Trustworthiness is a critical issue in artificial intelligence (AI), especially for real-world applications. It is impossible to deloy AI in the real world without its being trustworthy. However, the connotation and extension of AI trustworthiness are not entirely clear. There has not been a single definition that is accepted by all researchers. Nevertheless, the vast majority of researchers agree that AI trustworthiness should include at least accuracy, reliability, robustness, safety, security, privacy, fairness, transparency, controllability, maintainability, etc. This talk starts from a brief recall of trustworthy systems in the literature. It tries to understand any potential difference between classical trustworthy systems and modern-day trustworthy AI. It argues that AI ethics is a crucial part of trustworthy AI, which was not featured in classical trustworthy systems. The talk then presents a short summary of AI ethics, and dives a little deeper into the fairness and explainability issues of machine learning models. It demonstrates that many aspects of AI ethics, such as fairness and explainability, are inherently multi-dimensional, which cannot be defined completely and accurately by any single metrics. Multi-objective thinking is essential in AI ethics. While a weighted sum approach can convert a multi-objective problem into a single objective one, this talk offers an alternative and illustrates how multi-objective evolutionary learning can be used to enhance fairness and explainability of machine learning models.

Artificial intelligence is reshaping how we explore ideas, understand information, and make decisions. This talk examines how AI language models are transforming research and data analysis—accelerating insight discovery, lowering barriers to working with complex information, and expanding access to knowledge across disciplines and backgrounds. We shall reflect on how this shift is opening new possibilities in learning, creativity, and collaboration, while also considering the challenges, limitations, and responsibilities that accompany the growing use of AI. Whether you are a researcher, professional, educator, or lifelong learner, this session hopes to offer a fresh perspective on the evolving role of AI in how we learn, think, and discover.