The dazzling promises of AI systems to augment humans in various tasks hinge on whether humans can appropriately rely on them. Recent research has shown that appropriate reliance is the key to achieving complementary team performance in AI-assisted decision making. Accurately estimating the trustworthiness of AI advice at the instance level is quite challenging, especially in the absence of performance feedback about the AI system. Moreover, the performance disparity of underlying machine learning models on out-of-distribution data makes the dataset-specific performance feedback unreliable in human-AI collaboration. Through a series of empirical studies operationalising real-world decision making contexts, we systematically explored the role of explanations, cognitive biases, critical mindsets, and users' affinity to technology in shaping their reliance on AI systems and the overall task outcomes.
In a talk held on 24 March 2023 at RMIT University, Assistant Professor Ujwal Gadiraju from Delft University of Technology shares novel insights into why *appropriate reliance* is a non-trivial objective.

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