Human resources have been one of the last departments to be touched by machine learning and AI. Nevertheless, slowly but steadily, machine learning has been gaining more traction in the HR department owing to the array of benefits with creating job descriptions to attract the best talent, training recommendations for employees and predicting employee attrition.
Dr. Raul V. Rodriguez, Dean of the School of Business at Woxsen University, will be joining us for the Nordic People Analytics Summit in September to share more in-depth insights into how AI and ML are transforming HR. We had a conversation with Dr. Raul to learn more about the current impact of ML in HR, the state of HR & People Analytics in the post-COVID-19 world and how AI helps evolve organisations’ relationship with their employees.
Hyperight: Hello Raul, we are extremely pleased to have you at the second edition of the Nordic People Analytics Summit, this time in a virtual setting. Before we go onto more topic-related questions, let’s get familiar with who Dr. Raul V. Rodriguez is.
You are the Dean of the School of Business at Woxsen University, Hyderabad, India. But apart from that, you are a registered expert in Artificial intelligence, Intelligent Systems, Multi-agent Systems at the European Commission and a nominee for the Forbes 30 Under 30 Europe 2020 list. Also, you have experience working as a CEO & HR Manager and have a PhD in Artificial Intelligence and Robotics Process Automation applications in Human Resources. Could you please tell us a bit about how all these experiences contributed to the expert you are today?
Dr. Raul V. Rodriguez: That’s indeed a good question. To begin with, it is important to mention that I started my career in the field of psychology, as a counselling intern. I always had this passion and in-depth interest to understand the cognitive side of life. As I moved through the years, my academic experience was mostly drawn toward liberal arts along with emerging technologies, a combination which most people find unusual. However, we must remember that what we call AI or even robotics, is a mere resemblance of what we are, just artificially.
In order to develop my interest further, I thought of monetising it. So along with two friends and partners, I started and led a research institute with branches in India and some EU countries such as Spain and Germany. As I had a keen interest in understanding human behaviour, I proposed myself to lead the HR department, especially because we did not have a large amount of personnel in the first place.
It was a start-up that drew a lot of attention and it did not take long for us to get investors on board. We develop valuable projects in the human-machine arena, as well as in the field of non-verbal communication and what is commonly referred to as “lie detection”. It was surely a rewarding and enjoyable journey which led me to pursue my postgraduate education in more tech-oriented specialisations such as Big Data, AI and, lately, Robotics.
As I evolved professionally and developed a powerful network line-up, I started to get in touch with EU institutions such as the European Commission, among others. This led me to offer my services as a consultant and be registered as a technical expert for initiatives such as Horizon 2020. In regards to the Forbes 30u30 nomination, I must say it caught me by surprise as I had simply developed certain Machine Learning projects in HR and Agriculture, which were certainly innovative in their own way, but I never did so with the aim to get recognition. One fine day, I got an email from Randall Lane, while working in Mumbai as an Assistant Professor, and I remember being on a plane to Berlin a month later to join the 30u30 Europe Summit.
Overall, I believe my interest in human existence and life as a whole has guided my actions, both personally and professionally.
Hyperight: Your NPA presentation is with the topic Future of HR from 2020: Machine Learning. What impact does machine learning have in HR?
Dr. Raul V. Rodriguez: Well, the current use of Machine Learning is related to the ability of machines to discover talent in human beings, beyond their hard and verifiable competencies, such as their level of education, and tracking their performance and daily behaviour.
Software intelligence is transforming human resources. At the moment, its main focus has been placed on recruitment processes, which in most cases are very expensive and inefficient.
A first example would be the development of technology that would allow people to create job descriptions that are gender-neutral to attract the best possible candidates, whether male or female. This would boost a group of job seekers and a more balanced population of employees.
A second example is the training recommendations that employees could receive. On several occasions, these employees have a large umbrella of training options at their disposal, but they cannot find what is most relevant to them. Therefore, these algorithms present the internal and external courses that best suit the employee’s development objectives based on certain variables, including the skills that the employee intends to develop and the courses taken by other employees with similar professional objectives.
