UNAVAILABILITY OF EMOTIONS CAN NO LONGER BE A SYNTAX ERROR!

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Researches over the years have mainly focused on the astonishingly amazing capabilities that human minds have. Some part of the population was simply left awestruck while the other part of the population went ahead to bring about new changes in the field of machines and robotics using the qualities shown by human minds. Why do you think human minds have always been in the spotlight? It’s certainly because, that is the seat of all the simple and complex emotions human beings exhibit. The word emotion is a pretty common term but, do we really know what it scientifically means?
According to the American Psychological Association (APA), emotion is defined as a complex reaction pattern, involving experiential, behavioral and physiological elements. Emotions focus on how individuals deal with a matter to which they personally can find a connection. Well now the question arises, how is all this discussion at all relevant to artificial intelligence? Artificial intelligence as we use the term is a major part of cognitive science and that is exactly the field where one focuses while talking about the new advancements in the human mind.
Artificial intelligence (AI) in layman’s terms is simply machine intelligence. It is as simple as making a robot or a machine perform the exact similar tasks that humans can perform and also perform tasks which the later cannot. This ranges from interpretation of language or camera input through making medical diagnoses and constructing a completely imaginary virtual world that our eyes
are unable to capture daily. Can you somewhere relate this to the MRI machines in the clinical labs? Yes, that is the kind of artificial intelligence we find existing. But, don’t you think it would be a whole revelation in the field of science when mental health professionals will tell their patients, “Your robot therapist will see you now, Sir!” (as shown in picture above)
I am sure that the above quoted statement surely intrigued a lot of readers who are absolute youngsters like me. Well, not to get disheartened, by focusing on exactly what are the things we need to incorporate, we can make it happen for real. The first major component that we need to incorporate in a machine like that is emotions.
Just as said by Amit Ray, a famous AI Scientist and the author of Compassionate Artificial
Intelligence, “As more and more artificial intelligence is entering into the world, more and more emotional intelligence must enter into leadership.”
Can we not actually visualize the above picture as the next gen advancement? Margaret A. Boden in her book Mind as Machine specifies that it is truly possible as cognitive science in this case will use the abstract concepts drawn from artificial intelligence and work towards the control theory i.e. managing to control emotions and movements. Using cognitive science, we can develop an AI model of emotion keeping in mind to turn the drawbacks of AI when it comes to emotions into advantages.
Thus, as suggested in a research article by Rolf Pfeifer, the model can focus mainly on the ability of AI to trigger emotional processes. Emotion has to be viewed as a process if computer programming is the medium through which we would want to develop such a model. Triggering of emotions only happen when there is an influence or in simple words, a stimulus from the environment. This will only help to further exhibit overt behavior and of course, generation of suitable emotion for the situation. In the process, most of the theorists would also agree that emotions are goaloriented and to incorporate this into robots which are going to be an exact replica of humans, the model must have these goal structures of humans specified explicitly. We also know that emotions can be predicted. In scientific terminology, emotions have high heuristic value. This means that emotions have the ability to chalk out ways in which situations can be interpreted. To be able to incorporate this heuristic approach in AI robots too, the problem that has been persisting over the last 30 years need to be modified - the inability to represent knowledge from the environment by AI.

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