Human labour is largely invisible to AI
Lennard Berger's blogA Cognitive Scientist's blog 🌙RSSAboutGitHubHuman labour is largely invisible to AI24 Sep 2026@Lennard BergerI am beginning this blog post with a quote of Ilya Sutskever from a podcast with Dwarkesh Patel:Yeah. This is one of the very confusing things about the models right now. How to reconcile the fact that they are doing so well on evals?
- ▪Lennard Berger's blogA Cognitive Scientist's blog 🌙RSSAboutGitHubHuman labour is largely invisible to AI24 Sep 2026@Lennard BergerI am beginning this blog post with a quote of Ilya Sutskever from a podcast with Dwarkesh Patel:Yeah.
- ▪This is one of the very confusing things about the models right now.
- ▪How to reconcile the fact that they are doing so well on evals?
Hacker News (AI / LLM) files mainly under ai. We currently carry 6,319 of its stories.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Fohlen |
| Canonical URL | https://fohlen.dev/posts/invisble-human-labour/ |
| Publication time | Thu, 24 Sep 2026 15:20:05 +0000 |
| Retrieval time | 2026-09-24T15:35:26.120Z |
| Last seen | 2026-09-24T15:35:26.120Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | _fBnlEWQRB1q · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Lennard Berger's blogA Cognitive Scientist's blog 🌙RSSAboutGitHubHuman labour is largely invisible to AI24 Sep 2026@Lennard BergerI am beginning this blog post with a quote of Ilya Sutskever from a podcast with Dwarkesh Patel:Yeah. This is one of the very confusing things about the models right now. How to reconcile the fact that they are doing so well on evals? You look at the evals and you go, “Those are pretty hard evals.” They are doing so well. But the economic impact seems to be dramatically behind. It’s very difficult to make sense of, how can the model, on the one hand, do these amazing things, and then on the other hand, repeat itself twice in some situation?In my opinion this echoes a plethora of researchers in the AI field.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Fohlen.
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