- What is the psychological basis of Sentino analysis?
- How do you know that psychological data provided by Sentino are valid?
- What IT technologies is Sentino analysis based on? How does Sentino analyze the personality of individuals?
- What is Statistical Confidence Level?
- What is an API?
- What is Artificial Intelligence (AI)? And how does it differ from Machine Learning (ML)?
- Where can we find Machine Learning and Artificial Intelligence in our everyday life?
- What is Data Science? And how is it related to AI and ML?
- What is Natural Language Processing (NLP)?
1. What is the psychological basis of Sentino analysis?
Psychological basis of the Sentino solution is represented by the selected psychological personality tests like BIG 5, NEO, RIASEC, ORVIS, ORAIS, DISC, etc. These inventories are carefully chosen according to several basic criteria: scientific validity, relevance, and reliability; availability of vast open-source data constituted by answers of respondents from various groups to the questions of inventories; popularity of questionnaires and their widespread use by psychologists, HR specialists, academic community, consultants, and people interested in self-understanding.
2. How do you know that psychological data provided by Sentino are valid?
The psychological data underlying Sentino AI models are valid since we exclusively use scientifically proven reliable psychological scales. In terms of psychometrics, we use generally accepted standard procedures that are not able to somehow introduce any invalidity. Some minor discrepancies may occur in the analysis course due to the following fact that AI always searches its databases looking for the psychologically significant fragment that most closely matches the text fragment under analysis. It may be difficult to find if the analyzed text fragment is provided by a person with a low level of language proficiency or somebody who prefers long/complex/ambiguous phrases. However, this problem can be solved via continuous research and training of models. And we are constantly working on its resolution.
3. What IT technologies is Sentino analysis based on? How does Sentino analyze the personality of individuals?
The Sentino solution comprises AI / ML / NLP technologies. Our development team has integrated vast psychological data and built a natural language interface for it. We have trained our models using the state-of-art NLP stack (e.g. Spacy, Transformers) that is able to transform any structured or unstructured natural text (self-descriptions, CVs, answers to questions, LinkedIn profiles, social media posts, messages, etc.) into psychologically meaningful representation and link it to validated inventories (please see FAQ No. 5 below). We continuously keep researching and updating the models, striving for higher accuracy and better match with the customers’ needs.
4. What is Statistical Confidence Level?
The statistical coefficient of reliability is always calculated for each numerical value or result provided by Sentino Personality AI. It shows the reliability of the correspondent result within the range from 0 to 1.
5. What is an API?
An application programming interface (API) is a way for two or more computer programs to communicate with each other. It is a type of software interface, which facilitates the use of functions of one application within another. In contrast to a user interface, which connects a computer to a person, an API connects pieces of software to each other. It is not intended to be used directly by a person (the end user) other than a computer programmer who is incorporating it into the software. APIs help developers to expand the functionality of their products and connect them with others.
6. What is Artificial Intelligence (AI)? And how does it differ from Machine Learning (ML)?
Artificial Intelligence is the broader concept of endowing machines. Machine Learning is a subfield of AI. It can be seen as a way to implement decision-making in AI and getting computers to learn. A subset of Machine Learning and the most effective of all the machine learning algorithms is deep learning.
7. Where can we find Machine Learning and Artificial Intelligence in our everyday life?
There are many examples of AI and ML at work in our world today, that touch our everyday lives, but some people aren’t even aware of it. For example, every time you do a web search, when Netflix recommends a movie, when Facebook selects posts, when Amazon recommends a book, it’s Machine Learning that’s behind. Other more complex applications of ML or AI exist in domains like robotics, vision, and natural language processing, medicine, oceanography, and social science.
8. What is Data Science? And how is it related to AI and ML?
Data Science is an interdisciplinary field of scientific methods, processes, and systems intended for extraction of knowledge or insights from data in various forms, both structured and unstructured. It is similar to data mining and includes data cleansing, preparation, and analysis. Data scientists gather data from multiple sources and apply machine learning and predictive analytics to extract critical information from the collected data sets. The objective is to understand data and to provide accurate predictions and insights that can be used to power critical business decisions.
9. What is Natural Language Processing (NLP)?
The term “Natural Language Processing” refers to the branch of computer science – and more specifically, the branch of Artificial Intelligence – concerned with giving computers the ability to understand and respond to text or voice data in much the same way that humans do.