A systematic review of benchmark performance in deep learning for video super-resolution and restoration

Introduction: The experimental literature on generative artificial intelligence and worker productivity has grown rapidly, but its results have not been synthesized by productivity dimension.Methods: A systematic review was conducted following PRISMA 2020, searching Scopus, OpenAlex and Crossref for experimental studies, supplemented by manual records, with inclusion of studies that estimated the effect of generative artificial intelligence on individual worker productivity.Results: Fourteen experimental studies were included.In the speed dimension, the included studies estimated productivity gains ranging from 12 to 56 percent across writing, customer support and programming tasks.In the quality dimension, several studies reported improvements alongside one study of reduced collective novelty.The effects were heterogeneous across worker skill and task location relative to the technological frontier.Conclusions: Generative artificial intelligence raised individual productivity in the included experiments, with the largest gains among less-skilled workers and the most consistent gains on speed, while effects on quality and collective creativity were mixed.