Ep 817: The Human Bias Fueling Talent Shortages
Recruiting Future with Matt Alder - What's Next For Talent Acquisition, HR & Hiring?Show Notes
Cybersecurity is one of the hardest markets to hire in, and a lot of the difficulty comes from how companies approach the process. Candidates are still being filtered on degrees, previous employers, and years of experience- signals that are particularly weak in a field where the best work is confidential, and skills need updating constantly. Good people are getting screened out, and what looks like a talent shortage can often be a matching problem.
So, what changes when companies stop filtering on the usual proxies and start hiring on what candidates can actually do?
My guest this week is Laurent Halimi, CEO and founder of Cyberr.ai, a professional network for cybersecurity professionals. In our conversation, Laurent explains why the skills shortage in cybersecurity is only half the truth, where the bias in hiring really comes from, and what it takes to judge candidates on skills that you can actually verify.
In the interview, we discuss:
How AI is changing what cybersecurity professionals do and the new roles it is creating
A real skill gap at the senior level and a matching problem everywhere else
The certification race and why it is losing relevance
Why hiring in cybersecurity is different from other technical fields
Trust, stale skills, and work that stays invisible
Where the bias in hiring algorithms really comes from
Practical steps for judging candidates on verifiable skills
Anonymous applications and giving candidates control of their profiles
Will skills finally beat pedigree, and what does the future look like?
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More from Recruiting Future with Matt Alder - What's Next For Talent Acquisition, HR & Hiring?
If you've not listened to Round Up before, it's a short review of the episodes that I've published in the last month to make sure you don't miss out on the valuable insights that my guests are sharing.
AI is moving from a specialist technology to something employees in large parts of the organization are increasingly expected to be using. Skills, mindsets, and long-established habits are much harder to change than software, which is why meeting that expectation is proving difficult. If the challenge is mainly a human one, AI readiness is as much a matter for HR and talent leaders as for technology teams. So what does it take to get a workforce ready for AI, and what opportunity does that create for talent leaders?
Redundancies have become a constant feature of the talent market. AI is taking a lot of the blame, but the drivers behind this are much broader. Jobs and skills are changing faster than most organizations can keep track of and the conventional response is to restructure the workforce and then hire in the new skills that are needed. That approach relies on a ready supply of perfectly qualified candidates, and in a fast-moving skills market those candidates are increasingly hard to find. It also assumes that employers already have a clear view of the skills and potential within their existing workforce, which is rarely the case.
There is a lot of pressure on talent acquisition to adopt AI, and the discussion about how to do it tends to focus on tools and skills. With layoffs attributed to AI in the headlines, the people in TA teams have good reason to feel anxious about the technology they are being asked to use. That anxiety makes people less willing to experiment, and addressing it has less to do with the technology than with how leaders handle uncertainty.
TA leaders have to keep delivering for the business while they use AI to transform how hiring works. At RecFest USA in Nashville, AI was the main topic of conversation, although the people I spoke to talked about much more than the technology. So where should TA leaders be focusing their attention?