The Future of Psychology: Artificial Intelligence Applications
Every day, scientists continue to illuminate human psychology and find in-depth information. Human psychology is like an endless sea. As you dig deeper, you can find different and exciting details. No matter how much research is done, human psychology, an exciting research area full of unknowns waiting to be discovered, continues to inspire many fields with the details it contains. One of the fields it serves is artificial intelligence. The human mind, which is a guide for artificial intelligence, allows various studies in this field.
From this point of view, if we need to define psychology and artificial intelligence, Psychology is a science that examines the behavior, emotion, and thought structure of a living thing. On the other hand, Artificial intelligence is a system that tries to imitate human behavior, reasoning ability, and problem–solving skills.
In this respect, there is an adaptation from the natural to the artificial in artificial intelligence technologies. At this point, the better we analyze the natural, the better we can develop in the adaptation phase to the artificial. Understanding the structure and functioning of the human mind and observing their emotions and behaviors will be critical in transferring these outputs to the imitations of artificial intelligence.
The relationship between the mind and the brain is evident in all mind discussions, particularly in recent psychiatric and neuroscientific discourse. Cognitive science, and now brain processes, is busy understanding how behavior and cognition are interrelated. Cognitive neuroscience actively studies how humans, as active, thinking organisms, use their brains to achieve their goals and meet their needs in complex and variable environments.
The data they obtain provides an infrastructure for artificial intelligence technology. In this way, the level of ability to imitate with correct data begins to increase. In this case, what kind of contributions artificial intelligence systems can make in the diagnosis, prediction, and treatment stages of a psychological disorder will be at a detectable point.
At this point, what are the learning methods used in artificial intelligence?
- Supervised Learning: It creates a function for classification and regression by mapping between input values, labeled data, and output values.
- Unsupervised Learning predicts the unknown structure over unlabeled data, that is, the category the input values belong to.
- Reinforcement Learning: Based on behavioral psychology, it learns with the logic of reward-punishment.
At this point, if we look at the contributions of artificial intelligence to psychology with the determined learning paths;
A specialist with many years of clinical experience can see cases for each psychiatric disorder, and the data he can collect accordingly are limited to a certain extent. Artificial intelligence can provide severe convenience in facilitating the expert’s work here, as in many areas. Just as artificial intelligence in the chemical industry can help chemists work at the point of combination.
In addition, thanks to artificial intelligence, in the follow–up of the clients’ mood, data collection methods such as digital diaries and instant emotion–thought feedback systems are among the ways that will facilitate the work and ensure continuous monitoring. In addition, by modeling the process of the drugs used in the treatment process with correctly labeled data input, the machines can predict the appropriate medications by comparing the data on the subjective symptoms of that patient with the data of previous patients. In this way, rapid and accurate progress can be made.
Thanks to artificial intelligence technology, which allows us to gain convenience and speed in many other fields, psychology innovations continue to be achieved. This technology, which offers effective methods from digital recording systems to the correct labeling of drugs, from the diagnosis and treatment process to the systematic recording of data, serves to obtain more accurate results in a shorter time by analyzing the data, as in every sector company.
This case shows that artificial intelligence continues to establish itself and make a name for itself in many areas. In this way, it leads one step closer to the world of innovations. This process brings a different dimension to innovations by benefiting from digital transformation such as deep learning, machine learning, and the internet. Furthermore, it allows people to take time by offering faster, easier, and workload–reducing opportunities.
