Artificial Intelligence is changing the way companies, and their recruiters, hire people. Many recruiters think AI is a lifesaver because it helps sort through resumes quickly and finds the best candidates. But there’s a big problem: many recruiters don’t really understand how AI works or what it can’t do. This misunderstanding can cause a lot of trouble for people on the other end of the technology - those actually looking for jobs. Let’s take a closer look at the problems AI AI can create when recruiters rely on it without knowing its limits.
Too Much Trust in Automated Tools
- AI-Based Applicant Tracking Systems (ATS): Many recruiters use AI-based Applicant Tracking Systems (ATS) to help manage all the resumes they get. These systems look for certain keywords and qualifications to pick out the best candidates. But here’s the catch: these tools aren’t perfect and often cause problems for job seekers.
- Keyword Focus: ATS systems look for specific keywords in resumes. If your resume doesn’t have the exact words the system wants, it might not even get seen by a real person. This means even if you’re the right person for the job, you could be ignored just because you didn’t use the right words.
- Little to No Understanding of Context: AI systems still struggle to understand context. They can’t read between the lines. You might have the perfect experience, but if it’s not described in exactly the right way, the AI may not pick up on it. Recruiters who don’t understand this might miss out on great candidates because the AI doesn’t see the full picture.
- Little to No Understanding of Potential: I have yet to see and A! based tool built into an applicant tracking our sourcing system that truly identifies potential. In my 32 years of experience, I have hired many individuals that few would have hired based on experience, yet we hired on potential and have turned into rockstars!
Hidden Biases in AI
- AI Learns from Biased Data: AI systems learn from data they are trained on. If this data is biased, the AI will be biased too. Many recruiters don’t realize how much bias can be built into these systems. Biases go beyond skin color and gender, this can include thousands of accidental biases including where you live and what college you did or did not attend.
- Continuing Old Biases: If an AI is trained on data that reflects a company’s past hiring habits, it will likely continue those habits. So, if a company has always hired a certain type of person, the AI will keep doing that, even if the company wants to change.
Lack of Clarity in Decisions
- AI’s Mystery Decisions: One of the biggest problems with AI in hiring is that it’s not always clear how decisions are made. The systems are complicated, and it’s hard to understand why they make certain choices.
- The Black Box Problem: Many AI tools are like a “black box.” You put information in, and a decision comes out, but no one really knows how it got there. This lack of clarity can frustrate job seekers who don’t know why they were turned down.
- No Useful Feedback: Because recruiters don’t always understand how AI makes decisions, they can’t give good feedback to candidates. This leaves people in the dark, not knowing what they did wrong or how to improve for next time. With recruiter feedback already a problem, this just exacerbates the issue.
Ignoring the Human Touch
- AI Can’t Replace People: AI should help recruiters, not take over for them. But some recruiters rely too much on AI and forget the importance of human judgment in hiring.
- Overlooking Soft Skills: AI can’t judge soft skills like communication, teamwork, or cultural fit. These are things a human recruiter can pick up on through conversations and interviews, but AI just doesn’t have that ability.
- No Empathy: AI doesn’t have empathy. It can’t understand someone’s unique situation, like a gap in their resume due to personal reasons. A human recruiter can understand and see the value in someone’s unique story, which AI can’t.
- Declining Candidate Experience: More and more candidates just aren't feeling the love. Lack of timely feedback; no feedback; 18 interviews; etc.; all of these already play into declining candidate experience surveys. Remove the human element and watch the numbers decline at an even faster rate.
Forcing Candidates to Fit a Mold
- Pressure to Be the Same: With AI being used more and more in hiring, candidates feel pressure to fit a standard mold just to get through the system.
- Generic Resumes: To get past AI filters, many candidates end up using the same kind of language and formats in their resumes, making them all look alike. This focus on fitting a mold can hide a person’s true skills and creativity.
- Losing Authenticity: When candidates change their resumes just to match what the AI is looking for, they might hide their real strengths and experiences. This can lead to a less diverse group of hires, which isn’t good for any company.
Privacy and Legal Issues
- Concerns About Data Use: Using AI in hiring also brings up issues about privacy and data security. Many candidates don’t know how their information is being used, and recruiters who don’t understand these issues could accidentally break privacy laws.
- Data Misuse: AI systems need a lot of data to work well. If this data isn’t handled properly, it could be misused or leaked, causing legal trouble and making candidates lose trust in the company.
- Following the Rules: As more laws are made about using AI in hiring, recruiters need to understand these rules. Not knowing them could lead to discrimination or other legal problems, which could hurt the company.
AI has a lot of potential to make hiring better, but it’s not a perfect solution. Recruiters need to understand what AI can and can’t do and use it alongside human interaction and judgment. Relying too much on AI can lead to biases, a lack of transparency, missed opportunities, and even legal issues.
To make AI work well in hiring, recruiters need to educate themselves on its limitations and use it wisely. It’s time to understand AI’s role in recruitment and use it in a way that truly helps everyone, including the candidates.
