EXPLAINABLE ARTIFICIAL INTELLIGENCE -THE MAGIC INSIDE THE BLACK BOX

As Artificial intelligence gets more widely adopted, the importance of having explainable models increases manifold. The human mind has relied on these systems to be responsible for making major decisions and now feels the need to be able to communicate what the decision is, how it was made and why did the AI do what it did. Artificial Intelligence technologies are already used to rank your search results or suggest videos to watch on YouTube or smart replies on email and so on. AI algorithms are used in security for facial recognition or behaviour analysis, in medicine to identify tumours, into financial lending to identify if you will be able to repay a loan if sanctioned. But creators of these algorithms are may get prejudiced or get fumbled up explaining how it works. AI often relies on skewed programme logic, poor data sources and even developer biases which mean that the systems can easily get into the maze of human prejudices.