The Future of Decision Making: Augmented Intelligence

Abstract

Artificial intelligence's protracted  objective seems to be to teach robots to learn and think like  humans. Due to the general tremendous degrees of  accuracy as well as fragility in human existence, as well as  the open-ended nature of the challenges that people face,  no despite how sophisticated robots are, they will never be  able to successfully wipe out the human race. Artificial  intelligence, with a significant computing information  processing capacity as well as an appropriate  methodology, could perhaps broaden humans' cognition  because once attempting to address complex nature, so  even though Homo sapiens can indeed could provide a  rather more holistic, interactive approaches to dealing to  uncertainty as well as interpretation of data in  organizational decision making. This assumption is similar  to the concept of intelligence amplification, which also  asserts that automated tools should have been built with  both the goal of supplementing, rather than substituting,  human contributions. As a result, in order to produce a new  type of artificial intelligence, hybrid-augmented  intelligence, it is important to include cognitive processing  model capacities or cognitive processing modelling  capabilities within artificial intelligence algorithms. This  type of artificial intelligence, often referred to as computer  intelligence, seems to be a viable as well as crucial  development paradigm. The two primary concepts of  hybrid-augmented intelligence are human-in-the-loop  information services featuring human-computer  cooperation as well as mental health counseling  technology based augmented intelligence, in which a  cognitive model is incorporated inside the recurrent neural  network.