Will the future of AI will be with Cognitive Science?

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Cognitive science is an attempt to resolve how the mind functions and the nature of data it acquires, processes, and stores. In simple terms, it is the study of the human mind. It builds its foundation by taking concepts from different disciplines like psychology, AI (Artificial Intelligence), education, neuroscience, etc. This makes it interdisciplinary in nature and heavily reliant on research. 

Today we have human-regulated automatic systems like the flight management system (FMS) for pilots, and we are moving towards more and more autonomous systems that we call self-organized. From regulation to autonomy, the thought has always been to reduce human activity, based on the assumption that human beings are not entirely predictable or reliable. But at the level of internet services, human intervention is still substantial like for search engines and especially for email. Based on the idea of cognitive cost, in other words, the propensity of the brain to reduce its energy consumption, the ideal would be for all technological innovation to be designed to reduce this cognitive cost. A practical case of taking the user benefit into account would be, for example, to show the nearest service station to car drivers only when their car’s tank is nearly empty. This isn’t the case. Today, there is no real involvement in human cognition.

 Understanding cognitive effects to make calculable models enables us to design systems that are cognitive themselves, that simplify our lives, making certain tasks easier, and even increasing our abilities. 

As AI drenches itself into a variety of professions and aspects, the utilization of cognitive science turns out to be critical. Here are a couple of examples that exhibit why Cognitive Science is significant for AI:

1. The study of the mind is an invaluable resource for almost every company, especially education, psychology, and research. Educational companies embrace innovation to train better and they could utilize AI adequately if it understands the needs of the students better.

2. Engineering and medicine tools and devices need to be better equipped to gauge the coping of the human brain and simplify it for them. For example, automated cars need to be designed in a way humans can understand how to work them. 

 3. Human resources can use cognitive science to better productivity levels in individuals and grow them to the best of their potential. Any field that interacts with humans will need to have an understanding of the mental and emotional processes in human beings.

4. Banking professionals providing automated financing services would also need to have a great understanding of the human mind and how to appeal to them. The tools powered by AI offered by them need to be easy for people to use.

5. Personalized features in the usability of Apps need to ask the right questions to understand customer preferences and how to provide it to them. 

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