To read the first part of this article, go here!

Educating oneself and becoming aware of the current possibilities and not those of 2050, has become a crucial exercise for HR since the term ‘Artificial Intelligence’ sparks fantasies, fears and announcements that are proportional to its complexity.

Between dreams and anxiety around the world of tomorrow, there’s also today’s pragmatism.

This awareness is even more important since HR disposes of all the necessary tools to play a major role in the big game of chess that is the famous digital transformation.

So then, what are these tools?

  • First of all, the holy grail, the cornerstone of many technologies (and AI in particular): data! Data is hidden pretty much everywhere, gathered on a daily basis by numerous processes that address candidates via ATSs, sourcing tools, and CRMs, as well as the entire workforce simultaneously (administrative files, interview content, validated and registered skills, salaries, training, etc.).
  • Second, the business knowledge for which technology could create, repair or improve the processes.
  • Third, the company culture and the meaning we want to give to it via technological innovations.

And it often is in the correct alignment and estimation of these three key points that the problem lies. 

The mistake may be to think that it’s enough to provide a few tens of thousands of candidates resumes who have been recruited in the past – if these are of course available – without understanding or eliminating the possible biases embedded in this ‘data’, and to think that this will lead to atypical profiles being recommended (as unfortunately experienced by Amazon).

Another mistake: overestimating the capabilities of AI and thinking that it can, fully autonomously, be in charge of an entire business process, while current applications of AI find on the contrary their relevance in their verticality (meaning a strong expertise in a limited area).   

Or to think that employee representatives and employees of a company with a difficult social climate will welcome the regular collection of all their data and kindly give their consent.

However, some simple questions can help avoid pitfalls, amalgamations and, above all, failed projects. 

  1. Do we really need AI technology? This should be the very first question to ask as it’s the basis, the very starting point! Except for the fact that it’s, as every basic question, always the one we forget about. As a reminder: many tasks can be automated without AI by simple algorithms!
  2. Are the famous functional ‘pains’ we want to repair/improve horizontal (i.e. automating the entire recruitment process, proposing an actual virtual career coach that would have the answer to everything)? Or, on the contrary, are they vertical (e.g. automating the scheduling of candidate interviews based on their availability, proposing micro-learning at the best moment during the day, detecting the right competencies to assess during an annual review…)?   
    Illu_framework_Chatbot

    Illustration of a Chatbot’s Conversation Framework: the more open the field of application, the more complicated or even impossible the task becomes!

  3. What technologies are associated with AI needs and do they require internal data on the business world? This last point is important since big internal projects linked to data will potentially be necessary, ranging from their collection, standardization and reprocessing, to the process of obtaining the consent of a fairly large number of employees.
  4. How can we ensure the monitoring and the administration of processes? In other words, are we dealing with a pretty little black box whose results can’t be contested or changed in any way, or can we clearly understand the way it works and make it evolve?

Of course, the questions mentioned above aren’t exhaustive. The idea is for them to lead us to a more profound reflection around the dimension that any potential AI project should provoke! 

On a final note

To conclude, if we ask ourselves so many questions, if we try so hard to understand the realities that can be hidden behind the statements around AI, it means that we are finding ourselves in a period of technological acceleration – characterized by the famous 3rd industrial revolution – in which everything goes very fast, too fast even.

This period, which is certainly is very exciting, is also one of the most contradictory. And particularly for HR, who are asked to deal with the major expectations of what tomorrow’s challenges will be while remaining extremely pragmatic about the real opportunities of today.

According to the famous historian Yuval Noah Harari and his 4C principle (to which we could add Curiosity), developing and mobilizing transversal skills (also referred to as soft skills) such as critical thinking, creativity, collaboration, and communication have become major priorities in order to better understand this large gap. 

Although the Critical opinion has widely been talked about in this article, that doesn’t mean that the big expectations of the world of tomorrow are to be set aside. On the contrary! Whether it is today or tomorrow, we are and will be confronted with technologies that make up for what Bernard Stiegler calls a Pharmakon, which in Greek means both a remedy and a poison. In other words, the real flaw lies in the man who controls the technology, not the other way around!

This is where the heavy task HR is facing lies: to ‘design’, starting now, the ethical and moral frameworks of future technologies arriving at a fast pace… before the latter are imposed on them!

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