[Rperry2174]

This keeps repeating in different domains: we lower the cost of producing artifacts and the real bottleneck is evaluating them.

For developers, academics, editors, etc... in any review driven system the scarcity is around good human judgement not text volume. Ai doesn't remove that constraint and arguably puts more of a spotlight on the ability to separate the shit from the quality.

Unless review itself becomes cheaper or better, this just shifts work further downstream and disguising the change as "efficiency"

[SchemaLoad]

This has been discussed previously as "workslop", where you produce something that looks at surface level like high quality work, but just shifts the burden to the receiver of the workslop to review and fix.

[vitalnodo]

This fits into the broader evolution of the visualization market. As data grows, visualization becomes as important as processing. This applies not only to applications, but also to relating texts through ideas close to transclusion in Ted Nelson’s Xanadu. [0]

In education, understanding is often best demonstrated not by restating text, but by presenting the same data in another representation and establishing the right analogies and isomorphisms, as in Explorable Explanations. [1]

[0] https://news.ycombinator.com/item?id=40295661

[1] https://news.ycombinator.com/item?id=22368323

[lonelyasacloud]

> Unless review itself becomes cheaper or better, this just shifts work further downstream and disguising the change as "efficiency"

Or the providers of the models are capable of providing accepted/certified guarantees as to the quality of the output that their models and systems produce.