Does Soccer Trump Sex?https://i2.wp.com/hr-on.com/wp-content/uploads/2019/08/Fodb_Sex.jpg?fit=1200%2C628&ssl=11200628HR-ONHR-ONhttps://i2.wp.com/hr-on.com/wp-content/uploads/2019/08/Fodb_Sex.jpg?fit=1200%2C628&ssl=1
In the upcoming years, HR and recruitment related work will undergo a major change, where machine learning and AI will increasingly become key tools for the HR employee and the recruiter.
At the same time, this development creates some great opportunities and worrisomescenarios that need to be addressed from this moment on.
In this post, I would like to address some of the perspectives one can/should take in its reflections on data-driven recruitment and HR. I will focus especially on recruitment.
When collecting large amounts of data, it is natural to use said data to learn. The first step is to create statistics based on the collected data. The statistic says something about the past, but at the same time, it provides answers only to the questions asked. And maybe not even that.
The next step is the work on machine-learning, where one trains algorithms to find patterns in data, which one may not be aware of. It could be to identify various trends or see connections that may not come to mind.
However, the fact that there is a connection – a correlation between different types of data does not necessarily mean that there also is causality – that is causal relation. Machine-learning can provide a basis for making future analyses and not just looking at the past, as the statistics allow.
A little about data
When working with data, it is important to be clear that data does not necessarily say anything about reality or contains any truth. Data may be contaminated in many ways, and our way of putting together data may prove fundamental to be wrong and ultimately have disastrous consequences.
Recently, itemerged that the data used in legal proceedings for the last 7 years may be faulty . Specifically, it means that guilty people may have gone free and worse, that innocent people have been convicted by Danish courts. The Danish authorities are in front of a huge effort to review thousands of cases in the coming years. And people stand before having to tile the swathe from lives that have been destroyed along the way.
In the more curious section, I recently attended an HR conference where a presenter told an immersive story about a football fan who had seen a very exciting fight on television. Later, he was with his girlfriend in more intimate conditions.
His pulse-watch subsequently showed that the pulse had been at most during the soccer match, which was interpreted as being more engaged in football than intimate relations. In other words: Football trumps sex.
But it may just be a fallacy, because had the clock also measured the level of neurotransmitters in the brain, the conclusion might have been quite different. And furthermore, you could ask them yourself and perhaps get a third answer.
Onemust therefore constantly be critical of one’s data and how to use it.
Practical use in recruitment
When recruiting, you are of course interested in finding the right candidate and in that process, you collect as much data and knowledge about the candidate as possible. There’s nothing wrong with that.
However, the more data you collect about a candidate, the greater the requirements it actually puts on the recruiter’s professional as well as ethical, social and empathetic skills.
One must be able to sort in data and reject data that is otherwise exciting enough, but not necessarily relevant in the specific context. At the same time, one must be able to take a critical view of the data used and the attention to deficiencies and sources of error.
The fact remains that nothing can replace the personal meeting between people. In fact, the more data you have access to, the personal meeting becomes even more important and more crucial.
And if the personal meeting with the candidate experiences a mismatch between what has been seen in his data and what the candidate produces, then first of all, you have to be critical of your data and method.
One can put on the tip say that the recruiter’s level of competence must match the amount of data. The more data, the higher the level of compatibility required. But at the same time, it is a gift, because ideally it will lead to a much more qualitative recruitment and greater likelihood of the good match for the benefit of both employees and companies.
The above, of course, takes its starting point in a humanist perspective and a desire on my part for an increased focus on the human factor during a data-driven time.
Something I personally think is becoming increasingly important as machines increasingly take over tasks from us. And at the same time a wish I am not alone with, it is one of the core areas of the GDPR, where one has just made a lot out of automatic profiling.
Back is just one question: trumps football really sex?