Human Cognition and AI - 0 views
started by ai_ar_services on 08 Feb 22
started by ai_ar_services on 08 Feb 22
started by ai_ar_services on 08 Feb 22
started by ai_ar_services on 08 Feb 22
Human Cognition and AI
“Our intelligence is what makes us human, and AI is an extension of that quality”, Yann LeCun. Humans pride themselves on their intelligence and we know this purely from the fact that the biological name that we have given ourselves is homo sapiens, literally meaning, wise man. We staunchly believe that our species came to be the species leading development on this planet due to our superior intellect. Yet now we have finally created a foe worthy of attention, artificial intelligence, which based on human cognition has become so arithmetically and logically advanced that it can do a years’ worth of work often data scientists in a minute. The key to understanding this phenomenon of intellect we have created and aided in advancing it further is to understand the relation between our cognition and AI.
Human cognition and AI
The first step in understanding the connection between the two elements is important to define and understand each one individually. Computerized reasoning is a differing field in which specialists address an extensive variety of issues, utilize an assortment of techniques, and seek after a range of logical objectives. In essence, utilizes what is called an artificial neural net. Inspired by the human brain, where many neurons work together, a neural net creates layers upon layers of “neurons” through which the AI considers the data — and each layer provides a different interpretation. These interpretations work together to classify the data. Neural networks are exceptionally good at detecting images. Feed them enough data, they can tease out patterns and differences invisible to the human eye. This ability gets put to use in a variety of applications. Some are life and death — like an autonomous vehicle detecting a pedestrian or a diagnostic tool detecting cancer. No matter how advanced, a neural net is still brittle: when presented with something outside of its parameters, it will crash. A deep learning AI is often superior to a human in a specific, narrowly defined task. But because of its brittleness, when it fails, it fails spectacularly.
Human cognition, on the other hand, encompasses many aspects of intellectual functions and processes such as perception, attention, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning, and "computation". Cognition is not a unitary concept and various cognitive functions, or cognitive ‘domains’, responsible for the regulation of specific behaviors or actions have been identified. These functions are often convoluted and operate synergistically making it challenging to measure distinct cognitive processes. However, modern cognitive testing batteries such as CANTAB are able to tease apart distinct cognitive functions. These functions are namely, social cognition, Executive function, memory, attention, and psychomotor speed. Here social cognitive and executive parts of the brain aid in the process of thoughts and emotions while attention, memory, and motor cognition refer to a reaction to stimuli presented to the brain.
Simply from the observation of the definitions of the two, we can understand the majority of human cognition focuses on reaction and thought as compared to the currently analytical ‘brain’ attributed to AI. But on the other hand, we model most of AI’s deep learning neural networks on the portion of the brain responsible for logical cognition. This is what results in AI is only able to focus on narrow tasks as we have not yet managed to locate and understand how to model the understanding of consciousness and high order thinking. In conclusion, AI is more similar to us in regard to pure cognition as the black box of neural networks is directly obtained from the human model of basic reactionary thought, however, due to technological or philosophical conundrums, we still cannot or have not been able to identify and model our consciousness and multifunctionality to Artificially intelligent networks.