Processing Unlabeled Data in Machine Learning

When I talk about human labeling tasks, I am referring to business processes where humans are completing a SL problem. This can be content moderation on images in media companies (e.g., deciding between "safe for publishing" and "not safe for publishing"), routing incoming emails and documents through the organization ("department 1", "department 2", …), or extracting information from incoming PDF orders ("name", "IBAN", ...). With many of them, there is often a human-only process in place today, which could benefit from automation. Ideally, you don't try to shoot for a 1-to-1 replacement, but you start automating the obvious cases using algorithms and leave the rest to the human. At my company Luminovo, we have been thinking a lot about how to structure an ML system that truly lives up to the promise of continuous learning when used to automate a human-only SL process step-by-step.