As artificial intelligence becomes increasingly embedded in recruitment practices across the Philippines, concerns are growing that biased algorithms may silently exclude Filipino job seekers from fair opportunities.

According to the International Monetary Fund, women’s jobs are twice as exposed to AI-driven processes compared to men’s roles in the country, a disparity that raises red flags in the race to modernise hiring systems.

The question for many is this: is the promise of efficiency worth the risk of discrimination?

AI in hiring: Growing presence, growing concerns

From Metro Manila to regional hubs, HR teams across the Philippines are ramping up the use of AI tools in recruitment and streamlining everything from resume screening to candidate interviews.

Common platforms include resume scanners embedded in Applicant Tracking Systems (ATS), chatbots like Olivia and Gemini, video analysis tools, and talent intelligence software like Sprout Info and Payruler.

But while AI promises faster hiring and deeper insights into applicant suitability, it also inherits the historical biases baked into its training data. This includes the risk of penalising non-standard resumes, ignoring candidates with employment gaps, or deprioritising applicants with non-Anglo names or unfamiliar educational backgrounds.

In 2022, reports emerged of algorithmic systems screening out candidates based on Filipino surnames – an indication of how quickly AI can operationalise bias if left unchecked.

And although newer systems have been refined since then, the underlying problem persists: AI often reflects the biases of past human decisions rather than correcting them.

Who is most at risk? While all job seekers are potentially exposed to AI bias, the impact is far from equal as certain demographics are shown to be more at risk.

Data from the IMF and World Bank suggest that college-educated, urban, female, and younger professionals are the most likely to encounter AI-driven recruitment systems in the Philippines.

Women, in particular, are disproportionately concentrated in roles – such as clerical and sales jobs – frequently targeted by algorithmic hiring platforms. It means that even highly qualified female candidates could be unfairly evaluated by AI systems trained on datasets that reflect male-dominated historical hiring patterns.

A stark example comes from a now-defunct Amazon AI hiring tool, which downgraded CVs containing the word “women’s” and purportedly favoured male applicants for technical roles. It’s a cautionary tale that continues to haunt recruitment teams globally.

Geography also plays a role. Rural candidates in the Philippines often face barriers to accessing AI-reliant platforms due to patchy internet infrastructure and limited digital literacy.

As AI tools become the gatekeepers to formal employment, those without reliable access are effectively excluded from the process altogether.

Candidates from lower-income households face a similar challenge. If training data favours applicants from top-tier universities or corporate backgrounds, AI may unintentionally deprioritise job seekers from less privileged socioeconomic contexts, even if they are equally or more capable.

A gap in law and trust

Although AI-driven recruitment tools are widely adopted, the legal and ethical frameworks governing their use in the Philippines are still playing catch-up.

Concerns from both job seekers and HR professionals highlight a gaping trust deficit. According to a 2024 study by Greenhouse, nearly half of employed Filipino job seekers believe AI tools are more biased than human recruiters. It’s a sentiment echoed across HR forums and job search communities.

Some HR professionals have expressed fears about overreliance on algorithms, raising concerns about the erosion of human judgment and critical thinking in recruitment. Others worry that their roles may eventually be displaced by the very tools meant to assist them.

Despite these red flags, there’s no comprehensive AI regulation in place to safeguard against recruitment bias.

The Philippines’ proposed AI Bill of Rights (House Bill 7913) aims to set ethical boundaries and ensure algorithmic accountability. However, as of April this year, it remains stalled in Congress.

Meanwhile, the Department of Trade and Industry’s National AI Strategy Roadmap 2.0 acknowledges the risks of algorithmic discrimination but offers no enforcement mechanism to mitigate them.

Without legal repercussions, these well-meaning initiatives do little to curb the risks posed by biased AI systems in real hiring scenarios. A call for accountability and transparency Experts argue that bias in AI recruitment is not inevitable, but it does require deliberate action.

Knowing how AI is used in recruitment technology

Transparency in how hiring algorithms function is key, as is regular auditing to identify and rectify discriminatory patterns.

Employers must ensure their tools are trained on diverse and representative datasets, and incorporate human oversight into the decision-making process to flag anomalies.

Job seekers, too, are calling for greater clarity on how their applications are assessed.

Many advocate for AI to serve as a support tool rather than the final decision-maker, reserving ultimate judgment for qualified human recruiters who can consider context, nuance, and potential in ways no algorithm can.

To bridge the trust gap, government regulators, employers, and tech vendors must collaborate to develop and enforce standards that promote fairness. These include:

• Bias testing and auditability of all recruitment algorithms
• Clear disclosures to candidates when AI is used in decision-making
• Recourse mechanisms for job seekers to challenge automated decisions
• Education and upskilling for HR teams on ethical AI practices

Until these safeguards are in place, Filipino job seekers remain vulnerable to opaque systems that may unknowingly undermine their chances at employment.

AI has the power to transform recruitment in the Philippines, but only if its promise of efficiency doesn’t come at the cost of fairness.

As adoption accelerates, stakeholders must urgently address the silent risks of AI bias. Otherwise, the nation’s workforce transformation may unintentionally deepen the very inequalities it hopes to solve.