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Traditional psychological experiments have been performed at small scale: with relatively few participants, reporting on relatively restricted sets of conditions, designed to adjudicate a small number of situation-specific hypotheses. However a confluence of important developments -- from the replication crisis, to the advent of online experimental platforms, to the flowering of modern artificial intelligence -- has made it increasingly evident that psychological science can (and probably should) be done at a larger scale, and in a more systematic fashion, than ever before. In this seminar, we will discuss the meaning and purpose of scale, as it pertains not only to experiment size, but also ecological realness and validity of stimuli and conditions, and the richness of measurement instruments. We will survey recent works of "psychology at scale" from a wide variety of domains, including perception, memory, decision making, language, and social interaction. We will also discuss and develop design principles and best practices for modern psychological experiments ? principles that enable both learning from, and contributing back to, psychology-adjacent areas such as artificial intelligence, neuroscience, and statistical science.