Specialist recruitment firm Hays is employing artificial intelligence to accelerate the screening of candidates.
With the help of an unnamed external partner, the company is training an AI-based system which allows recruiters to enter a job description and be served a long-list of potential employees for further refinement.
“Matching candidates to potential roles is a complex AI challenge, requiring contextual knowledge about how job titles, skills and experience relate to each other,” Hays CIO Steve Weston told Computerworld.
“Once implemented, this advanced matching system means that our consultants no longer need to search using combinations of keywords and filters, iteratively opening up and narrowing down their search until a satisfactory shortlist is created,” he said.
Instead they can describe a job and immediately obtain a list of the most suitable candidates in the recruiter’s database. That list can then be refined based on less tangible factors like personality, weighting of specific requirements within the job description, and fit with the business culture of the client, Weston said.
The company is training the ontology of the tool which defines types of entity like jobs, skills, experience, professions, industries and employers, as well as the relationships between them like ‘includes’, ‘is-a-subset-of’, ‘requires’ and so on.
“While it is relatively straightforward for a computer to identify that someone currently working as a ‘Change Manager’ might be a good candidate for a ‘Senior Change Manager’ job, it is much harder to ensure that people working in similar but differently named roles – such as ‘Project Manager’ – are also correctly identified as possibilities,” Weston explained.
“Similarly, knowing that a job which requires ‘Intermediate Spanish’ as a skill should include candidates with skills such as ‘Advanced Spanish’, ‘Native Spanish’ and ‘Business Spanish’, but not include candidates with only ‘Basic Spanish’, is a task which appears trivial for human intelligence, but needs an automated system to be programmed to understand context and meaning,” he added.
The resulting system will mean better recruitment decisions and more time for consultants to assess candidates on an individual level, the firm said.
Hays employs more than 9,000 staff in 33 countries and has operated in Australia since 1974. Last year Hays placed 12,200 people into permanent jobs in Australia and New Zealand, and filled some 62,000 temporary jobs locally.
“Creating or training this ontology requires a large volume of data on historical jobs, careers, candidates CVs, hiring outcomes and more, as well as sophisticated capability in Natural Language Processing to convert the semi-structured data of CVs and job descriptions into a consistent format for processing,” Weston explained.
Hays CEO Alistair Cox last week said the use of AI at the firm did not mean the human element of recruitment would be forgotten.
“It remains incredibly difficult for any machine to analyse the soft skills that remain so crucial to modern business. I’m yet to see an algorithm that can read things like humour, temperament or enthusiasm as effectively as a person can. And let’s not forget that ultimately human oversight is still required to compile criteria – I certainly wouldn’t want a machine deciding the persona of my business, and I don’t think it would do a particularly good job yet,” Cox said.
The technology will give hiring consultants more time to focus on higher level tasks, rather than replace them, Cox added.
“Today people do business with people and I hope that never changes,” he said. “Despite the excitement and fears around the rise of AI, talent management largely remains a contact sport, where gut feeling, grounded in thousands of tiny facets of human experience which are never captured as data, plays just as strong a role as hard data.”