Trust in the Age of AI
We’ve written before about the virtuous cycle of AI.
Accurate systems attract traffic. They provide an incentive for the user not to try alternative methods to get their job done. So, a virtuous cycle picks up – accurate systems reward the user, driving more traffic to the AI system, which trains it better, in turn making the system more accurate.
How can we drive this accuracy? It’s easier than you think.
Our first suggestion is that you should use AI solutions designed for your business requirements, rather than going for the general-purpose AI products. What you need is a bespoke AI solution that can configure to your enterprise’s need better than any AI product. These solutions are specifically trained, making them more accurate. Further, responsible AI solution vendors deploy over your private cloud or on-premise infrastructure, ensuring that not a single byte of data leaves your secure firewall. More here.
In the same vein, you should work with vendors or system integrators that have already deployed successful AI solutions. Successful customer references are less common than expected today.
But solution accuracy is just one piece of the puzzle. Trust is a complex construct – built carefully over time, and fragile. Vendors in your pipeline must provide more than just an accurate system. Explainability and security concerns should be top of mind as well.
Some AI paradigms, like deep learning, don’t allow for explainability. This is what’s called black box AI. And still others take client sample data an use it to train their own engines. This is called transfer learning. At Coseer, we offer 100% explainability and keep all of your data behind your own firewall. Not a single byte ever leaves your system.
Setup a call with us to learn more.
