The age of Big Data, Machine Learning and Predictive Analytics promises some truly revolutionary changes in the way we select and filter in a modern HR process and narrow down the candidate pool. We are told that these systems can reduce OPEX/CAPEX and speed up the selection process, add quality to our hiring by spending time only on those applicants that matter.
I personally have a love/hate relationship with Big Data, but more about that later. Let’s first take a look what modern HRM systems promise.
For those unaware: these are the systems operating behind the scenes after you have submitted your CV for a specific job. Many are still pretty “dumb”, e.g. nothing more than a simple cloud based databases which map your CV to a specific job within the system and support a simple workflow within HR.
Some newer platforms which are either hitting the market now or have already been implemented by more tech-savy employers themselves are a different breed though. They might hook into system like watson or similar analytic platforms with state of the art artificial intelligence (AI).
They don’t just map skills from your CV to the job-spec and produce a ranking, but attempt to analyse your personality and character traits to decide if you will be a strong, mediocre or unlikely fit to the organizational culture.
Here is an overview of what many of the modern systems promise [source] (please bear with me throughout the spammy marketing tone in these bullets):
- Ability to screen candidates using smart technology: Whether candidates submit their applications using an online application form, through a job board or through your internal career site, the candidates are screened and automatically ranked on specific qualities and skills.
- Automatic scanning for exceptional talent: Not having a relevant vacancy should not mean missing good candidates. You can set up automated queries to scan each enquiry for a specific profile, generating an automated notification when a candidate fitting your profile applies.
- Integration of 3rd party assessment tools: You may choose to increase the predictability of your screening and selection process by integrating market-leading tests and assessment tools from 3rd party test vendors to help make more objective hiring decisions.
- Automated profiling and Talent Pool creation: Once you have built your talent pool searching within this invaluable resource will become your first step in uncovering talent for new opportunities. Our solution ensures that information from interviews and assessments are automatically added to the candidate’s profile, providing you with an even wider criteria base for screening when searching in the talent pool.
- Weighted Scoring: Virtual Psychology’s e-Recruitment solutions give you the ability to weigh questions with a score, based on responses, which allows the recruiter to assess applicants at a glance.
Let’s take a look at the currently undisputed leader in AI technology: Watson. Developed by IBM is probably the most advanced AI engine, comes with an API allowing integration into pretty much any product.
You can take Watson for a spin by visiting http://watson-um-demo.mybluemix.net/ and check what it says about your personality by pasting your blog posts, LinkedIn summary, or job application (hint: cover letter) inside. I did a quick test-run throwing in all my blog posts and was astonished by how well Watson knows me. (Between you and me I felt Watson understood me better than by my ex-wife, but that’s another story.)
The “techie” in me loves this sort of stuff because it’s a simple interface that hides the arcane complexity and produces results which are truly amazing (I’d be interested to hear feedback of how well you thought Watson knows you.)
Before your eyes glaze over in awe, and decide to eliminate the risk of bias in decision making by outsourcing the hiring process to a machine, please take a critical look and ask yourself: Aren’t you automating bias?
Apologies for being stoic (aka “2000 and late”) in my thinking. So let’s take a look at how the worlds most advanced AI system judges some well known but ‟lesser liked” personalities from recent history:
1) Joseph Mengele (aka Angel of Death) gets the following result when we feed the loving letter to his wife into Watson:
You are social, somewhat verbose and can be perceived as shortsighted.
You are assertive: you tend to speak up and take charge of situations, and you are comfortable leading groups. You are unconcerned with art: you are less concerned with artistic or creative activities than most people who participated in our surveys. And you are respectful of authority: you prefer following with tradition in order to maintain a sense of stability.
Your choices are driven by a desire for sophistication.
You consider helping others to guide a large part of what you do: you think it is important to take care of the people around you. You are relatively unconcerned with tradition: you care more about making your own path than following what others have done.
Well done Herr Mengele, Watson thinks you are highly suitable for the job in most tech-companies. Your ability to assist and guide others would be a great asset to our organization. However we feel that your desire to take charge and speak your mind as well as your tendency to make your own path instead of following what others have done, would make you a more suitable fit for a fast-paced tech start-up than an established firm like ours.
2) Watson’s thoughts of Osama Bin Laden in his letter to the American people:
You are confident and heartfelt.
You are laid-back: you appreciate a relaxed pace in life. You are confident: you are hard to embarrass and are self-confident most of the time. And you are calm under pressure: you handle unexpected events calmly and effectively.
Your choices are driven by a desire for modernity.
You are relatively unconcerned with tradition: you care more about making your own path than following what others have done. You consider helping others to guide a large part of what you do: you think it is important to take care of the people around you.
Maybe conspiracy theorists were right after all, and, 9/11 was an inside job? Maybe Osama is in fact still alive spending his days surrounded by forward thinking hipster friends in Brooklyn? I guess we need more data to say for sure.
Bad jokes aside, Watson’s predictions resonate with us especially when he is charming. He confirms what we want to believe: that we are special, have leadership qualities and really, really care about others. We tend to accept something nice about ourselves eagerly and without critical thinking. Don’t use AI to judge the personality of others – when most of times we can’t even trust ourselves with such judgement.
Another problem with such a system is that it never forgets. Once you are labelled it’s hard to shed such a label. People change and should be allowed to make mistakes.
Last but not least AI prediction (even it works 100% correctly) in psychological analysis becomes ineffective when these tools are used to craft or sanitize the input to make them conform. A cover letter, CV or any writing or data that is massaged to satisfy the tool is one of the biggest problems with data. When used in such intrusive ways leads us down a path of self-censorship and a world where only machines will read what you have to say because everyone else will find you utterly boring.
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