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.
“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. »
Many 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 »
Read the last article in our series on current events in the labor market, written from the perspective of an airport employee. We conclude it by turning to price pressure and the associated issue of consumer responsibility, and illustrate this with the example of the struggling airline industry. In doing so, we also show that this sector and its troubles are ubiquitous and should be of interest to all of us – not just because of its impact on the environment. » Read more about: “Dear passengers, please do care…” On consumer responsibility »
With the emergence of big data, organizations – private and public alike – are increasingly adopting AI technologies to drive automation and data-driven decision making in an effort to improve efficiency and drive growth. However, the growing adoption of AI technologies has been accompanied by a steady stream of scandals around unethical deployment. AI assistants like Alexa, Siri and co. – and workers in the companies behind them – listening in on people’s private conversations to gather data for personalized marketing; » Read more about: AI ethics – you can’t build something on nothing. »
The Federal Councillor’s solemnly echoing speech at the inauguration of the new office complex of a well-known technology company near Zurich Main Station booms from all the loudspeakers. Although baggage handler Mario is only half paying attention, the omnipresent buzzwords “digitization” and “innovation” cannot be overheard. On the way to his favorite pub on Langstrasse, Mario squeezes past the dozens of onlookers and aperitif hunters, doing his best not to catch a champagne shower. » Read more about: Shortage of skilled workers with vocational training: Planning isn’t everything, but a must »