How to choose a profession with the help of psychodiagnostics
In this article, you will learn how artificial intelligence helps you choose a profession to which you are predisposed. But first, subscribe to our Telegram channel. We often publish such valuable articles!
Choosing the right profession means being happy. It sounds simple, but not everyone knows what they want to do. Almost 25% of schoolchildren “Don't know who they will be and don't think they can understand it now.”
Choosing a profession is essential not only for young people. More than 30% of people over 45 plan to change their profession. And they think in what profession they would like to work in further. Many do not know where to start, and we have written a guide for such people. Find out what five myths prevent you from changing your tedious job.
If the profession combines “I want,” “must,” and “I can” (knowledge, abilities, health), you can find it with psychodiagnostics. You need to pass one or more psychological tests. They will show your psychological characteristics and predisposition to professions.
Psychodiagnostic tests are questionnaires, and the answers are “yes” and “no.” The answers show personality traits and character traits. The questionnaire is filled out on a computer, and the psychologist evaluates the results.
Until recently, the most popular personality questionnaires were the MMPI (Minnesota Multivariate Personality Inventory) and the Cattell Test. Now, these tests are practically not used.
The classic MMPI consists of over 500 questions and takes, on average, about an hour to complete. In addition, this test was created for diagnosing clinical abnormalities and not for professional selection. The Cattell test is not so difficult but is not suitable for testing people with high intelligence — such people easily calculate what kind of person they want to find for a vacant position and answer “as it should be.”
Some psychologists consider the MBTI (Myers-Briggs Type Indicator) the best test. This test has a relatively high predictive value. The MBTI recommends which area of activity a person will be successful in and where he may have difficulties.
Predictive psychodiagnostics is a forecast of the required metric based on the data of psychodiagnostic testing.
Combining classical psychodiagnostics with artificial intelligence gives a new level of career guidance. They combine psychological expertise and patterns formed from the data of thousands of completed questionnaires. The system instantly compares the test results with the results in the database.
Initial data for training artificial intelligence:
- the results of the psychodiagnostic test — the values of the scales and the calculated personality type;
- input data — the answers chosen by the person to the questions of the questionnaire;
- additional data — answers to questions that are not included in the methodology questionnaire, but contain additional information, for example, about the field of activity and position of a person.
The most exciting thing for us is that trained AI provides indicators and classification of a person according to indicators, not in the psychodiagnostic test itself.
For example, we can use AI to understand a person's predisposition to a specific profession or determine if he is satisfied with his position. Without asking the person about it on the forehead.
The results allow you to professionally orient a person or find the best candidate for a vacant position. You can identify unsuitable people in positions and much more.
The methodology is based on the synergy of objective data (scale values obtained from the basic psychodiagnostic methodology) and predictive assessment of other properties and qualities of a person using machine learning algorithms and teaching methods with a teacher.
The creation of models for a predictive psychodiagnostic system in the general case includes:
- definition of metrics calculated using machine learning;
- adding questions to the basic questionnaire, the answers to which clearly describe the selected metrics;
- collection of a sufficient amount of data for training the ML model (i.e., questionnaires filled out by respondents);
- model training.
The resulting model takes the answers of the tested person to the questions of the questionnaire, and the values of the scales are calculated according to the rules of the basic psychodiagnostic methodology.
The model produces a predictive estimate of the target metric at the output.
The choice of the basic methodology for psychodiagnostic testing should coincide with the subject area of the metrics determined using prediction to one degree or another.
For example, if it is necessary to predict performance in the field of people management, then using only methods for assessing intellectual abilities will not be enough since they do not contain data on emotional intelligence, which are essential for interpersonal interaction.
As a predictive metric, you can choose the potential satisfaction of a person when working in any professional field.
Potential Satisfaction (PS) describes a self-assessment of pleasure from a person's current job and a sense of professional fulfillment.
PU is a binary value, the value of which can be determined by the results of answers to 2 additional questions:
During your work day, do you more often:
- enjoy what you do;
- do the work without much enthusiasm.
If you would rather say:
- in my current profession, I realize my abilities;
- it would be easier for me to be realized in another field of activity.
If a person chooses the first answer in both cases, he is satisfied with the work and his field of activity. Any other combination of answers means that he is dissatisfied with the job.
Trained AI shows the stable statistical significance and makes predictions with at least 64% accuracy.
This allows you to calculate and visualize metrics that were not previously the subject of classical psychodiagnostics.
Depending on the metrics being analyzed, the number of available data models, and the format for outputting predictions, the architectures of the psychodiagnostic system change. These can be single models or their ensembles, decision trees, neural networks (read Networking with empathy: what is it, how, and why to build it), and other algorithms.
The model's features are answers to the questions of the questionnaire and the values of the psychodiagnostic technique. You can use combinations of responses and scale values. It depends on the algorithm and goals of the study.
Take the Menteora career guidance test; artificial intelligence will name your most suitable professions. The accuracy of the test is 70-80% because we use a mathematical-statistical algorithm (read about Menteora's unique career guidance methodology).