Robots are on the rise. A report from Oxford Economics estimates that as many as 20 million manufacturing jobs — that’s 8.5% of the global manufacturing workforce — could be lost to automation by 2030. Other industries will also feel an impact.
No one can predict exactly how this will play out. Some argue that the robots are our friends or assert that automation will incur losses but will ultimately make us more productive. Others preach doom and gloom. And still others dispute the nature of the problem, pointing out that robots are not so much stealing our jobs as becoming our bosses.
Regardless of your personal standpoint, there are two facts here: The robot revolution is real, and it will not affect all people or industries the same.
Robots in Recruiting
What does this mean for the job search and recruitment spaces, where robots already dominate? Artificial intelligence (AI) and applicant tracking systems (ATS) have become core elements of most corporations’ hiring processes. They first surfaced in response to technologies such as Google for Jobs, the direct apply features on Facebook and LinkedIn, and the proliferation of job board aggregators and career sites.
At the same time that applying to jobs became easier than ever before, job seekers also gained access to an unprecedented volume of listings. How could HR managers and talent acquisition professionals possibly cope with this flood of resumes and applications?
By using ATS software to scan resumes for keywords and weed out unqualified candidates, of course. Recruiters discovered that AI could not only save them from having to read every single resume; it could also help them combat bias in their hiring decisions. The love affair with tech blossomed into a marriage.
Automatic For The People?
AI causes as many problems as it solves, opponents say. The hiring process has lost its “human touch.” Applicants who are rejected feel unfairly discriminated against. Perception is widespread that the system is rigged and machines are valued over people.
But while job searching is, in fact, deeply broken, robots are not the root cause. The problem goes much deeper. It begins with traditional hiring’s failure to incentivize intentionality and ends with job seekers who are not clear on their goals.
So while it might be tempting to react to the imperfections or misuses of AI in the job sphere, those who make machines the enemy are missing the point: action — or rather, being proactive, both in terms of charting one’s own career path and in using AI to improve outcomes on both sides of the hiring divide.
When You're Hot, You're Bot
AI, despite the challenges it poses for job seekers and the hiring process, is not a problem to be solved — it’s a ray of hope.
Used correctly, it can save job seekers and companies from painful and costly “bad matches.”
On the hiring end, AI cuts the time and cost of talent acquisition. Candidates can be tailored to complement a company’s previous hires or to promote specific decision-making patterns and behaviors. Resumes are scored and shortlisted while applicants are evaluated against company benchmarks based on soft skill profiles created through the playing of immersive computer games.
But machine learning also has a lesson or two to teach job seekers. Skills assessment software yields insight into their style of working and steers them toward positions that fit their skills, qualifications and talents. Such knowledge is virtual gold and can pave the way to achieving their career goals.
Machine Learning Meets Career Pathing
How, then, does machine learning enable stronger, more self-actualized careers? The answer is surprisingly simple. So much more data is available today than 20 years ago. All those data points are helpful, but only if you view them with a keen sense of what’s important to you.
Companies must be clear on the qualities they seek in a candidate and conscientiously apply technology to favor those qualities without missing other important signs. Most ATS/hiring platforms allow you to clearly mark which skills are must, which are very important and which are simply nice to have. Companies must be clear on which skills are essential for the position and which are not. By placing weight on essential skills over all else, you can avoid bias sneaking into hiring decisions.
At the same time, job seekers need to be aware of their short-term and long-term career goals and stay one step ahead of their next job move at all times. It’s much easier to benefit from technology if you already know where you’re heading.
Beyond Bias, Better Jobs
Humans make mistakes. We miss cues and lack the ability to process all the information available to us as quickly and effectively as machines can. As our algorithms get smarter and our AI gets faster, machines will know better than we do what our next job should be and will make better connections than we could on our own.
When robots speak, we will have to learn to listen.
AI predicts things more accurately than humans, but of course, it has to be given a goal. The latter responsibility falls on us and must be taken seriously. But AI can, and will, make job search better.
Machine learning is there for us if we use it. The benefits are clear: Instead of getting lost in the labyrinth of job search, we can empower ourselves to find the one-in-a-million position that aligns with our goals. And as hiring managers, we can match our company’s needs with the one candidate who will stick around and create lasting value.
Our careers are up to us.