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Even worse, filtering the data in this way makes the model biased, i.e., not a useful model. Imagine for example that someone created a model of human behavior
by jhgb 5y ago
Even worse, filtering the data in this way makes the model biased, i.e., not a useful model.
Imagine for example that someone created a model of human behavior...but filtered out behavior considered "toxic" (whatever that means). Then someone else would naively create for example a simulation of the reaction of a large group of people to some expected events. Now there's a chance that if these events occurred, that mass of people would actually react very differently...because the model was biased! I.e., it did not approximate the average reaction since reactions in some directions were artificially clamped. So now any decisions based on that model would be worthless.
- skybrian 5y agoThat’s making a lot of assumptions. This isn’t the sort of model that you could base such a simulation on. It’s glorified autocomplete. (Impressive for what it is, but unreliable.)
- jhgb 5y agoI'm speaking in generic terms, of course. All models should be at the very least unbiased, though -- that's the least demand you can make of them (and generally an easy one to check, compared to other properties, such as having minimum variance of all possible models and such.)
- skybrian 5y agoI sort of agree in principle but I’m not sure what unbiased means for a language model or how you would measure it, so this doesn’t sound all that easy to me.