Why independent verification of AI output is crucial
This post will help you understand why checking AI's work independently is important. You will learn how to set up your own checks and what to do with the results.
Why separate the builder from the checker?
When you use AI tools, it is important to have an independent verification of AI output. This means someone or something other than the AI itself checks the work. Think of it like a builder constructing a house: you would not want the builder to be the only one to inspect the house for safety and quality. An independent inspector provides a fresh perspective and can spot issues the builder might miss. AI tools can make mistakes, and sometimes they can be very convincing even when wrong. Having a separate check helps catch these errors before they cause problems.
Why every check must be able to fail
A good check is one that can actually find problems. If your checking process always passes the AI's work, it is not a useful check. The purpose of a check is to identify errors, inconsistencies, or areas where the AI has not met your expectations. If a check cannot fail, it means it is not rigorous enough, or you are not looking for the right things. For example, if you ask an AI to summarise a document, your check should be able to find if the summary misses key points or includes incorrect information. This feedback is essential for improving how you use AI and for ensuring the quality of its output.
What to prepare for your checks
Before you start checking, you need to know what you are looking for. Define clear criteria for what makes a good result. For example, if you are asking the AI to write marketing text, decide what tone, length, and key messages you expect. If you are using AI to find patterns in documents, know what kind of patterns are relevant to you. Having these criteria ready makes your checking process objective and efficient. You might also prepare a small sample of known good answers to compare against the AI's output. This gives you a benchmark for quality.
How to set up your checks
Setting up effective checks involves a few steps. First, decide who or what will do the checking. This could be another person, a different AI tool, or a set of rules you apply manually. The checker should look for obvious errors, subtle inaccuracies and omissions. For example, if the AI generates a list of facts, the checker could cross-reference those facts with a reliable source. If the AI writes a report, the checker could check for logical flow and consistency. Consider using a structured checklist to make sure all important aspects are covered. This helps ensure that every piece of AI output gets the same level of scrutiny.
How to check the result
When checking the AI's output, compare it directly against your defined criteria. Do not just skim the results. For example, if you asked the AI to extract specific data points from a document, manually verify each data point. If the AI produced a translation, compare it to the original text to ensure accuracy and nuance. Pay attention to details that might seem minor, as these can sometimes indicate larger issues. It can also be helpful to have a second person review the checks, especially for critical tasks. This adds another layer of independent verification of AI output.
What if there are problems?
If your independent check finds problems with the AI's output, use the feedback to improve how you use the AI. This is a learning opportunity. For example, you might need to refine your prompts, provide more context to the AI, or break down complex tasks into smaller steps. Document the types of errors you find and how you adjust your approach. This helps you build a better understanding of the AI's strengths and limitations. Remember, the goal is not to get perfect results every time, but to continuously improve the quality and reliability of the AI's work. You can also learn more about how to handle varied AI responses by reading about why averaged AI answers can hide what you see when asking AI for multiple perspectives.
Keeping control of AI's work
Maintaining control over AI's work means actively managing its use and verifying its output. It supports human judgment. Regularly review your checking processes and adjust them as your needs or the AI tools evolve. Do not treat AI as a 'set and forget' solution. Instead, view it as a powerful assistant that requires supervision and guidance. By keeping human oversight at every stage, you ensure that the AI's work aligns with your goals and standards. This ongoing engagement is key to getting the most out of AI while managing its risks. You can also explore how AI can help you find patterns in documents by reading our post on using AI to find patterns in documents.
Next steps for your checks
Start by identifying one task where you currently use AI and set up a simple independent check for it. Define your criteria, perform the check, and learn from the results. Gradually apply this approach to more complex tasks, refining your methods as you go. This systematic approach will help you build confidence in the AI's output and ensure its reliability.
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Easy Read version
Why check AI work?
It is important to check what AI tools make.
Someone else should check the work, not the AI.
This is like a builder making a house.
The builder should not check their own work.
An independent person should check the house.
They can find problems the builder might miss.
AI tools can make mistakes.
Having a separate check helps find these mistakes.
Checks must be able to find problems
A good check finds problems.
If your check always says the AI work is good, it is not helpful.
A check should find errors or things that are missing.
If a check cannot find problems, it is not strong enough.
For example, if AI summarises a document.
Your check should find if the summary misses important parts.
Or if it has wrong information.
This helps you use AI better.
It makes sure the AI work is good.
What to get ready for checks
First, know what you are looking for.
Decide what makes a good result.
For example, if AI writes marketing words.
Decide what style, length, and main ideas you want.
If you use AI to find patterns in documents.
Know what patterns are important to you.
Having these rules ready makes checking fair and quick.
You can also have some good answers ready.
Compare the AI's work to these good answers.
This shows you what good quality looks like.
How to set up your checks
Setting up good checks has a few steps.
First, decide who or what will do the checking.
It could be another person or a different AI tool.
Or you can use your own rules.
The checker should look for clear mistakes.
They should also look for small errors or things that are missing.
For example, if AI gives you a list of facts.
The checker can check these facts with a trusted source.
If AI writes a report, the checker can check if it makes sense.
Use a checklist to make sure you check everything important.
This helps make sure all AI work is checked the same way.
How to check the result
When you check AI work, compare it to your rules.
Do not just quickly look at it.
For example, if AI took out specific information from a document.
Check each piece of information yourself.
If AI translated text, compare it to the original text.
Make sure it is correct and has the right meaning.
Look at small details.
Sometimes small details show bigger problems.
It can help to have a second person check your checks.
This is very important for big tasks.
It adds another check of the AI's work.
What if there are problems?
If your check finds problems with the AI's work.
Learn from them to use the AI better.
This is a chance to learn.
For example, you might need to ask the AI in a better way.
Or give the AI more information.
Or break big tasks into smaller parts.
Write down the types of mistakes you find.
Write down how you change what you do.
This helps you understand what the AI is good at and what it is not.
Remember, the goal is not perfect results every time.
It is to keep making the AI's work better and more reliable.
If you find mistakes, learn from them.
Keeping control of AI's work
Keeping control of AI work means managing how you use it.
It means checking what it makes.
It supports human judgment.
Look at your checking steps often.
Change them as your needs change or as AI tools change.
Do not just set up AI and forget about it.
Think of AI as a helpful assistant.
It needs you to watch it and guide it.
By keeping people in charge at every step.
You make sure the AI's work matches your goals.
This ongoing work helps you get the most from AI.
It also helps you manage any risks.
Next steps for your checks
Pick one task where you use AI now.
Set up a simple independent check for it.
Decide your rules, do the check, and learn from what happens.
Then, use this way of checking for bigger tasks.
Make your methods better as you go.
This step-by-step way will help you trust the AI's work.
It will make sure the AI's work is reliable.
aXai makes accessible AI tools and software.
Read about custom accessibility work.
aXai is a company led by people with disability.
Skilled people with disability do the work.
They have real jobs with proper pay.
AI removes the barriers.