Explainable AI (XAI) and its influence on Machine Learning


Artificial Intelligence saw wider acceptance with the adoption of Machine Learning. Machine Learning is a subset of Artificial Intelligence. Machine learning helps in analyzing a large amount of data into intelligent insights for applications like identification of fraud and weather forecasting. Machine Learning provides an understanding of organizations by analyzing and interpreting patterns and trends.

Machine Learning is a tool that has unlimited capabilities. But, despite having such potentials, confusions and questions arise in how the Machine Learning systems helps in decision making. Questions regarding the process used by Machine Learning and the speed of the process, how autonomous decisions are made, etc. often bother the reliability of Machine Learning models.

Explainable AI or XAI helps to increase the trust, clarity, and reliability of these applications. The XAI makes machine learning more transparent, intuitive, and provides information regarding predictions.   

Explainable AI also known as XAI, is a method or approach of artificial intelligence which is programmed to describe the goals of Artificial Intelligence, sense, and decision making in a way that is easily understood by an ordinary human user. The different users can be programmers, any person impacted by the Artificial Intelligence model decisions, or the end-users.

Explainable AI helps in removing the black box in AI algorithms, enhances the explainability, reduces the bias in information, and thus develops better outcomes or results for every user. Based on the research report of Science Direct, the AI model systems in the initial stage were easily understandable but afterward, Artificial Intelligence witnessed an emergence of complicated and less transparent decision systems like the Deep Neural Network or DNNs. The Deep Neural Network or DNN is a complicated black-box model and is less transparent.

The XAI or Explainable AI also focuses on the bias involved in Artificial Intelligence systems. Bias involved in Artificial Intelligence can cause many problems mainly in the process of recruitment, healthcare, etc.

Enterprises are ready to accept and adapt themselves to XAI tools because they have no other choice as there is a growing public interest in Artificial Intelligence and Machine learning. Therefore, multinational companies like Google and IBM various Explainable AI tools to help developers achieve more insights on Machine Learning models.


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