Algorithmic Decision Support

Algorithmic decision support (ADS) systems are increasingly used to augment human judgment in complex decision-making processes across various sectors. Current research emphasizes understanding how human biases and heuristics interact with ADS, particularly focusing on the impact of system design choices and the distribution of responsibility when algorithms make errors. A key focus is improving human-AI partnerships by aligning algorithmic outputs with human expertise and organizational goals, thereby enhancing the fairness, transparency, and accountability of these systems. This research is crucial for ensuring the ethical and effective implementation of ADS in high-stakes domains like criminal justice and child welfare.