Depending on the training data/methods, those algos might just be mechanized heuristics. Or hunches. The real Q may not be the algos per se but our trust in the institutions using them. Concern re that is rising sharply—with justification
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What is the folk definition that excludes Steven's examples? The real story seems to be "sometimes algo ok, sometimes not, it's complicated" - not about real-world impact.
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What is the specific thing it means that people uniformly understand?
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Complex computational decision making that affects them, that’s opaque, not either under their control, accountable or transparent although consequential. It’s not all about how to color a map with four colors with no adjacencies.
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A reminder every so often is worthwhile I think, whether the word is ‘algorithm’ or ‘bully.’
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Algorithms were around for many centuries before computers. They've been around for millennia of you count the years before they were called algorithms.
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