Artwork
iconShare
 
Manage episode 516827968 series 3570694
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/a-new-metric-emerges-measuring-the-human-likeness-of-ai-responses-across-demographics.
Posterum Software introduces the Human-AI Variance Score, a new metric that measures how closely AI responses match human reasoning across demographics.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #human-ai-variance-score, #posterum-software, #ai-human-likeness-metric, #ai-demographic-bias, #chatgpt-vs-claude-comparison, #ai-contextual-reasoning, #ai-behavioral-variance, #good-company, and more.
This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com.
Posterum Software’s new metric, the Human-AI Variance Score (HAVS), measures how closely AI responses resemble human ones across demographics. Analyzing ChatGPT, Claude, Gemini, and DeepSeek, the study found top HAVS scores near 94 but notable political and cultural variance. The HAVS method prioritizes human realism over correctness in AI evaluation.

  continue reading

2000 episodes