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AI systems require data. The more data they have, the better they perform. But the more data organizations collect, the greater their risk surface. This is the central paradox of applied AI: the tension between intelligence and privacy. For most of AI's history, the answer was simple: collect everything, secure it as best you can, and hope for the best. The breach of 2.6 billion records in 2024 (the largest in history) demonstrated the bankruptcy of this approach. Users are increasingly unwilling to trade privacy for convenience.
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