Integrating Large Language Models (LLMs) into the Indian judiciary promises access to justice but introduces severe risks. We identify the 'inertia of confidence'--an overconfidence phenomenon analogous to the Dunning-Kruger effect where LLMs provide incorrec...
VQV Signal
RESEARCH
WATCH
TECHNICAL
Can Legal AI Know When It Is Wrong? And Do Students Know When It Is?
Integrating Large Language Models (LLMs) into the Indian judiciary promises access to justice but introduces severe risks. We identify the 'inertia of confidence'--an overconfidence phenomenon analogous to the Dunning-Kruger effect where LLMs provide incorrec...
Integrating Large Language Models (LLMs) into the Indian judiciary promises access to justice but introduces severe risks. We identify the 'inertia of confidence'--an overconfidence phenomenon analogous to the Dunning-Kruger effect where LLMs provide incorrect legal verdicts with near-maximum confidence, driven by...
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Signal Strength 94%
Technical label WATCH
Public Interest 30
Category RESEARCH
Reader Depth TECHNICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 51
Practical Impact Score 0
Novelty Interest Score 48
Consequence Score 18
Curiosity Score 0
Shareability Score 48
VQV surfaced this signal because it is recent, relevant to Consumer AI, connected to arXiv.
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