A third example could be Sentiment Analysis, which is a form of NLP (Natural Language Processing) that analyzes the social conversations generated on the Internet to identify opinions and extract the emotions.
Lastly, we should mention the monitoring of employee attrition, through which we can predict which employees will remain in the company and which ones will not, based on several parameters such distance from the home and workplace, number of years spent in the company, promotions, general satisfaction, etc.
Hyperight: How does the current state affect companies’ perception of HR and People Analytics? If previously companies didn’t see people analytics as a strategic priority, with our new workplace reality, they don’t have a choice but to rely on data, advanced analytics and AI. What is your take on this?
Dr. Raul V. Rodriguez: Companies need to understand that the only choice right now is to choose whether to adapt or perish. The post-COVID-19 world is going to be extremely tech-oriented, hence relying on Big Data and advanced AI algorithms as the key to the companies’ future development. Those who were sceptical earlier, do not really have much of a choice other than becoming tech-savvy before the competition does the needful too.
Hyperight: In one of your presentation synopsis points, you appeal for companies to “Treat Employees Like Customers or AI will do it for you”. Could you elaborate on this thought-provoking statement?
Dr. Raul V. Rodriguez: I think this quote by Sir Richard Branson speaks by itself: “Clients do not come first. Employees come first. If you take care of your employees, they will take care of the clients.” The truth is that most companies do not care about their employees as individuals but numbers. They are on their payroll and that’s pretty much where their relationship begins and ends. Companies need to understand they are not doing a favour to their employees by employing them. They are paying a certain remuneration for the years they took to achieve certain milestones, obtain some particular skill set and their tenure in the company. More often than not, the client seems to be the king. But without committed and satisfied employees, a client will surely have a terrible experience.
“Clients do not come first. Employees come first. If you take care of your employees, they will take care of the clients.”
Hyperight: How should companies transform their approach towards their employees. And what is the role of AI in this process?
Dr. Raul V. Rodriguez: AI comes into play due to the need to make decisions based on data and pattern identification, not on mere human emotions, perceptions, and bias. Companies are expected to embrace this technology, even more now with the post-pandemic “new normality”.
For example, on many occasions, employees have several training options, but often they cannot find what is most relevant to them. Therefore, AI algorithms present the internal and external courses that best suit the employee’s development objectives based on many variables, including the skills that the employee intends to develop and the courses taken by other employees with similar professional objectives. Similarly, it supports the internal teams’ formations with employees whose skills are alike or with capabilities that could be aligned with the company’s long-term vision and mission. Alongside this, benefits, appraisals and promotions will be taken forward based uniquely on data and actual facts.
This is an important stepping stone toward employee, and ultimately, customer satisfaction.
Hyperight: Another crucial aspect you will introduce in your presentation is the importance of employee privacy and ethical use of their data. Is AI a ticking bomb for employee privacy?
Dr. Raul V. Rodriguez: Yes, AI can compromise employees’ privacy if not regulated adequately. But haven’t employees given their so-called “freedom” and “privacy” long ago, with the use of social media, biometric tools, or instant messaging? The problem here is that we might not be willing to be tracked by the company that issues our payroll, but we are fine being tracked by tech MNCs letting our data fly around for free. It is a slight hypocritical view of technology, in my opinion. However, to regulate this, companies shall request the employee’s agreement through a non-objection certificate upon hiring and on-boarding, to ensure that prior communication has been made about such internal AI use and policy.
Hyperight: And one last question, what are the HR trends with AI and machine learning organisations should prepare for to prosper in the age of artificial intelligence?
Dr. Raul V. Rodriguez: Well, most of the case examples have been mentioned above, but if we go one step ahead, companies shall consider a full-fledged AI implementation, company-wide, where AI-induced talent acquisition & recruitment, facial & voice emotion recognition, email tracking, behavioural analysis and appraisal or attrition will be present on 24/7 basis. This would ultimately increase profitability and accuracy of services while tackling difficult scenarios such as employee’s distress and anxiety.