Today, “artificial intelligence” seems to be everywhere — in our phones, vacuums, hospitals, and inboxes — but it can be hard to separate science fiction from science fact. Many discussions about AI imagine a fully autonomous superintelligence that designs itself with little to no human intervention, making decisions in ways that humans cannot possibly understand. Yet the work of designing, developing, engineering, training, and testing such systems requires a massive amount of human labor, which is typically erased when such systems are released as products. In this talk, Stuart Geiger gives a human-centered, behind-the-scenes introduction to machine learning, illustrating the creative, interpretive, and often messy work humans do to make autonomous agents work. Understanding the humanity behind artificial intelligence is important if we want to think constructively about issues of bias, fairness, accountability, and transparency in AI.