident and injury rates are up to 30% higher during night shifts compared with day shifts. Evening shifts aren't much better, with an 18% increase in risk. If you run a warehouse, distribution centre, or manufacturing operation that includes night shifts, this isn't a statistic you can afford to shrug off. The question isn't whether your night shift carries more ri

When we talk to safety leaders about computer vision AI, the conversations are almost always positive. They understand the technology, they see the value, and they're keen to explore it. But when it comes to rolling the technology out to the wider workforce, a different set of conversations begins. Workers have questions. Concerns. And sometimes, deeply held beliefs about what AI cameras do that simply aren't accurate. These misconceptions aren't unreasonable. Headlines about

This blog provides general information about workplace safety legislation in New Zealand and Australia. It is not legal advice. For guidance specific to your situation, consult a qualified legal professional. Worker participation in safety is one of those topics that tends to get filed under "best practice" — something organisations aspire to when they have the time and bandwidth, rather than something they are legally required to do right now. That is a misunderstanding wort

This blog provides general information about how workplace safety data and CCTV footage may be relevant in investigations and audits. It is not legal advice. For guidance specific to your situation, consult a qualified legal professional. When a WorkSafe inspector arrives following a serious incident, or when your ISO 45001 certification audit is scheduled for next quarter, there is one question that cuts through everything else: what does your evidence actually show? Not wha

If you mention AI cameras in a room full of warehouse workers, the first question won't be about detection accuracy or dashboard features. It'll be: "Is this going to be used to watch us?" It's a fair question. And how you answer it will determine whether your computer vision AI deployment succeeds or fails — not technically, but culturally. Because even the most sophisticated safety platform won't deliver results if the people it's designed to protect don't trust it. Privacy

If you're evaluating computer vision AI for workplace safety , the privacy question will come up early. It might come from your data protection officer, your legal team, your workers' council, or from the workers themselves. And the question is legitimate: when you connect AI to cameras that watch people work, how do you protect those people's rights? The answer depends on how the platform is designed, how it processes data, and whether the vendor has built privacy into the a

When you connect a computer vision AI platform to your CCTV cameras, you're handing it access to video feeds of your workplace. Footage of your people, your operations, your facility layout. That's a significant amount of trust to place in a technology vendor. So before you evaluate detection accuracy or dashboard features, there's a more fundamental question: how does this vendor protect your data? It's a question that doesn't get asked often enough. In procurement conversat