Ask HN: Are engineers afraid of free text?

[brianjkim21]

Text classification isn't new. Yet, very few product & eng teams actually do text classification.

Do you build text classification models in house? Why do you think eng teams with 'obvious' use cases don't?

Some examples below: - LegalTech categorizing legal docs for lawyers - HR Tech tagging job descriptions by category - Insurance labeling docs/records for claims adjusters

[cmcollier]

There can be multiple reasons for this[0], including but not limited to:

* The people or industry have low tolerance or fear around risk of false positives

* The industry is centered around billable hours and has no incentive for automation

* The engineers or people perceive ML as this obscure/difficult thing

I'd say the incentives and risks have hindered lots of legal adoption (this is what I observed while working in legaltech for instance). Insurance sounds similar, but I'm less familiar and assume they are coming along more quickly.

[0] I agree with minimaxir's point, that it's a bad assumption to think few teams use basic ML functionality. This will become even more true as emergent tech such as zero shot classification with LLMs becomes more commoditized.

[minimaxir]

> Yet, very few product & eng teams actually do text classification.

This is an extremely incorrect assumption.

[brianjkim21]

Example? To clarify, I'm referring to product eng and SWEs.

If you have a Data / ML team, they will handle ofc.