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.
From guessing to knowing with JANZZilms!: Academic overqualification is one of the main drivers of the intensifying global worker shortage.
/in Knowledge Base /by JANZZ.technologyMany countries worldwide, especially in emerging labor markets in Southeast Asia, Africa, and Latin America, are facing growing labor market challenges. More and more overqualified workers with academic backgrounds struggle to find work in their field. On the other hand, there is a shortage of skilled workers with technical or vocational backgrounds, leaving many jobs unfilled. Both are costly symptoms of an ever-increasing skills mismatch worldwide.
This trend is a result of several factors. » Read more about: From guessing to knowing with JANZZilms!: Academic overqualification is one of the main drivers of the intensifying global worker shortage. »
AI, automation, and the future of work – beyond the usual bubbles
/in Knowledge Base /by JANZZ.technologyIn recent years there have been many posts, articles, and reports on how AI and automation will shape the future of work. Depending on the author’s perspective or agenda, these pieces go one of two ways: either the new technology will destroy jobs and have devastating effects on the labor market, or it will create a better, brighter future for everyone by destroying only the boring jobs and generating better, much more interesting ones. » Read more about: AI, automation, and the future of work – beyond the usual bubbles »
The One-Eyed leading the Blind – Part 3: Farewell, Mythical Machine.
/in Knowledge Base /by JANZZ.technologyThis is the third in a series of posts on machine learning in HR tech. If you haven’t already, we recommend you read the other two posts first: part 1 and part 2.
In the last two posts, we discussed the need for domain experts in building a knowledge graph for a job matching engine as well as the problem we want to solve on a conceptual level. In this post, » Read more about: The One-Eyed leading the Blind – Part 3: Farewell, Mythical Machine. »
The One-Eyed Leading the Blind – Part 2: You can’t solve a problem you don’t understand.
/in Knowledge Base /by JANZZ.technology“If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem and five minutes thinking about solutions.” – Albert Einstein
This is the second in a series of posts on machine learning in HR tech. If you haven’t already, we recommend you read the first post here.
In our last post, we explained why it takes more than data science and machine learning (ML) to build a knowledge graph for a job matching system. » Read more about: The One-Eyed Leading the Blind – Part 2: You can’t solve a problem you don’t understand. »
The One-Eyed Leading the Blind – Why you need more than data science and machine learning to create knowledge from data
/in Knowledge Base /by JANZZ.technologyMany job matching and recommendation engines currently on the market are based on machine learning (ML) and promoted as revolutionizing HR tech. However, despite all the work put into improving models, approaches and data over the past decade, the results are still far from what users, developers and data scientists hope for. Yet, the consensus seems to be that if we just get more even more data and even better models, and throw even more time, » Read more about: The One-Eyed Leading the Blind – Why you need more than data science and machine learning to create knowledge from data »