The field of computational complexity and fairness is moving towards a deeper understanding of the interplay between randomized and pseudodeterministic communication protocols. Recent work has shown an exponential separation between these two models, highlighting the importance of pseudodeterminism in achieving efficient communication. Furthermore, researchers are exploring new approaches to fair division, including the allocation of indivisible items and the consideration of social impact. Notable papers in this area include 'Pseudodeterministic Communication Complexity', which exhibits a partial function with randomized communication complexity O(log n) but requires randomized communication complexity n^Ω(1) for any completion of this function into a total one. Another noteworthy paper is 'Fair Multi-agent Persuasion with Submodular Constraints', which presents a signaling policy that achieves a logarithmically approximate majorized policy in the setting of Bayesian persuasion with submodular constraints.