Technological advancements are causing a shift in how employers find and hire job candidates. One of those advancements is the practice of algorithm hiring.
An algorithm is a computerized process typically consisting of multiple steps. In the case of a hiring algorithm, those steps are designed to scan and analyze compiled resume data. Companies use the data generated by hiring algorithms to identify applicants who are the best candidates for specific positions.
If you are currently looking for a new job or you are open to the possibility of changing positions, you may think a successful interview is the key to success. However, a company relying on algorithms to choose job candidates may rule you out before an interview is even considered. While you cannot completely control how an algorithm assesses you, understanding the process of algorithm hiring can help you prepare your resume so it comes out on top. Learn everything you need to know about how your resume is assessed using algorithm hiring practices below.
Algorithms are nothing new in the technological world, and they are commonly used in computer-related industries for multiple purposes. However, the influence of this artificial intelligence on the job hiring process is relatively new. A few years ago, the first algorithms used for hiring emerged, with various initial uses. Some algorithms analyzed speech patterns, while others compiled data from a uniform series of questions each candidate was required to answer. Overall, they were all used to make the hiring process faster.
Related article: Why is it important to have a great resume?
The use of algorithm hiring quickly became popular, especially in small startup companies. Some employers use the algorithms to help them find new recruits. Others create algorithm hiring programs and market them to other companies. Algorithm hiring processes are especially popular with large corporations, such as Amazon. In fact, they are now almost required due to the number of job applications such corporations receive.
There are two primary goals of algorithm hiring. One is to make the job search faster, both for you as a job seeker and your potential employer. A hiring manager who does not use an algorithm must read each job application manually and analyze all the data contained in every application to find the best candidate. If yours is the only application on his or her desk, the process is easy. However, when reading dozens of applications, facts are easy to mix up or miss entirely. The recruitment process also takes a lot more time this way.
Meanwhile, a hiring algorithm analyzes writing patterns or seeks specific keywords in all of the applications received. If the algorithm does not locate the patterns it is designed to seek on your application, your resume is thrown out of the pool. In that way, a recruiter or hiring manager can quickly identify the candidates that have the exact skills and experience for the job. This process can save a lot of time, particularly if the company is large and typically receives hundreds of applicants at a time.
The other goal of algorithm hiring is to reduce or eliminate bias. A human hiring manager often has preconceived notions about candidates, while a hiring algorithm does not. For example, although unethical and illegal, a hiring manager may exclude you from contention for a position due to such reasons as your:
A decision made by a hiring manager regarding your eligibility for a job may also have other psychological influences. For instance, if you interview for a job on day one of a week-long interviewing process, the hiring manager may choose someone else due to a phenomenon called narrow bracketing. Narrow bracketing is when a narrow data subset is analyzed. In this case, the hiring manager may have fresh opinions in his or her head regarding the most recent interviews conducted after the week-long process. Therefore, candidates interviewed on the final day may receive higher consideration.
A company can use algorithm hiring tools at any time during the hiring process. However, such tools are often most useful in the early hiring stages. No hiring manager wants to sift through dozens of applications. Therefore, if your application makes it through the initial algorithm-based vetting stage, you are likely to secure an interview. Once the field is narrowed down, the hiring manager may prefer to trust his or her instincts and get to know you through phone calls and face-to-face contact.
Related article: Resume Resources
Hiring algorithms are not solely reserved for analyzing job applications after they are submitted. Companies can also use them to analyze information you post about yourself online. Doing so allows hiring managers to seek you out and offer you jobs you did not apply to, if they think you are a good candidate for the positions they have available. This makes it possible for job offers come to you. However, you may not receive them often if the information you post onlne is minimal or portrays you in a negative light.
One of the biggest potential flaws with relying on algorithm hiring is an inability to consistently meet its primary goal of eliminating bias. The artificial intelligence governing such algorithms only works with the data it is given. When human company executives and hiring managers provide biased or incomplete data sets, the resulting hiring decisions made using algorithms are flawed. For example, if a hiring algorithm is created using data primarily taken from job applications submitted by men, the program is most likely to favor applications submitted by men in the future.
One company that encountered such a hiring algorithm flaw is Amazon. In 2014, Amazon began creating an algorithm designed to locate talented new employees quickly. Within a year, company executives noticed the the program gave higher priority to males applying for technical positions. As a result, Amazon discontinued the use of algorithm hiring.
Similar problems can arise in any company using faulty data when running a hiring algorithm. Such issues may go unnoticed for a short time. However, as diversity decreases, a flaw in the algorithm hiring process can become apparent. The resulting public relations difficulties may permanently damage the reputation of the company. For that reason, many experts indicate algorithm hiring still has a long way to go before it is perfected. However, those opinions are not stopping the use of such practices, which are becoming increasingly more common.
Related article: How to Beat Resume Bots