47% of the working population might be under threat from robots in the next 20 years. According to the Darwinian Theory of Evolution, as we evolved through the natural selection of variation, so did our cognitive and learning abilities. In early 1969, Stanford Research Institute (SRI) gave us Shakey the Robot, with capabilities such as perception, mobility, and problem solving. Now, we have come to the age where Google is steadily working on developing driverless cars.
While these developments are interesting, they beg a certain question: will robots help us become more productive, or will they take our jobs? And in what ways will artificial intelligence (AI) affect human resources in the forthcoming years? Let us look at a rough overview of all the possibilities.
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AI in Consumer and Business Products
Does data beat algorithms? It is a matter of debate. Peter Norvig, research director at Google, says, “We don’t have better algorithms. We just have more data.” A plot of a production system at Netflix shows that more data does not always mean better performance. However, we all can agree that when developing a business product based on AI, the very first requirement is huge data sets. Vast data about consumers did not exist in the past; even artificial neural development and “deep learning” requires huge amount of data sets.
This problem was solved with the influx of big data, which uses predictive analytics to extract value from unstructured data, and also with the smart move to include graphics processing cards in computers instead of traditional processors, which can train the learning of the neural network in a faster way. This boom is going to affect the workflows and modify the existing, more traditional tools. Here is how it is going to affect HR.
1.NLP to drive prediction
AI is going to have a direct effect on the recruitment of new employees and the training of the existing ones. It is difficult to deal with humans because they are complicated. It has been difficult to derive data related to them, and even more difficult to process them into a structured form. Deriving conclusions from human speech requires a huge amount of data sets, and we don’t have enough information to feed to the AI. One breakthrough in the field of AI is NLP (Natural Language Processing); since human speech is primarily in the form of natural languages, an NLP engine can parse through the texts and find a pattern by analyzing the syntactic relationships between words. This will help HR come up with structured data.
Imagine this situation: you are in HR and there is an interview that must be scheduled with a panel consisting of 4 members. Now, you have to come up with a plausible time, check and confirm with each of the panelists, as well as the candidate, and schedule it. Suddenly, something happens and one of them is not available. Well, you must start again from square one, and that is tiring, time-consuming, and frustrating. Machine learning can be a great help in these cases; if the software can be shown enough examples of workflow, it can decide on its own which course of action to take. A few years down the line, HR functions such as employee onboarding, payroll processing, and scheduling training will be done by software driven by machine learning.
Software that can suggest movies or restaurants are very common, and these types of developments will progress in the human arena as well. How does one determine if an employee needs training based on the last few months of his performance? Well, the data might be there from all the evaluations, but deciphering the data manually is a tedious task, especially for organizations that have loads of employees. Providing a personalized mentor to each and every employee is costly, and software has not been accurate enough to serve the purpose — till today. With the evolution of AI, recommendations for employee training and improvement will be available very easily.
The most important factors here are time and quantity. Quantity is very much proportional to time, because as more time passes, more data sets are generated, which can then be fed to the AI. HR software and processes can be free of manual work as quantity increases, because the software would be able to learn and improve. This will increase the productivity of HR as well as that of the employees. As HR director, one should start focusing on becoming fluent in AI and try to find areas in the organization where it can be implemented.