Psychology and Artificial Intelligence (AI) are closely related disciplines, although the organizational divisions that exist in research centers and professional practice sometimes make it difficult to integrate the two areas.
Many people are still amazed when they discover that I am a psychologist and also an AI specialist. It strikes them because they think they are two unrelated areas of knowledge. However, the reality is that they have a lot in common. In fact, in the psychology degree some basic AI concepts are always covered, normally in the courses about Psychology of Thought. Also in computer science, when studying courses related to Artificial Intelligence, there are usually references to theories of human cognition.
It is a pity that, even today, university studies, even postgraduate programs, have a very little multidisciplinary character. Luckily, areas such as Cognitive Neuroscience have an eminently integrative approach and, in general, research in cognitive science usually brings together experts from different areas, such as
- Artificial Intelligence.
- Philosophy of Mind.
Certainly, both AI and psychology have a common axis: understanding the processes that give rise to intelligent behavior. In the case of psychology, the study focuses on human beings and we talk about mental processes. In the case of AI, the study focuses on machines and we talk about information processing. However, it is no less true that there are also great differences. Let’s not kid ourselves, even though there are certain parallels or analogies, a human being has little to do with an Artificial Intelligence system.
In general, psychology focuses on three main axes of the person: cognition, emotion and behavior. From the point of view of “weak AI”, machines do not think, although they process information, they do not feel either, although they can identify emotions, and they have behavior, which is determined by the output of their algorithms.
We could say that psychology deals with biological organisms (usually the human species), while AI deals with artificial cognitive systems. But deep down, both types of minds face the same essential challenge: adapting to the environment and solving problems efficiently even in situations of uncertainty, ambiguity, and noise. This capacity is what we commonly associate with intelligent beings.
Based on this analogy between intelligent biological and artificial systems, research in both disciplines is interrelated:
- Knowledge of the human mind can contribute to the design of more intelligent artificial system.
- The use of computational models can contribute to research on the functioning of the human mind.
In other words, the use of bio-inspiration in AI implies that the design of some artificial systems is based on the dynamics observed in the human cognitive system or other species. At the same time, hypotheses about how the human mind works can be tested, at least partially, using computational models based on Artificial Intelligence.
This parallelism between “artificial minds” and “natural minds” is not the only link between the two disciplines. For example, from the point of view of the possible practical application of Artificial Intelligence in the area of psychology, there are multiple possibilities, such as, for example, some of the ones we already explored at Psicobōtica:
- Intelligent systems based on Machine Vision for:
- Emotions facial expression training.
- Detection of situations of risk to health.
- Intelligent systems based on Natural Language Understanding for:
- Early detection of psychological problems.
- Automatic detection of personality traits.
- Intelligent systems based on Voice Signal Processing for:
- Identification of mood and level of physiological activation.
- Detection of symptoms of anxiety and depression.
- Intelligent systems based on Pattern Recognition on sensor data for:
- Automatic detection of a person’s behavior.
- Automatic detection of falls, accidents or assaults.
This technology is applied in different areas of psychology such as talent management, education, psychotherapy, neuropsychology or prevention in mental health.