Cracking the Code: Improving Psychodiagnostic Validity in Socionics

Everybody lies” (Dr. House).

The challenge of psychodiagnostics—the process of determining mental types within the Socionics models—shares fundamental issues with medical diagnostics and even a few additional ones.

First off, the survey method remains, unfortunately, the primary means of gathering information in Socionics, despite being one of the most unreliable sources. This makes the validity of the initial data rather questionable.

The format of these questionnaires involves two main aspects: the questions themselves and the respondent's answers. Today, I'll focus on the first part and cover the second in a future post.

Questionnaire questions, their structure, and their algorithms always have an author, even if it's AI. This means we encounter a known problem: the interaction between the subject and the system. The author belongs to a certain type and perceives the world through their own lens, the same Information Metabolism that Kempinski developed and Socionics uses.

Moreover, Socionics is conditionally linked to psychology. This means there aren't many specialists with university training and extensive field experience in survey-based work in this industry. In my opinion, we can improve the validity of questionnaire data in several ways:

1. Creating scenario-based questionnaires
2. Applying "weights" to questions in the data processing algorithm
3. Using questions to obtain objective data (e.g., age, gender)
4. Developing questionnaires with a team of specialists, including:
- Representatives of different types
- Professionals from various fields (at minimum, a sociologist, psychologist/socionist, and programmer) with a sociologist leading the team
5. Utilizing modern models for data processing

By addressing these aspects, we can enhance the reliability and effectiveness of psychodiagnostic tools in Socionics or rather in some new framework that has no name yet.