Recruiting teams nowadays face a contradiction: they’re posting more positions than ever, yet struggling to attract the right candidates.
Artificial intelligence (AI) promised to solve this problem by bringing speed and scale to the hiring process. But evidence suggests that unchecked AI systems can amplify the very biases they were designed to eliminate. Amazon learned this the hard way at the dawn of AI’s popularity in 2018 when its experimental recruiting tool taught itself to favor male candidates, automatically downgrading CVs that included the word “women’s”.
But in 2025, organizations that implement AI thoughtfully are achieving measurable progress on diversity goals.
Companies using AI strategically are building more inclusive workplaces while maintaining efficiency.
Transparency is the foundation of ethical AI. When candidates understand how decisions are made, we earn their trust — and that’s essential in every market. My name is Yevhen Onatsko, I’m the Country Manager for the U.S. at Jooble, and in this article, I want to share three evidence-based approaches the team at the job aggregator Jooble is using to leverage AI for fairer hiring outcomes.
Most discriminatory hiring practices don’t occur during final interviews. They happen much earlier, in who sees your job posting, how it’s written, and who feels encouraged to apply.
Research shows that women are significantly less likely to apply for positions featuring “masculine-coded” language like “competitive” or “rockstar.” Tools such as Textio use augmented writing technology to identify biased phrasing and suggest gender-neutral alternatives. This approach helped Atlassian increase the number of female technical hires by 80 percent in a single year.
Immediate Action: Deploy AI-powered job description tools to rewrite postings with inclusive, accessible language. Platforms like Textio, and Applied specialize in this analysis.
Language that discourages female applicants:
AI cannot create fair hiring outcomes if qualified candidates never submit applications in the first place.
Traditional screening methods often reward confidence over competence. Newer assessment tools evaluate candidates through structured, neuroscience-based exercises rather than subjective impressions.
Comparing Screening Approaches
| Method | Process | Bias Risk | Scalability |
| Manual CV Review | Recruiter evaluates résumés | High (influenced by names, schools) | Low |
| AI CV Parsing | The algorithm sorts by keywords | Medium (depends on training data) | High |
| AI Behavioral Assessments | Candidates complete neuroscience-based exercises; results are compared to role requirements | Low (when properly calibrated) | Very High |
Unilever implemented Pymetrics to assess candidates through behavioral games before conducting any interviews. This approach increased diversity by 16 percent while maintaining performance standards.
Immediate Action: Consider incorporating AI-powered behavioral assessments into early screening. Platforms like Pymetrics and Hirevue can reduce unconscious bias before human reviewers enter the process.
Read also: The Most Wanted Jobs and Searches in Summer 2025 on Jooble
Many technology providers claim their AI “eliminates bias.” But that assertion requires scrutiny, not acceptance at face value.
Demand transparency from your vendors. Ask these questions:
Vendor Accountability Checklist
At Jooble, our job feed algorithms undergo continuous fairness testing. We manually audit performance across demographic segments to identify and correct unintended disparities.
Bias in AI systems isn’t always obvious. Sometimes, it hides behind perfectly logical features like language fluency or tone of voice. A 2025 study by the University of Melbourne revealed that AI-powered video interview tools are significantly more likely to misjudge candidates with strong accents or disabilities.
In some cases, the error rate for non-native English speakers reached 22%, potentially eliminating qualified applicants simply because their speech didn’t match the algorithm’s trained “ideal” profile.
Artificial intelligence is a tool, not a solution. It can scale your efforts, identify patterns human reviewers might miss, and introduce objectivity into inherently subjective processes. But it cannot function autonomously. People should train these systems, monitor their outputs, and challenge their assumptions.
When implemented with appropriate oversight, AI can transform diversity aspirations into measurable outcomes, helping companies hire more effectively and equitably.
Read also: Top B2B Marketing Trends in Recruitment: Jooble’s Insights
At Jooble, we believe inclusive hiring starts with intentional systems. That’s why we continuously audit our algorithms, track how they perform across demographics, and adjust to eliminate hidden bias.
Want to ensure your recruitment efforts reflect both performance and fairness?
We’d love to help.
📩 Reach out to us: salesteam@jooble.com
👉 Or start posting your open roles right here
Let’s build a better hiring future together!
