The Ethics of AI in HR: Can We Build a Bias-Free Workplace?

The integration of artificial intelligence (AI) tools in core HR functions is no longer an exciting futuristic concept; it's a present-day reality reshaping organisational structures to unlock opportunities, streamline processes and improve decision-making. Across the entire spectrum of HR operations, from recruitment, talent management, and employee development to engagement, AI tools are markedly changing how new-age HR frameworks design, implement and measure workforce strategies. However, this transformative power comes with a critical caveat: the pressing challenge of ensuring fairness, transparency, and adherence to ethical standards.

The potential for embedded bias is one of the primary reasons why employers are being cautious about automating entire workflows. The pursuit of a truly equitable workplace demands an exploration of AI's ethical implications within HR, ensuring that technological advancement doesn't perpetuate or amplify existing societal inequalities. As we prepare to host the largest Filipino HR event - People Matters TechHR Pulse Philippines ‘25 - with leading minds and experts next month, we delve deeper into real-world case studies, use cases, and the regulatory landscape surrounding AI in HR.

How AI is transforming HR decision-making: A closer look

The influence of AI in fundamentally rewiring every aspect of HR is multifaceted and profound. One reason why it’s relatively easier to automate many HR processes is that workforce management produces rich and comprehensive datasets, and it’s easier than ever to capture and analyse these data points. Take hiring, for instance; AI-powered applicant tracking systems can not just identify ideal candidates but also assist in assessments, streamline the candidate experience and simplify the interview process. It’s not just AI’s ability to parse through thousands of resumes to shortlist the candidates with accuracy that is helping recruiters, it’s also the ability to write job descriptions instantly, write emails to candidates, and analyse the success chances of each candidate. Companies like Unilever have been some of the early adopters in using AI tools to analyse video interviews, where candidates are asked the same set of questions. The AI technology uses natural language processing and facial recognition to assess responses, behaviour, facial expressions, word choice and tone of voice. 

Similarly, AI is being used to analyse large data sets of performance management by deploying a variety of tools to assess employee productivity, engagement, communication and morale. Besides using AI to assess skills gaps and identify opportunities for professional growth, like at IBM, many organisations also use AI-powered HR chatbots to answer routine employee queries, freeing up HR professionals for strategic initiatives. Macro-level data on the workforce and engagement is also helping HR leaders predict employee turnover and forecast future staffing needs, enabling organisations to plan proactively.

Want to get an exclusive sneak peek into how leading Filipino industries are using AI in HR? Register for People Matters TechHR Pulse Philippines ‘25 and get exclusive early-bird discounts! 

The risks of bias in AI-driven workforce management

It’s important to remember that AI tools function and learn based on the data provided to them. This makes them vulnerable to potential algorithmic bias because of the historical data that they learn from favours a particular demographic for hiring or promotion, the tools may perpetuate this pattern, leading to unintentional discrimination. This isn't a theoretical concern; it's a documented reality, as critics have pointed out about the potential for bias, particularly against individuals with certain accents or cultural backgrounds. Even behemoths like LinkedIn identify this as a cause for concern as well. 

The challenge compounds when you consider the implications of decisions based on algorithms. Say a candidate was erroneously rejected by an AI tool - who do they approach for recourse? Is the recruiter, the tool or the provider of the tool responsible for this decision? Furthermore, how can the recruiter, with a limited understanding of the tool’s technical intricacies, ensure that this bias isn’t carried forward? While many AI companies have opened their source code for public scrutiny, others have not. This ‘black box’ nature of some AI algorithms further complicates matters. The complexity of deep learning models makes it difficult to trace the origins of specific outcomes, raising concerns about accountability and fairness.

The regulatory and ethical implications of this are even more complex. Consider a high-performing employee passed over for a promotion (or worse, wrongly terminated) and who uses the available remedial options to seek relief. In the absence of clear laws regarding the use of AI in HR, where does the buck stop? 

Want to explore the answers to these questions with leading industry experts at People Matters TechHR Pulse ‘25? Check out the list of speakers!

Strategies to ensure ethical and fair AI Usage in HR

Mitigating bias requires a comprehensive strategy that will need coordination between various stakeholders from the business, tech and government sectors. Firstly, data diversity in training AI tools is essential. Tech companies must ensure that AI models are trained on datasets that accurately represent the population, avoiding over-representation of specific groups. Data augmentation techniques can artificially expand datasets to include underrepresented groups, reducing the chances of bias.

Secondly, algorithmic transparency is crucial to identify and continuously correct AI decision-making. Organisations should strive to use interpretable AI models or develop methods to explain the decision-making process to users who are not privy to data analytics and algorithms. This allows users to conduct audits and assessments to identify potential biases at regular intervals. Regular monitoring and testing of AI systems (both internal and external) are also necessary to detect and correct any discriminatory patterns.

Thirdly, human oversight is indispensable, at least until we find the solutions to the challenges discussed. Organisations and regulators should aim to design policies where AI accentuates, not replaces, human judgment. HR professionals should retain the final decision-making authority, ensuring that algorithms are used as tools to analyse and inform, rather than dictate, outcomes. Implementing ethical guidelines and frameworks for AI usage can further provide a structured approach to addressing these challenges, also helping demarcate the roles and responsibilities of different actors in the process. 

From a regulatory and compliance standpoint, there is an urgent need to create easy-to-understand and implement frameworks that ensure transparency and fairness. The GDPR of the EU and the ICO of the UK have given some overarching guidelines on the use of AI, but more universal guidelines and frameworks are becoming indispensable as we increase the use of AI tools in everyday business decision-making. In the absence of such models, employers and HR leaders must also act proactively in addressing these considerations by implementing robust data governance practices and conducting regular audits of AI systems. Moreover, fostering a culture of ethical AI usage through training and awareness programs is a conscious choice that organisations must make to ensure that AI is used responsibly.

We will explore these strategies in greater detail at People Matters TechHR Pulse Philippines ‘25 on 14 May at Marriott, Manila. Check out the conference agenda!

To sum up, while AI has the potential to revolutionise HR practices, enhancing efficiency and decision-making, these benefits come with the risk of bias and discrimination. To address the ethical and regulatory challenges that come with the adoption of AI tools, we need industry-wide strategies to ensure data diversity, algorithmic transparency, and human oversight. Organisations can build a bias-free workplace, and the development of clear regulatory frameworks and ethical guidelines is a significant step in responsible AI adoption. However, as AI continues to evolve, ongoing dialogue and collaboration between HR professionals, technologists, and policymakers are essential to ensure that these technologies are used ethically and equitably. With the right strategies in place, AI can help create a more equitable and efficient workplace for all.

Interested to learn more about how AI will change the workplace? Sign up for People Matters TechHR Pulse Philippines ‘25 today!