International Workshop on Forging Trust in Artificial Intelligence

Establishing and upholding trust in AI systems is an imperative pursuit as Machine Learning becomes intricately interwoven into our daily lives. The workshop, "Forging Trust in Artificial Intelligence" brings together a group of experts and researchers from diverse subfields, converging on the exploration of how transparency, fairness, privacy, and security collectively contribute to making machine learning trustworthy. By uniting experts across these pivotal disciplines, this workshop illuminates the best practices that not only enhance the trustworthiness of AI but also reinforce its ethical foundations. Ensuring trust in machine learning is necessary for unlocking its potential while minimizing risks. This is especially true in the current environment, where the constant expansion of data sources aligns with a growing interest in using them to develop comprehensive and universally applicable AI systems. This interest highlights the need to address issues related to transparency, fairness, privacy and security, particularly in the area of multimodal learning, where various data types and learners are combined to create sophisticated, but often opaque AI systems. Within this context, establishing best practices for data integration is essential to ensure transparency and interpretability of AI systems based on diverse learners. Fairness considerations, on the other hand, may involve identifying and addressing potential biases from different modalities. This includes exploring approaches to mitigate their impact and leveraging fair representation learning when integrating information from sources with varying bias levels. By addressing such issues alongside data privacy and security concerns, this workshop aims to contribute to the development of ethical, transparent, and secure AI that has a positive impact on our global society's well-being.