Modern Artificial Intelligence systems finding their space across enterprises and business websites


Modern Artificial Intelligence systems are finding their space across enterprises and business websites with applications starting from chatbots, predictive systems, intelligent Robotic Process Automation to facial recognition. The predictions made by Artificial Intelligence data models are helping many industries like healthcare, banking, and many other industries which are of strategic importance. Now everybody is looking into its applications that are future innovations like driver-less cars and war drones. The executives of companies across the world agree on this statement that Artificial Intelligence-based decisions can be trusted provided they can be explained.

Artificial Intelligence and Machine Learning are already converting a large amount of data into insights that are useful to businesses to be more productive and smarter. Now it’s time to look into the newly emerging field of machine learning, it is explainable Artificial Intelligence or XAI. XAI explains how decisions are made and also tells the steps involved in the process. It helps users to ensure the decisions derived are accountable and transparent too. Does it help to answer questions like why the Artificial Intelligence system makes a specific prediction? Why didn’t the Artificial Intelligence system do something else? When did the Artificial Intelligence system succeed and when did it fail?

Uses of XAI

XAI’s main applicability is on technology that impacts user’s lives especially requiring trust and reliability. These include the following:

  • Healthcare: XAI provides an explanation which is traceable to allow doctors and medical professionals to trust the outcome given by the AI model. Explainable Artificial Intelligence acts as a virtual assistant helping doctors to find diseases accurately.
  • Banking and finance sector: Banking and insurance are industries that are using these technologies highly. Recent reports state that many mistakes are there in reports given by AI models on customer background checks. So by using Explainable Artificial Intelligence more credibility can be given to AI models given for these types of tasks. Also KYC checks, customer service like tasks can be done by XAI with credibility and transparently.
  • Autonomous Vehicles: The importance that XAI having on autonomous vehicles is very high. This can be used to explain whether an accident is avoidable and also what measures can be taken to ensure the safety of both passengers and pedestrians.

So we can conclude that the XAI is all about improvement and increasing the trust in AI models to make correct decisions for its users.


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