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The unprecedented amount of data being collected and the rapid advances in Artificial Intelligence (AI) have sparked a new wave of research into Intelligence Augmentation — developing AI systems to augment human capabilities for complex problem-solving. AI can be a valuable aid in areas where human cognitive abilities are limited, and human involvement remains crucial for adapting AI to dynamic and complex situations. However, this human-AI teaming presents a host of new challenges regarding trust, ethical integrity, and mutual understanding, especially in high-stakes or in-the-wild contexts.

In this talk, I will first present several typical scenarios where human-AI teaming is essential and discuss how visual analytics can offer significant assistance. Then I will specially focus on the Sintel (Signal Intelligence) system, a visualization-empowered human-AI teaming system, for time series data analytics. My primary focus will be on the task of detecting anomalies in time series data, based on the motivating scenario of large device (e.g., satellites) health monitoring.