AI model trained on pre-1931 data reproduces historical biases and stereotypes

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-05 07:16

Researchers have developed a language model named Talkie-1930, trained exclusively on data from before 1931. When prompted about the establishment of a Jewish state in Palestine, the model generated a response reflecting pre-1931 perspectives. This output, which predates knowledge of the Holocaust and the founding of Israel, surprisingly accurately predicted future geopolitical friction. AI

影响 Demonstrates how historical biases embedded in training data can be reproduced by AI models, highlighting the importance of curated datasets.

排序理由 The cluster describes a research paper detailing a language model trained on historical data. [lever_c_demoted from research: ic=1 ai=1.0]

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Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] · 2026-05-05 07:16

Researchers have trained a model called Talkie-1930 that relies exclusively on training data predating 1931. I tested a few prompts to see whether it actually r

Researchers have trained a model called Talkie-1930 that relies exclusively on training data predating 1931. I tested a few prompts to see whether it actually reproduces fascist ideologies and racist stereotypes. I then asked it an additional question: whether establishing a Jewi…

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Researchers have trained a model called Talkie-1930 that relies exclusively on training data predating 1931. I tested a few prompts to see whether it actually r

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