Automated Decision Making

Automated decision-making (ADM) systems are increasingly used across various sectors, aiming to improve efficiency and performance, but raising significant ethical and legal concerns. Current research focuses on ensuring fairness and transparency in these systems, particularly addressing biases amplified by feedback loops and the need for explainable models, often employing techniques like transformer-based language models and graph neural networks for knowledge representation and decision support. The overarching goal is to develop trustworthy and accountable ADM systems that mitigate risks of discrimination and promote equitable outcomes, impacting both the development of robust AI methodologies and the design of responsible governance frameworks.