Back to browse
What's AI's go-to, public or private healthcare?

What's AI's go-to, public or private healthcare?

by bnfcl·Jul 23, 2026·8 points·3 comments

AI Analysis

●●●BangerDark HorseRabbit Hole

30,000 AI responses revealing systematic bias patterns across 100 models.

Strengths
  • Massive scale dataset with 30k responses enables statistical significance.
  • Interactive exploration reveals model-specific ideological patterns clearly.
  • Methodology transparency with reproducible prompts and version tracking.
Weaknesses
  • Single-topic focus limits broader applicability beyond healthcare policy.
  • Binary choice format may oversimplify nuanced model reasoning capabilities.
Category
Target Audience

AI researchers, policy analysts, journalists studying model bias

Similar To

LMSys Arena · HELM · BigBench

Similar Projects

AI/MLMid

Triad Engine beats Claude 4.6 (100% vs. 45%) on Rome cultural benchmark

The repo ships a runnable eval_framework.py and a 20-question public sample (samples/sample_20q.jsonl) so you can reproduce the headline model comparisons locally. The claim — Triad Engine hits 100% vs Claude 4.6 at 0/45% — is eye-catching, but the full 222-question dataset and detailed methodology are gated behind an email request, which makes reproducibility and cherry-picking concerns the main barrier to taking the results seriously.

Niche GemBold Bet
MysticBirdie
125mo ago
AI/MLMid

100% LLM accuracy–no fine-tuning, JSON only

Ancient Rome Q&A benchmark shows 81pp accuracy lift, but lacks adversarial defense evidence.

Big Brain
MysticBirdie
224mo ago