Job matching is the AI of the job board world.

It’s like this: for decades AI has been held out to computer geeks and normal folks alike as something that was ‘just around the corner’. Even the definition of AI has changed – sure, Big Blue could beat a chess master but that wasn’t really intelligence, right? Since 1950, the Turing test has been the gold standard for AI – and no computer program has been able to pass it. (I will leave for now the various strengths and weaknesses of this test).

Job matching has held a similar spot in the job board industry. As far back as I can remember, there have been vendors promising solutions – but the solutions have always fallen short in one way or another.

The promise: A job seeker can fill out a form (often of significant length) that details skills, likes, dislikes, and job history. The job matching software will use this information to ‘match’ the job seeker to a ‘perfect’ (or pretty darned good) job. The job seeker is happy because he/she has found a great position, the employer is happy because they’ve found the perfect employee, and the job board is happy because a position has been filled.

The problem: People are impatient, even lazy. They don’t want to spend 10, 20, or even 30 minutes filling out forms for an uncertain return. On the other side, programmers and designers must decide which factors are most important in matching a job to a person. Those factors can be overwhelming – for example, is it enough to have a B.A.? Or is it better to have a B.A. from Amherst? Or is it better to have a B.A. in English from Amherst in the late 80s? With a 3.5 GPA or higher? And believe me, I’m simplifying the problem here. Think about cultural fit, hard and soft skills, personality traits, and much much more.

Who has tried it? Well, there’s Jobfox, RealMatch, and many others. None dominates the job board industry, although each has made inroads. There are also stand-alone services such as ClearFit and QuietAgent that are unaffiliated with specific job boards. I suspect that all face the problems described above: job seeker resistance and the complexity of matching.

What’s next? Heck if I know. Certainly if a system could gather information from job seekers in a painless manner, and then use that information to match jobs to seekers, it would have a chance of succeeding. One path forward could be the collection and collation of data left on various social media platforms (imagine
analyzing ALL Facebook postings for everyone ages 18 to 26, for example), which could then be fashioned into candidate profiles. Talk about a challenging project! But it’s just data, after all (although there is a small issue of privacy there).

Or perhaps a perpetual resume site like LinkedIn could somehow extract enough information from its users’ profiles, comments, and actions to build candidate data that would be used in matching systems.

Sounds like a job for AI!