Building an AI strategy needs to include explainability for complete visibility into machine-generated decisions.
Explainable AI ensures there’s a human present in the loop of the AI process, where the machine provides transparent and reliable explanations, and the human can correct the machine in cases where its decisions are wrong. The sooner such an AI strategy is explored, the sooner an organisation can start reaping AI’s incredible rewards.
There is a growing concern in the business community about the implications of artificial intelligence and its automated decision making. We know AI as a set of techniques that allow computer software to learn from old data, and make sense of new data in a way that resembles human intelligence.
As humans, we tend to hold machines to a higher bar than humans when we lend them control to perform tasks on our behalf. As machines start making decisions, whether someone gets a loan or not, or a patient has cancer - it becomes important for humans to know why and how these decisions are being made to be able to trust the machine. In all the talk around AI, it’s easy to forget that it’s a business tool like any other – only more holistic and powerful than most.
Thankfully, a new way of approaching AI and machine-decision making is quietly emerging.
Read the full article from Fiddler's CEO, Krishna Gade, on ITProportal