The expectations and hype we see around artificial intelligence (AI) today are amazingly overwhelming. Soon we will be talking to our computers, drones will make purchases for us, cars will start driving on their own, and most office workers will only control the operation of machines. Is this so and how real is all this?
As an industry analyst and engineer who has studied technology for decades, I can say that we are going through a rather interesting stage when, on the one hand, the hype around is much ahead of reality, and on the other, the result can be much more significant than we think. Well, the possibilities at the level of personnel management are simply enormous.
Despite the fact that almost all HR providers are working on building AI teams, and we all want our system to be smarter and more efficient, it seems to me that the modern market is still too young, and in confirmation of this I would like highlight a few points.
Keywords: artificial intelligence, history of the development of artificial intelligence, areas of application of artificial intelligence, artificial intelligence in human resources.
The Role of AI in Human Resources and Leadership
It must be admitted that AI is not some magical computerized person, but a wide range of machine learning algorithms and tools that can quickly retrieve data, identify patterns, and optimize or predict trends. Systems can recognize speech, analyze photographs, and use pattern matching techniques to determine mood, honesty, and even personality traits. Algorithms like these do not rely on «intuition» like a human, but they work very quickly and can analyze millions of sources of information in a matter of seconds and quickly categorize them.
Using statistical data, AI systems are able to «predict» and «learn» by plotting curves of possible decisions and then optimizing decisions based on a variety of criteria. Hence, it's not hard to imagine an AI system that looks at all possible demographics, work experience, and interview questions for candidates, and then “predicts” how effectively each one will do their job (HiredScore, Pymetrics, HireVue, IBM, and others already are working on it).
Despite the fact that the process itself is much more complicated than it seems, solving this problem is an important and noble deed. Answering a question on this topic a few weeks ago, I noted that “the majority of management decisions are made by us today exclusively on an intuitive level. If such systems make us a little smarter, then we can significantly improve our operational efficiency. "
Of course, there are many risks and obstacles to be overcome, but the potential is enormous.
Which apps can we expect in the near future?
In recruiting, many decisions are made intuitively. One study found that most recruiting managers infer a candidate within the first 60 seconds of an appointment, often based on the candidate's appearance, handshake, outfit, or speech. Do we know what characteristics, experience, education and personality traits guarantee success in playing a particular role? No, we don’t know. Managers and HR professionals spend billions of dollars developing assessments, tests, simulations, and games used in recruiting, yet many argue that despite this, in 30–40 % of cases, candidates are selected incorrectly.
AI-powered algorithms can scrutinize resumes, find suitable candidates within companies, identify high-performing employees, and even provide transcripts of video interviews to help us select the people who are most likely to be most successful. One client of ours uses the AI-powered assessment of Pymetrics, built on gamification principles, to validate applicants for marketing and sales jobs. By eliminating all the mistakes made in the interviewing process and in reviewing the candidate's track record made in the current process, the success rate increased by more than 30 %. AI in recruiting has a bright future.
It should also be borne in mind that while there is a general preoccupation with professional skills (software skills, sales skills, math skills, etc.), most research shows that mastering technical skills is only a small percentage of success. Most recent research on high-performance recruiting suggests that Maturity Four companies, that is, the ones that perform the best financially due to smart hiring, rely (40 % of the hiring criteria) on emotional and psychological characteristics such as as ambition, learnability, dedication and dedication. Will AI take this into account? Perhaps.
(Suppliers in this market include LinkedIn, Pymetrics, Entelo, HiredScore, IBM, Textio, Talview, Unitive, PredictiveHire, and more.)
Will AI become the hallmark of talent decisions?
The hype around AI is very high right now. Every HR software vendor wants to make you believe that their machine learning team is delivering the best-of-breed AI solution. Of course, opportunities in this area are important, but don't be influenced.
The success of a HR tool depends on many things: the accuracy and completeness of the algorithms, the ease of use of the systems, but, more importantly, the ability to provide the principles of the so-called «narrow AI» (or specialized solutions that can solve your problems). This can only be achieved if the supplier has a large amount of data (for training the system) and receives a large amount of feedback on the results of the system. Therefore, the main challenge, in my opinion, lies in setting directions, developing a business strategy and building trust with the client, not just having professional engineers.
And don't buy a black box system unless you can test it first with your company. All decisions made at the level of management or employees in a company are often based on the principles of culture, so it will take time to use the systems in real life and customize them to meet our needs. For example, IBM has spent years optimizing remuneration and talent management solutions for its company based on its culture and business model. They now offer their tools to enterprise customers, and each implementation reveals something new about algorithms to them, helping them to optimize them for industry, culture or organizational needs.
Conclusion
Despite all these complexities and risks, the potential is incredible. Companies spend 40–60 % of their earnings on payroll, and most of this huge amount is the result of managerial decisions that are made only on the basis of intuition. I am confident that through the development, reliability and focus of AI workforce systems on solving specific problems, we will see significant improvements in terms of productivity, efficiency and well-being of employees. We just need to be patient, vigilant and ready to invest in the future.
References:
- Profiles of the Future, by Arthur C. Clarke
- Artificial intelligence VS financial management [Electronic resource]. URL: http://www.sbr.in.ua/?p=620/ (accessed: 07.12.2018).
