This morning I attended an innovation update session by the wonderful people of Resource Solutions. One of the attractions was my favourite robot called Pepper, who had been trained to do a few poses for selfies. But imagine a robot as your secret weapon in the candidate resourcing, recruitment and career coaching field.
We were given a brief flavour of what is possible with the virtual sourcing assistant Arya, who trawls the net for matches to your open positions. It comes back with best fit based on skills and values listed in your role description in the shape of a star rating as well as an indication of the likelihood that the person is in the market to move to a new job and their predicted timeframe for doing so. Based on how you shortlist candidates and how you reject others, the virtual resources will become more intelligent over time and learn about your preferences and selection criteria. As with all machine learning powered systems, it gets better by use. Because the virtual sources is purely searching on a factual level, unconscious prejudice and bias can be avoided to some extent (until your humans obviously have started shortlisting). In any case the level of inclusion and better fit based on a larger number of criteria is made possible this way.
IBM showcased Watson application MyCa, a cognitive career advisor app, which is a chatbot to create personalised learning at the point of need or to match employees to internal job opportunities. In layman’s terms this means it uses a smart algorithm to search for information based on questions asked in the application called Myca. IBM Watson can be deployed to assist with recruitment career coaching, talent development, to create a virtual agent for HR and talent insight. Myca looks for demand for a role internally, previous successful candidates and their profiles, how the individual using the app matches the successful candidates and if they are not appropriate they will look for more appropriate fit or provide feedback on how to gain the necessary skills.
The final presentation was by HireVue, who allow again through the shape of an app, to shorten the recruitment process. From interview, to assessment and evaluation, is all carried out through an app. The machine learning hiding in the application analyses audio, video and language patterns to detect behavioural traits and give insights on the likelihood if a person is a good fit or not for a specific role. It uses micro expression analysis, such as minor facial movements from smiles to frowns to assess suitability. The number of data points it analyses is vastly larger than most of us humans can absorb and look for. The data models provide scoring and ranking for faster, smarter hiring and coaching decisions.
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