The Future of Decision Making: Augmented Intelligence
Keywords:
Artificial Intelligence, Augmented Intelligence, Cognitive Model, Decision MakingAbstract
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.
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