Technology is evolving and changing the dynamics of various industries every day. And Artificial Intelligence and Machine Learning are technologies that are creating an impact in multiple markets. Albeit it is fun for us to interact with AI on Alexa, Apple’s Siri, or Google Assistant, AI has now entered the field of tech hiring, and it is not as exciting as it should ideally be.
Many companies have turned to digital interviews, automated assessments, and data analytics to screen candidates. The IT industry stands for diversity, equity, and inclusion. Still, when it comes to AI – it does more harm than help if companies aren’t careful and strategic about their hiring processes.
If you are looking to hire the right tech talent, then it is vital to note that in different contexts, AI in hiring amplifies the very same problems one thought it would solve. AI was introduced in recruitment as most companies felt it would root out biases and increase fairness in candidate evaluation. Although, you would be surprised to find the exact opposite happening.
Let’s see why AI might not work well for tech hiring.
The Dangers of Bias in AI and ML in Hiring
AI algorithms require vast data to give results with accuracy. Unfortunately, the system is trained with the help of past data, which can affect good candidates. For example, if your datasets reviews are from companies that have historically hired few women and minorities, your algorithm will spit out the same biases.
For the uninitiated, bias here means an error that arises from faulty anticipations in the learning algorithm. Another bias for the tech industry is its historical issues with tech diversity. So, training your algorithm on historical hiring data can derive erroneous results.
It is tough to gauge whether the hiring process through AI software doesn’t have biased effects or isn’t inherently limited. In fact, various systems show biased effects based on disability, race, and gender.
How Does AI Function?
It is essential to understand that AI functions best when it has massive amounts of objective data, which is next to impossible in hiring. The candidates do furbish data on educational background, previous job experiences, and other skill sets. However, often with AI, such data is mixed up with complex intersections of biases and assumptions.
Moreover, these data samples are small and difficult to measure, because of which the outcomes are unclear, which means AI can’t learn what worked and what didn’t.
As a result, as the algorithms perform more of these biased actions, the more it learns to repeat them. Also, the system codifies bias which does not project a great image of forward-thinking companies in front of potential recruits. When such companies scrutinize their hiring software, they come to realize that their AI is taking terrible actions, for reasons beyond their control, and if a human performed them, it would lead to termination and legal complications for the organization.
Even New York City is making laws to curb using AI in hiring decisions so that all employees get a fair chance.
Why Can Relying on AI in Hiring Make You Lose a Good Candidate?
No Human Judgment
Recruiters and hiring managers want to build a relationship with the candidates, but they feel it is challenging to give equal time to everyone. So, they feel AI can act as a representative to the candidates and help with the outreach process.
Unfortunately, AI can only predict different patterns and human judgment is necessary for screening candidates. In many cases, AI gets stuck as it reads insufficient data and suggests the same candidates to you repeatedly.
Less Accurate
AI functions based on the data you feed in. It will not be accurate enough for your tech hiring process if you have insufficient or inadequate data. For example, a candidate might be completely fit for the job, but he will fail to qualify in the AI’s list for using a different style of bullet points in their application or resume!
Dependency on Keywords
AI gives a lot of importance to keywords while screening candidate applications. Candidates can figure out this loophole and add specific keywords that can have the potential to trick the system.
It can make them seem more qualified than they already are. AI cannot tell you this difference and will recommend them as suitable candidates to you.
Lacks Personalization
AI cannot build solid relationships with candidates. It is excellent for answering the candidate’s FAQs about the job, but it cannot replace the human touch.
You can select an AI software that analyzes people’s expressions, tone of voice, and other aspects of their personalities. But, all the results are based on data that can be biased. Instead, human intervention can judge all of this much better.
Why did Amazon Stop Using AI in Hiring?
Let’s have a look at where AI went wrong in Amazon’s hiring process
Amazon has been building computer programs to review job applicants since 2014. Automation has played a significant role in Amazon’s eCommerce dominance. So, they created an AI hiring tool that gave their candidates stars from 1-5, much like the shoppers’ ratings for their products.
They wanted their tool to give out the top 5 resumes when they added 100 resumes to it. But, by 2015, they realized that their system was not gender-neutral for candidates applying for technical and software jobs.
It is because the AI algorithm was trained to screen candidates based on observing patterns in applications submitted to the company over the span of 10 years. Most came from men who dominated the tech industry during that time.
As a result, the system rejected applications with words like woman or female. Amazon edited the program, but there was no guarantee that the machine would choose candidates without discriminatory biases.
Finally, the company disbarred the tool as it had a lot of complications.
Should You Use AI in Hiring?
The straightforward solution is to stop using AI in hiring altogether. That said, AI can still be implemented in hiring, provided it is thoroughly vetted from time to time and includes human intervention at every stage necessary. Many time-strapped companies might find this solution challenging, but it doesn’t have to be that way.
If you are looking to hire good talent in the tech industry, you can get help from a tech hiring platform like Workfall.
It helps you to find the ideal candidate in tech for your business without compromising the factor of human touch. The best part is that you can hire for specific projects based on your needs. You can decide on a cost and pay the candidate based on their work hours.
What Does Workfall’s Hiring Process Look Like?
Workfall has multi-layered filtering criteria that weed out the mediocre and handpick only top-notch candidates. Our hiring process matches the best of the best software developers to your tech needs. You get to hire them based on your requirements for 3 months, 6 months, or 12 months.
We have a stringent 5-step screening process that involves:
- Application
The candidate has to fill in their details in the application form and send it to us. - Technical Screening 1
We evaluate the candidate’s technical profile with their skill set, past experiences, and current expertise. - Technical Screening 2
This round includes a detailed evaluation of the candidate’s tech competence which involves coding and architecture assessments. - Personal Screening
Someone from our team gets in touch with the candidate for a personal interview round. We specifically do this to assess the candidate’s language skills, fluency, communication, and overall personality. - Final Review
We review the application and assessments for one last time, and if the candidate meets our quality standard, we induct them as a Partner.
Our processes have human intervention at each level which means that the entire screening process is intact, and there is no use of Artificial Intelligence and Machine Learning – leaving no room for inefficiency in screening candidates. We have institutionalized our own set of internal quality checks, ensuring that the candidates meet the highest benchmarks.
If you are looking to hire tech talent, throw away your AI software and choose a platform that actually helps you hire genuine and promising candidates that are a complete fit for all your tech requirements.