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Why AI Failed to Live Up to Its Potential During the Pandemic

Despite initial optimism that AI and machine learning systems could aid various aspects of the response to Covid-19, many did not work as successfully as anticipated. This article highlights potential reasons for underperformance of those systems, particularly those related to data. For example, machine learning tools used for outbreak detection and response to available Covid remedies did not do well in diagnosing Covid from data trained on various datasets or predicting outbreaks. Looking ahead, the authors focus on solving these challenges by merging datasets from multiple sources and clarifying international rules for data sharing.