Automation and AI: HR directors must keep a finger on machine learning

Image: Shutterstock

Using AI to recruit and retain employees is hugely advantageous in terms of establishing a holistic and cost-effective process, but it’s vital that HR directors should retain full control of implementing systems so that bias and non-compliance do not creep in, writes Dr Alan Bourne.

In our experience, if used responsibly, AI and machine learning can help organisations find more best-fit employees, eliminate bias and make the whole recruitment journey more efficient and better for the candidate. We are using it with clients to improve their organisational agility and to create fair and robust development processes. In the future we see it not only supporting a wide range of assessment functions, but also ensuring a better and more effective employee journey, increasing the ability of organisations to be agile and adaptable.

However, one of the key issues HR directors face, which other sector practitioners are better used to dealing with, is linking technology and data integration. For AI and automation to work effectively, the data points need to link up and integrate so that there is a continuous feedback loop.

For example, if you look at the marketing space, there are not only tools that measure how people interact with brands online, what customer’s motivations are, and when or if they become repeat customers, but all those different points in a customer journey now link up, making it easier to organise, learn from and apply the data.

Integrated employee journey

It’s important to understand an employee journey in the same way as you would a customer journey, and to do this, you need a much more integrated landscape. For example, on the recruitment side, currently a company might go to one supplier for video assessment, one for a digital assessment, do some of the assessment on paper, and then hold interviews where no data is recorded. If you join up all those processes and capture the data in one platform from the whole recruitment journey, not only do you then have the ability to start automating it, but you are able to start applying the learning through human and artificial intelligence to your talent management and planning as well.

The fragmented technology landscape in HR is standing in the way of progress. Once this is addressed then the readiness by most HR directors to make the most of AI can really be applied. We need to be able to slot in platform-level solutions at each stage of the talent management cycle, such as assessment, L&D, or even as people leave the business. This is crucial to be able to supply an organisation with insights into their workforce that drive key markers of business success such as productivity, retention, and employee happiness; and can equip organisations for future success.

There are two overarching points to be aware of when applying AI to use in HR: it needs to be error free and grounded in sound ethics about how it will be used, and it must be HR-led.

AI must be blemish-free

As with driverless cars and cancer screening, we believe that AI in assessment has the potential to do great good in ensuring the best fit employees are selected as fairly as possible, but as in those examples, it cannot afford to make mistakes; it has to be free of systematic bias or error. Any use of AI in an organisation must be guided by an ethical framework and overseen by processes not directly linked to the technology being used. That could be an internal human resource, an external advisory board, and/or the use of AI itself to audit other forms of AI. The key is ensuring that humanity, laws, regulations and ethics guide these principles.

Secondly, AI cannot be applied to HR systems simply by the technology department or investor-led tech-consultants, it has to be led by the HR director in order to combat bias, increase diversity, ensure the system is compliant and accurate, and that the technology is responsible and explainable. The HR function has a critical role as guardian of ethics and good practice in the organisation, to guarantee that the technology is applied with these requirements at the forefront of planning.

Using machine learning to optimise the recruitment process

For example, by tailoring an AI-led assessment programme to an organisation’s specific requirements, not only are you able to lean on the experience of a hiring department that has an ingrained ethical code, but you can ensure that the ethics and values of your organisation are taken into account in the technology, as well as assessed in the candidate. This is done by using machine learning to optimise the process, constantly refining the algorithm throughout the campaign to increase fairness, visibility of process and accuracy.

Importantly, HR managers need to be able to explain how their technology made decisions and arrived at its conclusions in the worst-case scenario because at a discrimination case in court or tribunal – there is no acceptable “black box” answer. By ensuring this “explainability” is built into the specifications, algorithms and processes of the program from the beginning, the alternative “glass box” approach means you engender trust from both applicants and employees, and ensure a level of transparency that holds up to scrutiny. The conventional rules such as the Equalities Act still apply, bias in recruitment is still subject to the same laws and always will be. Any recruitment process will need to be transparent and explainable, which is why it’s so important to include experts on HR law right from the design stage.

HR must recognise AI risks

As well as applying AI and machine learning to the HR processes to optimise and future-proof an organisation’s workforce, HR also has a responsibility to advise on the risks associated with introducing AI that replaces human jobs. Broadly speaking, AI is frequently assistive or augmentative, not generally substitutionary, but it is of course important to go into the process with your eyes open when losing or reshaping a percentage of your workforce. By using AI and machine learning in the HR processes, HR departments can get a sense of how to make the technology work for them, and how to ensure it’s fair, responsible and ethical applied across the organisation.

AI can absolutely supercharge an organisation’s ability to leverage data for business success, but an HR director needs to be asking the right questions, joining up the dots, and ensuring it meets wider strategic objectives in order to get the best out of it.

Alan Bourne

About Alan Bourne

Dr Alan Bourne is CEO and founder of global assessment company Sova Assessment
No comments yet.

Leave a Reply