Will HR continue to be the game changer for the future? Without leveraging on AI, we will be left behind.
Machine learning is getting better and faster at understanding tasks performed by the Human Resources (HR) function. Recent advances in Artificial Intelligence (AI) have led to speculation that AI might one day replace the HR professionals. Take for example, in recruiting for the right fit, cognitive computing power has developed deep learning neural networks that can identify verbal and non-verbal data points. These data points are then used to determine the “fit” of the candidates by calculating the muscle movements, matching it with proprietary algorithms and database to make the hiring decision.
Sounds advance and complex, right? Well, not necessary. As a former HR practitioner, I have often used my Psychological training to determine the “Fit” of the candidate. Like AI’s non-verbal data practices, I have also used multiple sources of non-verbal communication to pursue the needs of the open position. One practical source of data for non-verbal communication that I have often used is the eye-movements model in Neuro-Linguistic Programming (NLP). Using this approach, the non-verbal evidence is used to construct interview questions, drive the interview process to gain more evidence to support the hiring decision.
(Image Source: learning-mind.com)
However, as a “human” HR practitioner, I may not have effectively processed and captured all the non-verbal communication data points exhibited by the candidate. This is where cognitive computing power is needed to improve the hiring outcome. AI is currently on par or above par with human performance in capturing non-verbal communication. Deep learning is advancing rapidly. With increased data points collected in every video interviewing conducted, this only portends and affirm AI-driven recruitment is inevitable.
The question then arises, “if AI is a necessity in the recruitment process, how then a “human” HR professional makes a significant impact on the hiring decision?”
Let’s face it! The recruiting process must be altered and enhanced by AI. But as long as AI is portrayed negatively as a role replacement, resistance will be high. This is only natural as humans respond to threats are through hyperarousal or acute stress response, or simply put fight-or-flight.
Stress is a mental state of mind when expectations outweigh reality. This affects our ability to maintain a balanced response to our mental wellbeing is not in equilibrium. As such, in this stressed mode, AI is perceived as a job “replacement”, jeopardizing a person’s livelihood.
That is also the reason why as HR practitioners, we need to elevate and focus our services on building Human Capital instead of managing human resources. In an earlier article, Technological SWOT for HR to transform, I shared the weaknesses of AI. Building on these factors, these are my take on how HR practitioners are able to elevate their practices to becoming Human Capital practitioners.
Firstly, Basic AI systems perform single task (Narrow AI) while deep learning models combine multiple narrow tasks through complex algorithms to predict potential findings. These are all “hard skills”. The inability to process “soft skills” via AI is, therefore, the winning advantage for human. Focusing on these essential “soft skills” such as questioning techniques, investigative cultural fit, and integrity questioning techniques as in my earlier example is the only way forward.
Secondly, deep learning algorithms required in AI must be “trained”. Huge amounts of past and present data are needed to achieve these “trained experiences”. Often, this itself is both challenging and time-consuming. So, what does this translates to us, the Human Capital practitioners? Simple, focus on current and future experiences to make predictive analysis; while building long-term foresight and helicopter view skills critical for Human Capital practitioners.
Lastly, model on how AI works; which is continuous learning and relearning. Past and current skillsets have shortened lifespan thus affecting one’s marketability. Hence, being able to predict market skills gap is critical in our learning journey. Work on skillsets that are highly complex and not easily replicated by AI. This will lengthen the marketability lifespan of our Human Capital skillsets.
Concluding thoughts: Repetitive functional human resources skills are being replicated quickly by AI. We need to transform our practices now to one that builds human capital for the future economy.
About the writer
Jian Hong is the Co-Founder and CEO of Su-Ette, a company focused on bringing Advanced AI and NLP technology to serve the HR function. Equipped with more than 17 years of professional HR experience, he holds a Master’s Degree in Human Capital Management and Bachelor Degree in Psychology.
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