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Face recognition plays an increasingly important role in our security and surveillance infrastructure, despite substantial evidence that neither human observers nor automatic systems can reliably match unfamiliar faces in real-world settings. In the present article, we contrast real-world performance with performance in benchmark tests. We then consider human limits in unfamiliar face matching, and offer two discussion points: First, that face photographs may not contain enough information to establish a reliable match in practical settings. Second, that we should abandon photographic snapshots as a means of identifying unfamiliar people. We end by outlining some broad alternatives to relying on face photographs.