Suhani Thakur
Navrachana International School (NISV), Vadodara, Gujarat
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http://doi.org/10.37648/ijrst.v16i03.004
Data driven decision making has changed a lot over the years. In the past people used statistics to figure out things, test ideas and understand how things are related. Then machine learning came along. People started to focus on making good predictions handling large amounts of data and finding complicated patterns. Now Explainable Artificial Intelligence or XAI for short is trying to make machines more understandable to humans by explaining how they make decisions. This makes us wonder should we care about making good predictions or should we also think about being transparent dealing with uncertainty and being accountable for our decisions.
Keywords: Statistical Inference; Explainable AI Machine Learning; Data-Driven Decision-Making; Interpretability; SHAP; Predictive Analytics; Artificial Intelligence; Transparency Uncertainty
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