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Explainable AI and Human-Machine Interplays

Explainable AI and
Human-Machine Interplays

AI is everywhere in our daily lives, permeating a broad range of sectors including healthcare, education, manufacturing, law, engineering, and finance. The use of AI-enabled systems helps in making predictions and decisions that have profound effects on peoples’ lives and wellbeing.  Pressing questions arise, such as Why does an AI system make a specific prediction or decision? Why didn’t the AI system do something else? When did the AI system succeed and when did it fail? When does the AI system provide us with enough confidence in the decision that we can trust it, and how can the AI system correct errors that arise? Explainable AI aims to address how the black box decisions of AI systems are made, helping us to understand the steps and models involved in making decisions. We have an obligation to improve not just the power and accuracy of AI systems, but also their transparency, explainability, and interpretability. This will ensure that when an AI system makes a mistake in a real-life situation, we can identify its source and prevent future mistakes.