The field of medical Artificial Intelligence (AI) is moving towards developing more explainable and reliable models, with a focus on evaluating the clinical reliability of Large Language Model generated clinical reasoning. Researchers are investigating prompting strategies to enhance the quality of clinical Chains-of-Thought (CoTs) and proposing frameworks to generate trustworthy data at scale. Meanwhile, machine learning is being applied to understand the progression of climate policy, with studies exploring the use of text representation methods and metadata features to predict policy adoption. Noteworthy papers in this area include: Reliability of Large Language Model Generated Clinical Reasoning in Assisted Reproductive Technology, which proposes a Dual Principles framework to generate trustworthy data. Machine Learning for Climate Policy, which highlights the potential of ML tools in supporting climate policy analysis and decision-making.