ABSTRACT
Artificial intelligence (AI), or more precisely, machine learning models, learn from the data they are given. AI and augmented intelligence systems are both built on technologies such as machine learning, natural language processing, and predictive analytics. Douglas Engelbart’s idea of “augmentation” gave the name “augmented intelligence” to the “symbiotic relationship” between man and machine previously described by J. C. R. Licklider. Implementing an augmented intelligence strategy must incorporate a combination of efforts. One of the benefits of augmented intelligence is that it becomes a tool to assist humans in gaining better insights and understanding of complex data. The value of augmented intelligence is that it can help individuals overcome human limitations. Machines can provide guidance to a human decision maker based on an analysis of large volumes of relevant data. Human governance and controls are needed to guard against algorithmic bias in the machine intelligence resume-matching algorithm.
