Artificial Intelligence seems to be taking over many areas in our lives today. One area that it could impact is job search and recruiting. In my career, I’ve been blessed with having a large network of friends and family who over the years have helped me navigate my career. I can confidently say that every job I’ve ever had was a result of networking. In fact, according to several surveys, anywhere between 70-85% of all jobs are found through networking. This dynamic may change through the use of technology. With the increased competition caused by globalization, companies are now turning to Artificial Intelligence (AI) to screen, and in many instances hire, candidates.
“During your job search, you must also be networking as much as possible, attending events, talks, lectures, and conferences where you’ll meet people you can add to your contact list.”
― Kate White, author and job search expert
I remember when I shifted careers and went from the semiconductor industry to being a Wall Street analyst, I used all my resources to find the job, then was introduced to the hiring analyst through a friend of a friend. However, my future employer put me through a rigorous interview process to make sure I could handle the job and get along with the team. Not only did I meet with the entire research department in Alex. Brown’s San Francisco office, I also had to write a mock research report and put together a financial forecast for a company in the segment I was proposing to cover. Today, companies are increasingly using a variety of AI-based software tools to analyze candidates’ various “characteristics” including facial expressions, scanning work samples, and analyzing social media content, among others. There are a few start-ups who have a strong presence in this segment, which we’ve profiled below:
HireVue calls itself the “Digital platform to build and coach a team”. The company combines digital video with predictive analytics to help companies recruit and build their teams. Here’s how it works:
Candidates introduce themselves using video (not a resume). The video is then put through the company’s data analytics to help identify the best fit (i.e. use data vs. gut-instinct). Managers then watch these videos to assess the candidates. The candidates are also put through a series of digital challenges and scenarios, which are then automatically scored and ranked by the company’s algorithms. These scores are then crosschecked vs. the company’s top performers. Once they’ve survived this man vs. machine obstacle course, only the “best” candidates are automatically scheduled for in-person meetings. The company has over 600 customers in over 140 countries. Clients include GE, Under Armour, Hilton, Delta Airlines, HBO, Morgan Stanley, among other top names.
Koru also uses predictive analytics and a written assessment to evaluate candidates. Their evaluation is based on 7 principles:
Grit (ability to stick with it even in hard times)
Ownership (integrity, proactivity)
Curiosity (creativity, asking questions, learning)
Polish (related to communication)
Teamwork
Rigor (ability to read and process data quickly)
Impact (real world problem solving)
Customers include Facebook, LinkedIn, Reebok, airbnb, among others.
Fama is a practical tool that automates the analysis of an individual’s public web presence to help businesses hire top performers. The company’s value is straight forward: their software scans the web using natural language processing to scan news coverage, blogs, and a person’s public social media presence. The tool is clearly useful to identify candidates with a history of violence, racism, and sexual content, among others. The company leverages AI to learn how candidates present themselves online, highlighting content that can affect job performance.
Originally backed by Y-Combinator, the company has developed advanced simulations for job candidates who are interviewing for non-technical positions like sales, customer support, or administrative positions. The simulations on Interviewed are extremely realistic, and include the use of mock tools like email and phone calls. Their AI engine can be used to check for “soft skills” such as empathy, as well as hard data driven tasks. The company uses machine learning to drive its tool. It has both off the shelf and customizable solutions, crossing virtually every industry. Customers include Uber, Fidelity, Zillow, and others.
While the jury is out on whether or not these companies will succeed, in our opinion, companies looking to hire qualified candidates should use a hybrid approach, heavily weighted towards human, not AI-based, interactions. Given that not every hiring situation is the same, outside of eliminating criminals or identifying incompetence/knowledge, we believe ultimately people should be responsible for hiring, not machines. After all, human interaction is what hiring is really about, not necessarily how smart a machine believes you are. Networking will continue to be a key ingredient in any job search for the foreseeable future. It would be a shame for our society to simply move into a AI/machine learning/bot-based set of algorithms.
BitNavi is a blog conceived by Karl Motey in the heart of Silicon Valley, dedicated to emerging technologies and strategic business issues challenging the industry.
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