The huge potential of technology to reshape the role of the modern HR professional is striking.

In a world of big data, there is a vast quantity of information on employees and job candidates that can be used to improve outcomes for employers – in recruiting and retaining the best talent, developing HR strategy and ensuring a diverse workforce with equal opportunities for all. Artificial intelligence (or “AI”) has a significant role to play in helping HR to do this.

To take just one example, in an increasingly competitive job market, an organisation may receive applications from hundreds of highly qualified, hopeful graduates for just a few vacancies. Often, it will take a disproportionate amount of human effort to sift through them. Crucial experience, context or personal attributes may be lost in the morass of information. Application forms may be divided among several people who each take a slightly different approach. Some may not be given due attention, simply because they are considered at the end of a long day. As a result, gifted candidates may be overlooked due to human fallibility or unintentional bias.

To meet these challenges, AI systems might be put to effective use in conducting an initial review of applications, to produce a shortlist of candidates for interview. Similar automated decision-making processes could be deployed effectively in other scenarios – for example, in making bonus assessments or recommending promotions. This would, in turn, free up both HR and management to focus on other things.

However, in recognising the opportunities that AI brings, we must also be mindful of the possible pitfalls. In particular, workers and job candidates are protected from discrimination related to certain protected characteristics (such as age, disability, sex, race, sexual orientation and religion or belief). When asking machines to make decisions for us, there remains a risk that they will throw up potential discrimination issues.

In practice, very few employers are likely to use AI to make decisions that they know will result in less favourable treatment because of a protected characteristic (known as “direct discrimination”). However, what about unforeseen discriminatory outcomes arising from the use of AI?

For example, a machine may make automated decisions (or influence humans in making non-automated decisions) across a large population with a roughly equal gender split, but which inadvertently place women at a particular disadvantage. Unless the approach can be objectively justified as a proportionate means of achieving a legitimate aim, it will constitute unlawful ‘indirect discrimination’.

Similarly, where employers have a duty to make reasonable adjustments to level the playing field for disabled workers, this would need to be factored in to any machine learning processes.

Machines have the potential to make more objective, consistent decisions than humans. They can be more reliable, more accurate and work 24/7 if needed, without getting tired or distracted. However, they are not foolproof and humans may still be required to intervene and manage any unintended outcomes.

So how should organisations manage this risk? In my view, the answer lies in the end-users of AI solutions working together with those who create them. As a starting point, they could consider adopting internal guidance for employees who use (or, as the case may be, develop) AI tools and an external policy or agreement which sets out clearly how discrimination issues will be managed.

There are also questions over who might be liable for any discriminatory conduct. Any of the employer, the AI solution provider or even the individual employee who uses it might be on the hook and allegations of discrimination may also bring reputational damage. Therefore, it makes sense to adopt a collaborative approach that is aimed at spotting issues early, agreeing who is responsible for putting them right and refining automated processes to avoid repeat mistakes.

This comment was first submitted to the Westminster Employment Forum on “The Future for Human Resources – technology and the changing role of HR professionals”.