AI is taking on more tasks in recruiting and job seeking
AI has come a long way in the past few years. After a splash in the 1970s and the bifurcation into expert systems and neural networks, some felt heuristic programming was a gimmick and not likely to ever deliver on its promise: a means to solve intractable problems without humans having to program solutions.
But in the last decade, AI has surged in new unforeseen forms. While not yet delivering the apocalypse forecast by Terminator or the psychosis foreseen in Kubrick’s 2001, A Space Odyssey, AI’s impact on our daily lives is growing. The growth in AI, in fact, sits at the heart of this site where using heuristics we help end-users assess market opportunities, for example in telecom investment research.
Of the many aspects of daily life that many welcome, scoring and ranking productivity, helping drivers navigate, translating languages and handling mundane, call centre enquiries top the list of reasons to leverage the technology. In these situations, simply by having a quicker response where one does not rely on the time of another person eases consumer interaction and reduces staffing costs.
But more so, there are other situations where simply removing the human from the equation is the key objective. Consider the element of bias. While such can be programmed into software intentionally, interacting with another person whose bias is hidden, is not something consumers want. For example, consider the recruitment process as reported not long ago by Forbes.
AI And Recruiting
In recruitment, companies want to hire those people that are likely to best fit both the job requirements and enhance the dynamics of the company. To ensure that they have the largest population of applicants from which to choose, companies broadcast their needs on forums that hopefully reach the right segment of respondents.
But when viewed by 1000s, there are likely 100s of responses; many of them would be a poor fit for the specific job. Enter AI. An AI pre-selection ‘bot can easily trawl such and recommend a handful of prospects for shortlisting.
AI is suitable here because of the bias as well as the indefatigable nature of the approach. While junior staffers are able to perform similar assessments, they lose their ability to concentrate and bring their bias into their reviews.
Apart from the initial assessment, AI is also applicable in conducting subsequent testing. By subjecting applicants to what might appear to be games or quizzes, an AI can rank the responses and catch original and applicable thinking. And ‘bots can even perform job interviews, highlighting strengths and weaknesses for subsequent follow up.
Of the many challenges to launching and evolving a company, hiring the wrong people is one of the top concerns.
AI And Applying For Jobs
On the other side also, ‘bots are now available to help job seekers find suitable positions. These are relatively inexpensive to engage. As such, savvier end users are using AI to scan for job and investment opportunities. Lensa is a platform that has heavily invested into AI with the purpose of helping recruiters find the more worthwhile people to pursue, so too they can highlight which positions are worthy of one’s attention. As such, prospectors can focus their efforts on what is more likely to pay out and be of interest.
However, using AI can lead to over-applying: that is, pursuing and winning too many job offers. When one has devised a killer search criteria and found a way to automate much of the application process, chances are one will land more opportunities.
This leads to a welcome, but still uncomfortable conundrum: having to turn down a job offer. Unlike the AI that helped win the opportunity, this is something that at the moment can not be addressed with technology. To put it simply, one has to roll up one’s sleeves and bite the bullet. One has to decline in person and in a way that is graceful so as to not burn a bridge that might day, need to be crossed.
Too Many Opportunities
Knowing how to decline a job offer you have already accepted is not something one learns naturally. If anything, it is usually something one learns by making mistakes.
Of course, there are some obvious do’s and don’ts, but suffice it to say that most of us learn how to politely decline by embarrassing ourselves at least once or twice. The difference though, between declining an invitation to dinner or meeting up, and joining a company, is that friends tend to be more forgiving.
For the moment then, while AI is turning up more opportunities and reducing the decisions we make by muting our biases, we still have to do some things the old-fashioned way: that is, providing the personal touch.
It is odd to think that someday, even declining a dinner date will be something that our personal AI will handle for us, but until then, we will continue to be polite as our parents taught us and say, thank you, but no, thank you.