Building Data-Intensive Systems that Care

Computer science has been about automating everything including data science pipelines. Data science and humans do not optimize for the same "objective function". Many of us have been claiming that we build human-centric systems. But are we? and if we are, are we doing it properly? This talk will attempt to answer this question at various stages of the data science pipeline, illustrating the essential roles that humans take along the way, as data labelers, as domain experts, and as end-users, and providing recommendations for building data-intensive systems that truly care.