PSYCHOLOGICAL AI

The personality of humans is expressed through their speech. Our aspiration is to better interpret their speech and understand their personality better. Therefore, we have developed an artificial intelligence, which is able to read between the lines.

Psychological AI identifies mood, motives as well as personality traits and provides reliable results.

These results are based on a comprehensible procedure which should be a given when analyzing the personality of people. For us it is the prerequisite for a trustful cooperation. We are aware of our responsibility and take it seriously.

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  • IDENTIFY IMPLICIT MOTIVES
  • VALIDATED WITH INDEPENDENT DATA
  • ACQUISITON FROM REAL SPEECH
  • NO BLACKBOX
  • LEADING IN THE INDENTIFICATION
CONSCIOUSLY NOTICING THE SUBCONSCIOUS
HOW IT WORKS
Psychological AI-Sprachanalyse-Funktion
WE MEASURE DIFFERENT PSYCHOLOGICAL TRAITS
The face gives us our physical appearance and individuality. We measure characteristics such as thinking style and dominance to better understand the speaker's personality.
The heart is often associated with emotions. We measure prevailing moods and emotions such as anger or disappointment.
The legs drive us forward. Implicit motives such as power, achievement and relationship, which we measure in language, move us in the same way.
CAPTURING PERSONALITY TRAITS WITH PSYCHOLOGICAL AI

Die Häufigkeit, mit der wir bestimmte Worte und Wortkombinationen benutzen, verrät etwas über die Persönlichkeit. Diesen Zusammenhang – den viele auch intuitiv vermuten würden – konnte in vielen wissenschaftlichen Studien gezeigt und repliziert werden. Bei der Entwicklung der 100 Worte Analyse wurden zahlreiche psychologische Studien berücksichtigt an denen Forscher aus verschiedenen Disziplinen beteiligt waren. Insbesondere der amerikanische Sozialpsychologe J. Pennebaker, trägt viel zum Verständnis des Zusammenhangs von Sprache und Persönlichkeit bei. Durch seine Arbeiten wissen wir, dass gerade die scheinbar unwichtigen Funktionsworte (z. B. Personalpronomen oder Artikel) am meisten über eine Person verraten. Funktionsworte sind satzlogische Elemente, die keinen Inhalt transportieren, sondern Inhaltsworte strukturieren und ihnen ein sprachliches Gerüst geben. Hier einige Beispiele, wie die sprachliche Struktur etwas über die Persönlichkeit von Menschen verrät. Wie Menschen denken – eher analytisch oder intuitiv – bildet sich in der Verwendung von Funktionsworten ab. So verwenden Menschen mit analytischen Denkstil vermehrt Funktionsworte, die der Sprache Genauigkeit geben wie z. B. Artikel oder Präpositionen. Diesen Zusammenhang entdeckten Forscher als sie Motivationsschreiben von Studenten untersuchten. Auch die Dominanz von Menschen lässt sich aus Sprache ableiten. Dazu wurde in mehreren Studien untersucht, wie dominante Personen im Vergleich zu anderen Mitgliedern einer Gruppe diskutieren. Schließlich gibt es auch einige Befunde, die auf einen Zusammenhang zwischen Depression und Sprache hinweisen. Wiederholt konnten Studien zeigen, dass das Personalpronomen „Ich“ häufiger von depressiven Menschen verwendet wird als von Menschen ohne Depression.

CAPTURING EMOTIONS WITH PSYCHOLOGICAL AI

The use of words can reveal something about a person’s current mood. Is the person currently sad, furious or happy? First, emotions can be separated into positive or negative. In addition, especially negative emotions can be separated further. The most relevant negative emotions are grief, anger and anxiety. Moods and emotions are expressed through so called content words.

CAPTURING IMPLICIT MOTIVES WITH PSYCHOLOGICAL AI
Humans are led by motives. To know, what drives us forward, is particularly important in the context of profession. But what even are motives? Motives are internal action stimuli. They induce people to think a certain way and to behave in a certain manner. They express an aspiration: “I would love to be…“ or “I wish I was…”. Generally, three different motives are differentiated which are the motives of power, status and leadership, the motives if achievement and advancement and the motif to have harmonious relationships to other people. These motives have been formulated by the social psychologist David McClelland and have been researched in psychology. For example: what impact do motives have in different areas of life? These motives, however, are no distributed evenly but developed differently within each person. For one person it might be more important to have good relationships to others while another person might pursuit admiration. Moreover, we do not consciously decide which motive we would rather develop more strongly. They develop from our upbringing, our social surrounding and from experiences which we have made. Most of the time we are even not able to tell which motives actually drives us forward. Such unconscious motives are called implicit. Implicit motives have so far been measured with projective procedures where people are presented with picture containing ambiguous content. They then have to invent stories for each picture. The implicit motives of the story teller have an impact on the story they choose to invent. This means, that people project their unconscious motives onto the neutral situation. Long-term studies have shown that this procedure gives information about success factors for career such as salary. This procedure, however, is very time-consuming and complex because the content has to assessed by experts. Thanks to 100 Worte and its automatic analysis, this assessment is no longer needed. And we do not only claim this, but we are able to prove prognostic validity in external as well as own studies.
AUTOMATIC CAPTURING AND PROCESSING

The 100 Worte Psychological AI captures implicit motives like established successfully used procedures (e.g. Thematic apperception test, TAT). The steps of an analysis:

  1. The text which should be analyzed will be compared with our nine motif lexicons. Individual words signalize specific motives e.g. “passed” the performance motif.
  2. Before the actual word is counted, the context needs to be checked since it gives information about the exact meaning of the word. “Passed” in the context with “exam” has a totally different meaning than it has in the context of “departure”. We only count words when they have the suitable meaning.
  3. Finally, if the regarding word is negated will also be checked for since it then will also have a different meaning and has to be rated differently. We therefore look if the regarding word is part of a negation (e.g. “not”).

Thanks to this technology we are leading in the recognition of implicit motives from speech.

HOW WE USE MACHINE LEARNING
SIMULATING HUMAN TEXT UNDERSTANDING
An easy task:
Does the word “conduct"have the same meaning in the following sentences?
Gold conducts electricity better than wood.
He conducts research on second language acquisition in adults.
 
Presumably, you give these words different meanings since you can understand the context in which they are given. But, a machine interprets these words always as the word “conduct”- We have the knowledge of different word meanings and use it daily without thinking about it. A machine has to attain this context knowledge. In order to give the machine this knowledge we use diverse techniques of text processing and text comprehension. These processes are summarized under the term Natural Language Processing (NLP).
ACCOMPLISHING MACHANICAL COMPREHENSION (TWO EXAMPLES)

Part-Of-Speech Tagging (POS) is the allocation of words and punctuation characters of a text into word classes such as adjectives or verbs. We use this technology in order to, for example, differentiate between the following sentences:

He attributes his success to lots of hard work. ("attributes" = VERB)
Our research has identified certain attributesof successful open source projects. ("attributes" = Plural NOUN)

ELMo:

Embedded-Language-Models (ELMo) give words a vector which also takes the context into account. We use ELMo when words with different meaning cannot be differentiated by their word class.

The right brain perspective dominates his consciousness.
Both parties can benfit from the right working relationship.

Publications and Whitepapers
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