---
title: "Show HN: Slop or not – can you tell AI writing from human in everyday contexts?"
slug: "show-hn-slop-or-not-can-you-tell-ai-writing-from-human-in-everyday-contexts"
date: 2026-03-12
category: community
tags: [openai, anthropic]
language: en
sources_count: 1
featured: false
publisher: AInauten News
url: https://news.ainauten.com/en/story/show-hn-slop-or-not-can-you-tell-ai-writing-from-human-in-everyday-contexts
---

# Show HN: Slop or not – can you tell AI writing from human in everyday contexts?

**Published**: 2026-03-12 | **Category**: community | **Sources**: 1

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## TL;DR

- A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop.

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## Summary

- A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop. Three wrong answers and you're out.
- The dataset covers 16,000 human posts from Reddit, Hacker News, and Yelp, each paired with AI generations from 6 models across Anthropic and OpenAI at three capability tiers.
- Early findings: Reddit posts are easy to spot — humans write too casually for AI to mimic convincingly. HN posts are significantly harder to distinguish.
- Every vote is logged with model, tier, source, response time, and position. Full dataset planned for HuggingFace, a paper to follow.

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## Why it matters

A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop. Three wrong answers and you're out.

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## Key Points

- A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop. Three wrong answers and you're out.
- The dataset covers 16,000 human posts from Reddit, Hacker News, and Yelp, each paired with AI generations from 6 models across Anthropic and OpenAI at three capability tiers.
- Early findings: Reddit posts are easy to spot — humans write too casually for AI to mimic convincingly. HN posts are significantly harder to distinguish.
- Every vote is logged with model, tier, source, response time, and position. Full dataset planned for HuggingFace, a paper to follow.

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## Nauti's Take

The methodology is solid: pre-2022 data, no adversarial coaching, length-matched, real platform contexts — that's more scientific rigor than most commercial detection tools offer. The implication is striking: if even tech-savvy HN users struggle to spot AI text, then 'just ask humans' is no longer a reliable safeguard. Whether the paper materializes depends on crowdsourced participation, but the dataset alone should be valuable for researchers.

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## FAQ

**Q:** What is Show HN about?

**A:** - A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop.

**Q:** Why does it matter?

**A:** A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop. Three wrong answers and you're out.

**Q:** What are the key takeaways?

**A:** A developer built a crowdsourced AI detection benchmark: two responses to the same prompt — one human (pre-2022), one AI — and you pick the slop. Three wrong answers and you're out.. The dataset covers 16,000 human posts from Reddit, Hacker News, and Yelp, each paired with AI generations from 6 models across Anthropic and OpenAI at three capability tiers.. Early findings: Reddit posts are easy to spot — humans write too casually for AI to mimic convincingly. HN posts are significantly harder to distinguish.

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## Related Topics

- [openai](https://news.ainauten.com/en/tag/openai)
- [anthropic](https://news.ainauten.com/en/tag/anthropic)

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## Sources

- [Show HN: Slop or not – can you tell AI writing from human in everyday contexts?](https://slop-or-not.space) - Hacker News AI

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## About This Article

This article is a synthesis of 1 sources, curated and summarized by AInauten News. We aggregate AI news from trusted sources and provide bilingual (German/English) coverage.

**Publisher**: [AInauten](https://www.ainauten.com) | **Site**: [news.ainauten.com](https://news.ainauten.com)

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*Last Updated: 2026-03-20*