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The Machine Learning and AI Recruiting Future
As the technological ecosystem evolves so do the various components of that ecosystem. A more decentralized world and the proliferation of knowledge can equip the right persons with access to game-changing technology. In the worlds of industry and business, the incorporation of emerging tech can mean the difference between dominance and obsolescence. For recruiters, this concern is no different. One's continued success depends on staying alert to dynamic changes in recruiting technologies. The reality of artificial intelligence has captured the imagination of some of the world's largest industries. Now is the time to consider the machine learning and AI recruiting future. We researched three separate functions of artificial intelligence and machine learning to provide insight on the future of recruiting technology.
The Human Element
Perhaps one of the boldest and most prevalent adaptations, and perhaps the most likely to lay the bridge to the AI recruiting future, is HireVue’s video screening platform. This system is akin to a video interview, except the candidate uses the video technology to answer 11 questions; therefore, the technology replaces the human factor. The A.I. calculates given responses to questions and analyzes visual cues, recording and measuring them through a particular algorithm. Consequently, a compatibility score is formulated by reviewing the interviewee's facial behavior (looking down, looking away, smiling, etc.). This technology filters out candidates who do not meet a baseline score before they ever reach the recruiter.
Survival Rate
The data scientists at Randstand Sourceright have announced the potential of an AI recruiting future built upon principles of the healthcare industries use of machine learning technologies, particularly a technique referred to as survival analysis. In healthcare, survival analysis technology is used to analyze given data, so that outcomes can be predicted. These outcomes can relate to a patient's likelihood of relapse or even death. Randstand Sourceright is looking to incorporate a similar format of machine learning technology to determine the survival of a job. They hope that a compilation of data can determine the survivability of a job opening. This data includes hiring history, number of candidates, job market data and more. Recruiters can therefore use this information to better determine the viability of a client. Furthermore, they can estimate the timeframe of a placement.
Robot Recruiters
While this speculation may seem farfetched, the AI recruiting future offers even more unbelievable possibilities. The full-service recruiting bot is a concept that may seem like some bogeyman, but recruiting platforms like Celectiv are actively working to launch technologies that combine talent-seeking tools with analytical tech like organizational psychology assessments. According to Greg Carrott, the founding company chairman, the goal of Celectiv is to create a single platform that identifies, assesses, recruits and retains talent. Celectiv looks to go a step or two beyond the initial assessment tools used by hundreds of companies to take the recruitment process from selection to placement.
The machine learning and AI recruiting future poses numerous questions. What is important is to remember that much like the major technological innovations in recruiting, little can be done to exist separate from them or avoid their effects. Survival will largely hinge on developing an understanding of the oncoming technologies. What is encouraging is that for the recruiters who adapt to these changes, they will likely find their operations increasing in functionality and efficiency. The AI recruiting future may be hazy, but it overwhelmingly seems bright.
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