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concept:bender-et-al-2021-on-the-dangers-of-stochastic-parrotsBender et al. 2021: On the dangers of stochastic parrots
Paper on LLM biases from training data; cited in relation to base models reflecting training data biases
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Derogatory term for LLMs; Nix's commentary frames it as camp opposite to nascent consciousness.
- Key motivation for precautionary action.
- Distinguishes genuine context-driven adaptation from mere statistical randomness.
- Key distinction between genuine living structure and pseudo-random variation.
- Core claim: Turing test and brain homology fail for synthetic, AI, and radically non-human agents; new frameworks required.
- Core normative claim: frameworks must identify fundamental properties of sentience independent of phylogenetic accident or familiar substrates.
- Normative motivation for the paper's conceptual contribution
- Related work studying capability of LLMs to subvert safety measures if severely misaligned