The significance of AI technology has taken the world by storm. Nowadays, people are amazed by the capability of ChatGPT, a language model that can give human-like responses to a wide range of prompts and questions. As a result, AI technology has become one of the main tools that can move businesses forward, and organizations are beginning to eye various AI models for implementation. At its core, an AI model is complex. Depending on its objective, an AI model combines multiple techniques, such as machine learning, deep learning, data science, and artificial neural networks. While the outcome of AI model adoption is proven fruitful, it increases the importance of understanding this complex model, thus leading to the rise of Explainable AI.
Explainable AI or in short XAI is a set of tools and frameworks used to explain the prediction, decision and recommended made by an AI model. Also known as Interpretable AI, or Explainable Machine Learning (XML), Explainable AI refers to the ability of an AI model to provide an explanation for its output, which is understandable to human users. whether in the form of text, visualisation or any means of communication.
The effort to achieve highly effective and accurate results in decision-making has increased the complexity of AI models, which has raised questions about how these models arrive at solutions. While AI models are useful for making intuitive and effective decisions, it is crucial to understand the decision-making process. Decision-makers need to know why a particular decision is better than others, what factors contribute to success or failure, and whether the decision is trustworthy, among other things.
The rise of Explainable AI makes AI models simpler to understand, making it easier for stakeholders to accept and trust the decisions made by the models. Explainable AI enables decision-makers to correct and improve the AI model’s output as it offers a framework for identifying and correcting any biases or errors in the models. Furthermore, the dependence on AI models is becoming prevalent as they are proven essential in enhancing growth in organizations. However, AI bias can cause AI models to be unreliable, making Explainable AI an important tool to solve this problem by providing a clear and dependable AI model.
In conclusion, AI technology has changed the way businesses operate by providing intuitive and effective decision-making tools. Nevertheless, the complexity of AI models has brought about questions regarding their decision-making processes. The rise of Explainable AI has become increasingly important, as it allows AI models to provide clear explanations of their outputs in a way that is understandable to human users. Explainable AI makes it easier for decision-makers to accept and trust the decisions made by AI models as well as allows them to identify and correct any biases or errors in the models. As the use of AI models continues to expand, the importance of Explainable AI will become increasingly critical in ensuring that these models are trustworthy and reliable decision-making tools.
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