The term cognitive science defines the set of disciplines that have as their object of scientific and philosophical study the cognition of a thinking system, whether natural or artificial, and that although operating in different fields combine the results of their research in order to reach the ultimate understanding of cognitive functioning. That is, the set of mental faculties involved in the processes of acquisition, processing, storage and manipulation of information (attention, perception, learning, memory, thinking, etc.).
Among the disciplines included in the cognitive sciences it is possible to distinguish cognitive psychology, neurophysiology, cognitive neuroscience, artificial intelligence (AI), cognitive linguistics, philosophy of mind, as well as computer science (mainly involved in the formation of simulative models such as neural networks). However, cognitive science can also involve anthropology, genetics, ethology, economics (think game theory), the cognitive science of mathematics, and even art.
Cognitive science methodologies
The basic assumption from which the cognitive sciences started was that the human mind is an information processor, like a computer, and the research carried out in this area was intended to identify models of information processing experimentally reproducible, from which to infer general models of operation highly realistic.
In this perspective there is a wide range of research aimed at simulating in computational form the functioning of the mind, for example how to solve a problem starting from inferential processes. Newell and Simon (1972), in this perspective, devised the Human Problem Solving, according to which the information useful for the solution of a problem, after being retrieved from long-term memory, can be used for the solution of various sub-problems in which is decomposed the starting problem, so you get to a final state (state-meta) which is the solution or the goal pursued.
In those years researchers aimed to create machines capable of exhibiting reasoning skills similar to human ones thanks to specific programs designed to reproduce the different reasoning processes, we remember the one created by McCarthy and collaborators. Among the many programs created, we emphasize the program DENDRAL created by Ed Feigenbaum, Bruce Buchanam and Joshua Lederberg, capable, starting from the information derived from the molecular mass from a spectrometer, to reconstruct the structure of a molecule. Thus, this program was the first that relied on knowledge intensive, i.e., obvious experience in a given application scenario.
Subsequently, Searle (1992), highlights how the artificial intelligence programs used for computers, fail to highlight the specificity and intentionality of mental phenomena. There is, therefore, something missing that allows to identify the true nature of the human mind.
At this point comes the cognitive psychology able to explain what happens in the mind at the level of thoughts, reasoning, cognition and emotions. The most used method in cognitive psychology to understand what happens in the human mind is to perform laboratory experiments in which human subjects participate and can be studied under controlled conditions. Thanks to these experiments it was possible to observe in detail how a series of inferential and planning processes occur from empirical data. It became important to understand what exactly was going on in the human mind while performing a task. As a consequence, connectionism took over, that is the area in which we try to give an answer to behaviors starting from the assumption that the brain is made of neural networks.
Artificial intelligence and affective computing
Emotions, therefore, play a fundamental role in knowledge processes and the study of behavior. Emotional processes are a fundamental part to investigate when we talk about cognition and mental functioning. For this reason, in those years, in the field of artificial intelligence, the idea that human rational thought depended on emotional processing became more and more evident.
Rosalind Picard was the first to speak of Affective Computing or machines (computers) capable of recognizing, expressing and communicating emotions or moods.
Affective computing is the interaction between man and computer that occurs when an electronic device is able to detect and respond appropriately to emotions arising from an external human stimulus. A machine that shows this ability could be fundamental in extracting information inherent to different emotional aspects, such as facial expressions, posture, gestures, language, changes in body temperature, etc..
Affective computing can offer a wide range of benefits to be applied in many areas, including, for example, it could be highly useful during online therapies, a field increasingly used, because it would allow to have emotional cues that otherwise could not be accessible to the therapist if not through a real session. Therefore, through affective computing posture, gestures and facial expressions could be used, together with the interview, for a more accurate assessment of the patient’s psychological state.
Already in ancient Greece many philosophers, for example Plato and Aristotle, theorized about the mechanism of human cognition. The study of the human mind for a long time was the prerogative of philosophy, but in the nineteenth century, when experimental psychology was born, Wilhelm Wundt and his collaborators began to study the mind and its functions in a systematic way.
The advent of behaviorism in experimental psychology led to focus the attention of researchers on the relationship between observable stimuli and behavioral responses, totally eluding the central “invisible and intangible” content of the mind. In fact, in this period it was forbidden to talk, in the scientific field, about how the human mind works inside.
Cognitive science was born in the ’50s, when researchers from different disciplines began to develop theories about the functioning of the mind starting from complex representations, symbol processing and procedures of computation and calculation.
The historical and theoretical assumptions for the birth of cognitive science, however, can be identified in the test devised by Turing, in which the human mind was considered a system of information processing (Human Information Processing – HIP). From here was born all the research on artificial intelligence and computer science, which led to the creation of the first computer. John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon are also considered the first pioneers of cognitive science.
According to the HIP approach, the mind possesses mental representations similar to the procedures of computation, symbol processing and computations found in the computer. These mental representations are the rules, concepts, images, and memories that are used by the mind, as computational algorithms, to deal with different problems that arise.
Its organizational origins, however, occurred exactly in 1978, year in which in La Jolla (California) was held a conference organized by the Cognitive Science Society in which participated researchers psychologists, linguists, neuroscientists and philosophers, to be able to have a greater communication between different disciplines and get more complex and elaborated theories about mental functioning. Consequently, the journal Cognitive Science was born and from that moment on, more than ninety universities in North America, Europe, Asia and Australia established different courses in cognitive science.
At the same time, the intellectual landscape began to change radically, with the advent of George Miller and his studies on memory, because they began to talk explicitly about what happens in the human mind. According to Miller’s theory, the mind is able to process information thanks to short-term memory. It is able to contain a limited number of information, which according to Miller corresponds to 7 elements, a number that can increase or decrease by two units, depending on the limitations or biological characteristics that distinguish one person from another.
Therefore, in the scientific landscape the interest was shifting from the outside, from the stimulus-response relationship, to the inner workings of the mind. Even Noam Chomsky, rejected the behaviorist theory according to which language was a learned process, replacing it with the hypothesis that the understanding of language comes from innate mental abilities, developed and refined in the relationship with the environment.