# AI Selection Tech Data Algorithms

> - Use FIRST when evaluating, classifying, or comparing any AI-based or technologically enhanced personnel selection tool — to separate the three independent things it combines: technologies, data, and algorithms (Tippins, Oswald & McPhail, 2021). Establishes that a technology is never "universally valid," that data range from intentional to incidental, and that ML effectiveness depends more on data quality than algorithm choice. Triggers: "evaluate an AI hiring tool", "is this video-interview/game/social-media tool valid", "AI vs ML vs deep learning", "supervised vs unsupervised selection", "big data hiring", "what does this technology actually measure".

## Facts
- Page: https://tashan.sh/capability/skill-openmatter-network-ai-selection-tech-data-algorithms
- tashan id: skill:OpenMatter-Network/ai-selection-tech-data-algorithms
- Source: https://github.com/OpenMatter-Network/agent-io-skills
- Type: skill
- Category: search
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 71.0
- Freshness: 76.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: MIT
- Official: no

## Install

```sh
cp -r ai-selection-tech-data-algorithms ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

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Measured 2026-08-15 by tashan (https://tashan.sh) from public evidence. Scorer s5.