Building AI Applications requires a lot of data and a lot of work. Understandably, those who provide this data feel that it is a form of IP. Yes, it is. It contains a person or a company’s understanding of quality and other important aspects – which is related to its competitive advantage.

Why do we have Quality Standards?

Quality standards evolved through common understanding to facilitate trade. Trade can only be based on notions of quality if it is shared – between buyers and sellers. Standards are generally shared – so there is no real IP around standards. But the interpretations of standards differ, and this is where – there is some special knowledge that is particular to each buyer or seller.

Do you ahve a chance against AI Assessment?

Think about this seriously. We are now taking baby steps in matching existing standards – and are not quite there yet. While bodies that maintain standards may have samples in the hundreds – we will ahve it in the thousands. Not only that, we will be able to map the different ways in which different people interpret those standards. Eventually AI will be more knowledgeable about the standards than any QC person – but it will be able to differentiate how different QC people interpret those standards. AI Apps will have the capacity QC the QC people.

The choice of whether to share or not is yours,

We certainly have services (at a higher cost and price) that will respect your data and details of how you classify what you classify. As a platform company, it is of extreme importance for us to maintain confidentially around data.

But if your data is shared to build more accurate engines – which is the common proactive, you will benefit from higher accuracy. The accuracy of AI apps depends on the amount of data and the clarity with which it has been segmented into various categories. So if you do not wish to use exteranious data – your AI app will be less accurate, and you will pay more for it.

The choice is yours – make it wisely.