What Is Machine Learning?
Machine learning (ML) is the process of teaching algorithms to make decisions, based upon data. It encompasses a range of sub-domains like reinforcement learning and plays a crucial role in the discipline of data science.
Organizations use ML primarily to automate decisions that humans would otherwise perform. The major benefit of outsourcing decisions to ML is that it is quantifiable and enforced.
Humans are free to make their own decisions, which is both a blessing and a curse. It is problematic when different people make decisions based upon their own rules.
Take an application form, for example. If humans applied their own judgement then two different people would make two different application decisions. ML encodes the knowledge of all humans to make an unbiased, systematic, traceable assessment.
The downside of ML, however, is that it is hard to encode exceptions. Humans are quick to react to exceptional circumstances, but ML often struggles because it hasn’t observed enough of these states. In these cases human-in-the-loop approaches are beneficial.