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Emily Segal defines "tasteslop" as the hollow deployment of tasteful design markers stripped of their social context—what happens when AI or algorithms reduce taste to data indexes rather than genuine discernment. True taste requires idiosyncrasy, social validation, and tension; tasteslop has none of these.
- Good taste depends on three things: discernment (knowing why one thing beats another), pattern recognition (understanding historical and cultural references), and idiosyncrasy (personal, contextual connections that can't be easily copied). Tasteslop fails at all three.
- AI and algorithms can't have taste because taste is fundamentally social—it needs to be witnessed and validated by actual people. An LLM can only index data about what's considered tasteful; it can't understand why something would feel refreshing or contextually relevant in a specific moment.
- The same object becomes tasteful, vulgar, or camp depending on its social route and context. Trader Joe's tote bags cost hundreds in Japan but nothing in America. Obvious, copied taste markers (Togo couches, Dieter Rams books in moodboards) become vulgar precisely because they've lost their original context and idiosyncrasy.
As AI and LLMs make competent drafts trivial, the real edge shifts to human judgment—spotting what’s generic, diagnosing flaws, and owning outcomes. True value comes from combining taste with context, constraints, and stakes, not just selecting polished AI outputs.
- AI makes generic "7/10" drafts nearly free, so the scarce skill becomes diagnosing precisely why something is generic or risky, not just picking the best AI output
- The practical drill: generate 10-20 AI versions of an artifact, write a "fails because..." line for each, then rewrite the best under hard constraints (no buzzwords, one idea per sentence, real trade-offs noted)
- Refusal—recognizing when "good enough" hides risk or mismatches real needs—matters more than selection
- Real authorship requires holding actual stakes (regulatory liability, brand damage, budget/material constraints) that AI can't bear, so curation alone leaves humans without genuine ownership