We live in a world where a camera mounted on a street corner can pick out your face from a crowd, where a piece of software can calculate the likelihood that you might commit a crime, and where everything you do online can be silently collected, stored, and picked apart — all without you ever being told. Artificial intelligence has taken surveillance from something that was once selective and required human attention, and turned it into something that runs constantly, automatically, and at a scale that touches almost everyone. This is not a warning about the future. It is a description of the present, playing out in cities all over the world right now. The problem is that this leap forward has come at a real and serious price. AI surveillance systems are far from neutral. They carry built-in biases, they operate in ways that are difficult to see or question, and they repeatedly end up causing the most harm to the communities they are supposed to protect — racial minorities, people on low incomes, and those engaged in political activism. And underneath all of that, they press hard against something that every human being is supposed to have: the right to privacy. This paper takes a clear-eyed look at what happens when AI-driven surveillance collides with that right. Drawing on recent work in law, ethics, computer science, and governance — and looking carefully at how the US, EU, China, and Canada each deal with this problem — we identify five core issues: algorithmic discrimination, a surveillance scope that keeps expanding well beyond its original limits, legal frameworks that have fallen apart, a near-total absence of accountability, and a version of consent that has been so watered down it no longer means anything. From there, we lay out five practical steps that governments, regulators, and civil society can actually take. The argument running through all of it is straightforward: privacy will not be protected by half-measures. What is needed is structural reform, and the political courage to see it through.
Seemeen et al. (Fri,) studied this question.
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