Technologies, trends and theories:
knowledge at the cutting edge.
Our knowledge base contains information, interesting facts and selected articles on the latest trends and current developments on global labor markets and in the world of semantic technologies relating to human resources and recruitment, occupation (big) data and ontologies / knowledge graphs, job classifications, CV parsing, skills and job matching and much more.
Digitalization, automation and AI pose a great threat to today’s job market that requires constantly changing skills. However, some of the skills are not missing due to the evolution of technology, but rather due to a loss of attractiveness. This is especially the case for positions with an unusually high number of vacancies or such that remain vacant for a long time.
According to the Swiss Skills Shortage Index, “a skills shortage exists if there are more vacancies than job seekers in an occupation.” Last year, » Read more about: Is reskilling and upskilling the real cure for today’s skills shortage? »
Ontologies have been around in artificial intelligence (AI) research for the last 40 years. Just as trends come and go, ontologies too have had their ups and downs. Introduced in the 80s, ontologies became popular in the mid-90s. After machine learning (ML) came on the scene in 2000, the widespread opinion was that in the future every task performed with a computer (by means of AI and ML) could be solved with a smart algorithm. A lot of companies invested heavily in these algorithms hoping to have the next breakthrough in AI. » Read more about: JANZZ ontology – empowering your data and realizing smart applications »
Artificial intelligence (AI) is unquestionably a powerful tool. Its economic value is increasing tremendously and transforming numerous industries such as manufacturing, fintech, healthcare and automobile. Workers in finance and marketing have much success using AI technologies, whereas HR practitioners find it rather hard to integrate these into their daily practices.
Prasanna Tambe, Peter Cappelli and Valery Yakubovich state in their research: “there are systemic and structural differences for HR that do make it harder, » Read more about: The potential of AI in human resource management »
The segregation of people in the workplace according to their biological sex is partly due to different preferences and aptitude for specific occupations. Traditionally, jobs with the highest concentration of women are to be found in teaching, nursing and other care-related service work. The majority of male workers, conversely, holds blue-collar jobs, for instance in construction, equipment operation or repairing.
Furthermore, since occupation fields dominated by female workers have a lower compensation in comparison, » Read more about: Sex segregation in the workplace »
Over the past decade, thanks to the availability of large datasets and more advanced computing power, machine learning (ML), especially deep learning systems, have experienced a significant improvement. However, the dramatic success of ML has forced us to tolerate the process of Artificial Intelligence (AI) applications. Due to their increasingly more autonomous systems, current machines are unable to inform their users about their actions.
Nowadays, most AI technologies are made by private companies that make sure to keep their data processing a secret. » Read more about: JANZZ.technology offers explainable AI (XAI) »