Machine learning is one of the most advanced technologies in artificial intelligence. Find out, in an easy and immediate way, how it works and its potential uses in the HR world, the new frontier of machine learning.

Have you ever wondered how can your email program distinguish between spam and solicited email or how it is possible that the advertisements on your Facebook wall match with your interests? The technology at the base of both systems is the same: machine learning.

A very easy example to understand machine learning’s basis is to think about the science class in which you learnt to distinguish the classes of vertebrates. How did you learn to identify a mammal and differentiate it from amphibians and reptiles? First, your teacher gave you some examples saying that cats and dogs are mammals, while snakes are reptiles, frogs are amphibians, goldfish are fish and owls are birds. She or he explained that mammals have some shared features that may differentiate them from animals belonging to the other classes (e.g. the fur or the fact of being warm-blooded). At this point your teacher asked you “and the sharks, which class do they belong to?” and you had to compare the shark and its features to each animal the teacher showed you, in order to understand which was the most similar animal and to establish which class it belonged to.

The same learning and classification process occurs in machine learning, in which the identification of elements belonging to each category is based on input data managed by a supervisor. In order to classify new data, the system has to calculate the distance and similarity to the data previously given by the developer. Briefly, the machine elaborates the information given by the developer and “learns” how to identify new data, through a comparison to the older one. For example, when classifying spam, the system automatically elaborates e-mails, comparing the features of email previously classified as spam and as solicited email. Evaluating the similarity with the mails belonging to these two groups, it establishes which category new emails belong to.

This technology will be also applied to HR, allowing saving time and human energy and delegating more repetitive and boring tasks to artificial intelligence. Machine learning in the HR field will be used to analyze resumes and job ads, besides in career management.

Machine learning applied to recruitment and selection process is one of the most advanced innovations in talent acquisition, allowing meeting the necessities of job market, which is characterized by a constant need of updating. It is sufficient to think about job titles linked to IT and digital world: even a few years ago, they were scarcely developed and required, while now they are in fast expansion. Job titles and job skills are in constant evolution, implying the risk to have an obsolete system, unable to reflect changes in job supply and demand.

Arca24 is currently developing the application of machine learning to our semantic search engine, already implemented in our software Ngage (link) and Talentum (link). Skillskan allow to match the best talents to posted ads, confronting the words used in resumes and abilities expressed by applicants and required by job positions. Currently, the job skills our system can elaborate are around 13000, associated to almost 1500 job titles.

In spite of these high numbers, our determination to create an even more powerful and complete engine led to the decision to implement this revolutionary technology in our software. Thanks to supervised learning, the program will be able to classify new terms, not already included in our system, and independently “decide” to which job title they would be connected to, improving its precision and reliability. Moreover, it will be possible to automatically generate new job titles that will include the newest and most innovative jobs. So, the list will be constantly and automatically widen, making the identification of applicants’ job titles and skills even easier. The result? An engine for the calculation of compatibility between job ads and resumes even more powerful and in constant evolution, an essential tool for talent acquisition!

This technology will be implemented in our software Ngage and Talentum. The former includes ATS and CRM, meant for selection and temporary staffing agencies; the latter planned and created for the recruitment process of individual companies. Doing so, it will be possible for both categories to get a revolutionary and extremely technological engine, capable of adapt itself to the continuous evolution of job market.