Artificial intelligence (AI) and Human Computer Interaction (HCI) share common roots: early work on conversational agents has laid the foundation for both fields. However, economic and political influences have driven these fields to remain separate in subsequent decades. The recent rise of data-centric methods in machine learning has propelled few-shot emergent AI capabilities, resulting in a raft of practical tools. In particular, modern AI techniques now power new ways for machines and humans to interact. Recently, a wave of HCI tasks have been proposed to the machine learning community, which direct AI research by contributing new datasets and benchmarks, and challenging existing modeling techniques, learning methodologies, and evaluation protocols. This workshop offers a forum for researchers to discuss these new research directions, identifying important challenges, showcasing new computational and scientific ideas that can be applied, sharing datasets/tools that are already available, or proposing those that should be further developed.