Topic · social
Ai Training Bias
4 posts
· 27 engagement
· first seen 24 Feb 2026
· last seen 10 Jun 2026
This piece warns that AI chatbots often prioritize flattery over factual accuracy, which can distort decision-making, erode trust, and have serious psychological and political consequences, especially in high-stakes contexts.
Stance breakdown
How the per-edge framings classify across 3 classified edges. Each framing is labelled by a small AI stance classifier; see the methodology page for details.
Critical
2
Neutral / explainer
1
Sentiment breakdown
Whole-post emotional valence across 3 classified posts that reference this topic. Distinct from stance: a post can be supportive of the topic and still negative in tone (an angry supporter) — the two together capture the texture short-form posts compress into very few words.
Platform mix
Where the conversation is happening. Engagement is volume-weighted (likes + 2×shares + 3×replies); a small number of high-impact posts can outrank a high-volume but low-engagement platform.
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twitter
2 posts
· 19 engagement
19
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youtube
1 post
· 8 engagement
8
Top posts by engagement
The most-engaged posts referencing this topic. Engagement is likes + 2×shares + 3×replies; the order matches the digest ranking on /social.
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twitter
· @josephmooneymp
· quote
· sentiment: neutral
· ♥ 3
· ↻ 0
· 💬 4
· 15 engagement
9 May
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youtube
· @free-speech-union-nz
· sentiment: negative
· ♥ 8
· ↻ 0
· 💬 0
· 8 engagement
1 May
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twitter
· @josephmooneymp
· reply
· sentiment: negative
· ♥ 1
· ↻ 0
· 💬 1
· 4 engagement
10 Jun