Pinaki Laskar on LinkedIn: #artificialintelligence #AItechnology #machinelearning

Today's AI is largely machine learning techniques, deep learning algorithms and deep neural networks can't identify causality, its elements and structures, processes and mechanisms, rules and relationships, data and models, all what makes our world. This leads to all sorts of decision and prediction errors, data and algorithmic biases, the lack of quality data, and implementation failings, or the absence of real machine intelligence and learning. Correlation-based ML; Predictions only; Limited explainability; Spirals out of control in novel situations; Minimal human-machine interaction; Constrained by historical data; No guarantees on fairness; Needs a lot of data; True AI will emerge as Causal AI, State-of-the-Art AI Causal AI True AI: Real AI Platform. Decision-making AI: Causal AI doesn't just predict the future, it shapes it. Explainable AI: Put the "cause" in "because" with next-generation explainable AI.