Recruiters today face a clear contradiction: they’re advertising more roles than ever, yet finding it harder to attract the right candidates.
Artificial Intelligence (AI) was meant to solve this — speeding up hiring and expanding reach. But in reality, unchecked algorithms can sometimes reinforce the same biases they were built to remove. Amazon learned this back in 2018, when its experimental hiring tool began favouring CVs containing the word “men’s” while penalising those mentioning “women’s.”
Fast forward to 2025, and the landscape looks different. Organisations that apply AI thoughtfully are now seeing measurable progress towards their diversity and inclusion goals. Used well, technology can both broaden opportunity and improve efficiency — but only when transparency is at the core.
When candidates understand how hiring decisions are made, trust follows — and trust remains the foundation of ethical AI.
I’m Yevhen Onatsko, Country Manager for the U.S. at Jooble, and in this article I’ll share three proven methods our global team uses to make AI a force for fairness in recruitment.
Bias in hiring rarely begins at the interview stage — it starts much earlier, in who sees your job ad, how it’s written, and who feels invited to apply.
Research shows that women are far less likely to apply for roles containing “masculine-coded” words such as competitive or rockstar. Tools like Textio can automatically flag this kind of language and suggest more inclusive alternatives. When Atlassian adopted this approach, it saw an 80% rise in female technical hires within a year.
Quick win: Use AI-powered writing tools like Textio or Applied to review and refine your job descriptions. They help remove bias, simplify your language, and make your roles more appealing to everyone.
Phrases to avoid: rockstar, ninja, competitive
Better options: collaborative, motivated, team-focused, results-driven
AI can’t deliver fair hiring outcomes if the right people never apply in the first place.
Traditional screening methods often reward confidence more than competence. AI-driven tools are helping to change that — replacing instinctive judgments with structured, science-based assessments.
| Method | Process | Bias Risk | Scalability |
| Manual CV Review | Recruiter reviews CVs manually | High – often influenced by name, education, or background | Low |
| AI CV Parsing | The algorithm sorts by keywords | Medium – depends on quality of training data | High |
| AI Behavioral Assessments | Candidates complete neuroscience-based tasks aligned to role requirements | Low – when tools are well-calibrated | Very High |
A good example comes from Unilever, which introduced Pymetrics — a platform using behavioural games to assess candidates before interviews. This approach increased workforce diversity by 16% while keeping performance levels consistent.
When designed and monitored responsibly, AI assessments can scale fairness without sacrificing quality.
Quick Win: Introduce AI-powered behavioural assessments early in your screening process. Tools such as Pymetrics or HireVue can help reduce unconscious bias before a recruiter even reviews a CV.
Read also: The Most Searched Jobs on Jooble: Summer 2025 Insights
Plenty of tech providers promise that their AI “removes bias” — but such claims should be challenged, not taken at face value.
Responsible hiring means demanding transparency and accountability from your vendors.
Ask these four questions before you sign:
At Jooble, we hold ourselves to these same standards. Our job-feed algorithms are continuously tested for fairness, and we manually review performance across different demographic groups to spot and correct any unintended imbalances.
Bias in AI isn’t always easy to spot. It can hide behind features that look perfectly logical — such as assessing language fluency, tone of voice, or facial expression.
A 2025 study by the University of Melbourne found that AI-powered video interview tools were far more likely to misjudge candidates with strong accents or disabilities. In some cases, non-native English speakers faced an error rate of up to 22%, meaning qualified people could be unfairly screened out simply because their speech didn’t fit the algorithm’s “ideal” profile.
Even the most advanced technology needs oversight. Without regular auditing and human review, what seems efficient can quietly become exclusionary.
Artificial intelligence is a tool, not a substitute for people. It can spot patterns, scale your efforts, and add consistency to processes that are often subjective. But it still needs human direction.
Recruiters and hiring teams must train these systems, monitor their results, and question their assumptions. Only then can AI truly support fair, effective, and inclusive hiring.
Used responsibly, AI turns diversity ambitions into measurable progress — helping organisations hire both more efficiently and more equitably.
Read also: B2B Marketing in Recruitment: The Top Trends to Watch in 2026
At Jooble, we believe that inclusive hiring doesn’t happen by chance — it’s built through intentional systems and constant improvement.
That’s why we regularly audit our algorithms, monitor their performance across demographic groups, and fine-tune them to reduce hidden bias.
Want to make your recruitment process both effective and fair?
We’re here to help.
📩 Contact us: salesteam@jooble.com
👉 Or post your vacancies directly on Jooble
Together, let’s shape a hiring landscape where every candidate has a fair chance — and every employer can hire with confidence.
