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Do These 6 Things Before Releasing Your AI Software to the Public





Before listing your AI software in the GCP marketplace, or another similar cloud marketplace, you need to do several things. This list of six is not all-inclusive but covers the basics that most companies should consider before releasing their AI software to the public.

1. Test your AI software on a small group of people to make sure it’s working properly

Find some beta testers to test out your AI software before you release it to the public. This will give you an opportunity to fix any kinks in your system and make sure that it’s working properly before hitting the big time.

2. Make sure that there is no bias in the data used for training

When training your AI software, be careful not to use biased data due to outdated stereotypes, covert or not-so-covert racism, sexism, and other biases. This can lead to problems later on when your AI ends up reinforcing these stereotypes due to the data it was initially trained with. One way this has been done is by having a human also select and tag data that they think will end up being useful for the software.

3. Be clear about what your AI can and cannot do

It is important to be clear about the limits of your AI when you are marketing it to customers. Your customer should know exactly what they’re getting into when they buy your product, so make sure that you advertise it accurately – if it does X but not Y, say so.

Be clear about what is required to use your AI, and what it will do.

4. Educate customers on how they will be affected by the software

This point is important because if you don’t educate the customer about how the AI will affect them, you might not get their business.

For example, an insurance company using AI software to help determine car insurance premiums might want to note that the assessment will be done by a computer instead of an actual person because people are biased – they might discriminate against certain groups, like races or genders.

With this, customers can decide if it affects them positively or negatively.

5. Have a plan for when things go wrong with your AI, like if it starts behaving unexpectedly or makes mistakes

When things go wrong with your AI, you need to have a backup plan in place. For example, if it starts acting strangely, what can you do about it? Can software be used to shut the system down if necessary? If so, how? What are its limits? The more information you provide about your AI, the better.

6. Have an emergency manual override available so you can shut down your system if necessary

When things go wrong with a computer program, they can go really wrong in a hurry. To avoid this from happening, have a way to shut down your system manually – maybe via software or by turning it off. Of course, your backup plan needs to be tested – if it’s never turned on, you’ll probably forget how to shut it down when the time comes.


Test out these six things before releasing your AI software to the public. Make sure that it works properly after being trained by non-biased data so that you know what its limits are when you’re marketing it to customers. Be clear about what is required, and what the AI can actually do. Also, have a plan in place for when your system starts acting up or makes mistakes; make sure that there’s an easy way to shut down your system if necessary.

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