However, some experts worry that this approach may come with hidden costs. Hilke Schellmann, a journalism professor and author of The Algorithm: How AI Can Hijack Your Career and Steal Your Future, argues that AI’s biggest risk to job seekers isn’t about machines taking over their roles; it’s about quietly keeping them out of those roles altogether.
This reliance on AI is growing fast. Bloomberg Intelligence projects that the generative AI market, valued at $40 billion in 2022, could soar to $1.3 trillion over the next decade.
Yet, as companies place more trust in these tools, they may be closing doors to qualified candidates through biases buried deep in the technology; without even knowing it.
Also Read: The ABC Model for Effective Remote Employee Onboarding
How AI Bias Slips In
AI bias in recruitment is the unintended effect that occurs when tools built to find the best fit echo the past.
We know AI algorithms feed on the data they’re trained on, digesting patterns that shape their decisions. But when that data carries human biases, AI can mirror those patterns, reinforcing the very barriers it was meant to break.
Take Amazon’s hiring tool from 2015. As Reuters reported, the system, designed to spot top candidates, began scoring resumes with the word “women” lower. It’s obvious that AI had picked up cues from past hiring data that favored male applicants and repeated the trend.
Amazon eventually pulled the plug on the project, but it left a nagging question: How many other AI systems might quietly inherit these same biases?
The issue doesn’t stop there. In a recent analysis, Bloomberg reported that some AI hiring software favored resumes based on certain names. Resumes tied to one ethnic group ranked higher, while others consistently landed lower. These findings reveal that AI meant to level the playing field, can sometimes tilt it in unexpected ways.
For companies relying on AI in hiring, these hidden biases may go unnoticed. However, for job seekers, AI’s quiet influence can close doors with little explanation, leaving companies to pass over top talent unknowingly as well.
How AI Bias Affects Hiring Decisions
AI’s expanding role in hiring has also revealed a new kind of blind spot. As we’ve seen with Amazon’s recruiting tool, algorithms can quietly overlook capable candidates who don’t fit a predefined mold. Ironically, this bias risks filtering out the very talent companies are eager to find.
According to the American Staffing Association, AI screening is now in place at 42% of companies, and its influence is already shaping hiring pools in unexpected ways.
Candidates with fresh ideas, unique perspectives, or varied backgrounds may be overlooked, not for lack of ability but simply because they don’t match the criteria the algorithm has learned to favor. When companies rely on these tools to filter and rank, it’s easy to see how top talent can slip through the cracks, quietly waning the quality of hires.
This isn’t a hypothetical concern. Recently, Workday faced a class-action lawsuit over claims that its AI screening software discriminated based on race, age, and disability. The case, led by a job seeker who says he was passed over due to these biases, raises questions about how AI bias may shape hiring on a larger scale.
Examples like this show that AI bias doesn’t just impact individual candidates; it can affect entire teams, narrowing perspectives and limiting the adaptability and innovation that diverse talent brings.
For companies relying heavily on AI, missing skilled candidates due to these biases can weaken their talent pipeline and damage their reputation in a competitive job market.
How Companies Can Address AI Bias in Hiring
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