---
title: How To Control Smarter Intelligences
date: "2025-07-01T06:37:40Z"
lastmod: "2025-07-01T06:37:42Z"
categories:
  - llms
wp_id: 4155
description: "The way to govern smarter systems is through mechanisms like checklists, sampling, red-teaming, gating, consensus, and outcome-based evaluation."
keywords: ["AI governance", "checklists", "red teaming", "sampling", "consensus", "evaluation methods"]
---

![How To Control Smarter Intelligences](/blog/assets/ChatGPT-Image-Jul-1-2025-11_27_23-AM.webp)

LLMs are smarter than us in many areas. How do we manage them?

This is not a new problem.

- **VC partners** evaluate deep-tech startups.
- **Science editors** review Nobel laureates.
- **Managers** manage specialist teams.
- **Judges** evaluate expert testimony.
- **Coaches** train Olympic athletes.

… and they manage and evaluate "smarter" outputs in **many** ways:

1. **Verify**. Check against an "answer sheet".
2. **Checklist**. Evaluate against pre-defined criteria.
3. **Sampling**. Randomly review a subset.
4. **Gating**. Accept low-risk work. Evaluate critical ones.
5. **Benchmark**. Compare against others.
6. **Red-team**. Probe to expose hidden flaws.
7. **Double-blind review**. Mask identity to curb bias.
8. **Reproduce**. Re-running gives the same output?
9. **Consensus**. Aggregate multiple responses. Wisdom of crowds.
10. **Outcome**. Did it work in the real world?

For example:

- **Vibe coding**: Non-programmers might glance at lint checks (**Checklist**) and see if it works (**Outcome**).
- **LLM image designs**: Developers might check if a few images look good (**Sampling**) and check a few marketers (**Consensus**).
- **LLM news articles**: An journalist might run a **Checklist**, a **Double-blind review** with experts, and **Verify** critical facts (**Gating**).

You **already** know many of these. You learnt them in Auditing. Statistics. Law. System controls. Policy analysis. Quality engineering. Clinical epidemiology. Investigative journalism. Design critique.

Worth brushing up skills. They're **more** important in the AI era.