Artificial intelligence – or AI – touches many parts of our daily life.

Digital voice assistants answer the questions we ask, robots at work take away some of the repetitive tasks we face and chatbots give us extra support when we need it.

The use of AI in assessment within organisations is not new. For years personality questionnaires have been scored and "interpreted" by expert-developed algorithms.

But this was just the start. AI in assessment is growing at a rapid pace – and there are questions you’ll be asked in your role as an HR, recruiter or talent professional.

Do you know the answers?

Below are the 8 fundamental questions to which you need to know the answers.

Question 1

What is meant by AI in assessment?

AI-based assessment is beginning to be part of many candidate and employee psychometric assessments, from realistic chatbot-type conversations with candidates in situational judgement tests (SJT) to proven algorithm-based decisions made from looking at candidate responses to test questions. The use of AI in assessment now regularly informs HR and talent decision making.

Question 2

Is artificial intelligence (AI) already used in talent assessment?

A simple answer is "Yes!" The use of AI in assessment has ramped up over recent years. There is more debate about how AI affects the workplace, including talk of it changing the way HR services the workforce and how it’s taking on some routine tasks of human employees. And we’re all getting used to AI being part of our lives through online purchase suggestions and smart-home devices. 

So it’s not surprising that talent assessment too is being shaped by AI.

The first move to AI in assessment came in the 1990s, when paper-based versions of tests moved to computers, with automated scoring and computer-generated interpretive reports. For the first time, technology was taking on some routine tasks and using algorithms to produce a candidate report.

AI is now being used to generate unique test questions “on the fly,” and in tests that make use of adaptive scoring.


Question 3

What does all the AI jargon mean?

Robots in the workplace. Deep learning. Pattern matching. All sounds like gobbledygook to you? You're not alone. Here are a few key terms that you really need to know regarding AI and the use of AI in assessment:

Robotic process automation: This is achieved by gathering and transferring expert knowledge and then programming the system with an ‘if/then’ rule-based approach. Chatbots are a great example. But this, rule-based system is not capable of learning and improving without being given explicit instructions. In terms of its use in talent assessment, computer-generated interpretative reports make use of this.

Machine learning: Even though a computer system cannot think for itself (at least, not yet!), statistical tools can be included which enable the system to model predictions from any given data – and to add to this to improve prediction over time.  This is used in data analysis to create predictive people analytics, to help employers make better talent decisions.

Pattern matching: This AI technique gets the computer to check the sequence of responses to determine if there is a pattern. It can be used to carry out some of the ‘human tasks such as recognising faces or identifying emotions.

Natural language processing: Makes use of text and speech analytics to extract the underlying meaning. This could have applications in analysing speech in interview question responses.

By combining all these aspects, AI has a key role to play in analysing and interpreting vast amounts of candidate data.

Question 4

How does AI improve candidate and employee assessment?

There are five key benefits of AI in assessment.

1. Precision. AI can analyse massive amounts of data, much more than any human could accomplish. Thanks to the increased power of today’s computers - as well as algorithms and machine learning - more candidate data can now be precisely evaluated. This can help make better selection decisions.

2. Efficiency. Whenever you automate a process, you gain efficiency. AI enables recruiters and talent teams to conduct consistent and objective assessments of job-relevant data at a much earlier stage in the selection process. AI enables you to utilise video interviews far earlier in the selection process than is typically the case with in-person interviews.

3. Reducing bias. Humans are vulnerable to biases and stereotypes. This is often why poor selection decisions are made. In theory, AI’s objectivity will help recruiters to eliminate conscious and unconscious bias in the selection process. But, in reality, you have to be very careful about how your AI system is programmed. An algorithm is only as good as the data that’s fed into it. As part of your AI design, makes sure it is not mimicking just one assessor (and all his or her biases) but draws from several assessors.

4. Legally defensible. The AI that’s built into your talent assessment must be transparent and open to challenge. One problem here is that complex ‘black box’ algorithms are sometimes used in AI. These can make selection decisions difficult to justify, because it’s almost impossible to understand how these algorithms reach the conclusions they deliver. If your selection decisions cannot be easily explained, they could be challenged by applicants in a court of law. Allowing AI to continuously learn by ‘observing’ the best practice of human raters offers the best and most legally-defensible approach for assessment.

5. Engagement. AI can significantly improve the candidate experience in recruitment. It enables recruiters to offer immediate support and help, for example through interactive chatbots that can answer queries about the selection process or about specific assessments. AI can also optimise and enhance the selection experience for candidates. For example, by allowing open-ended (not fixed) responses in personality questionnaires and situational judgement tests. By speeding up decision times, reducing bias, enhancing the assessments and making the process more candidate-centric, AI can improve the whole selection experience for jobseekers.


Question 5

How does AI support video interviewing?

Video interviewing nowadays involves candidates being asked to record themselves responding to, typically, competency-based interview questions. These video recordings mean that candidates no longer need to travel for interviews, interviewers get to re-watch and share candidate responses, and less time is spent on the interview itself. But there’s a considerable amount of time that is spent analysing the responses.

How great would it be if the analysis could be done quickly and objectively? And this is where AI has a role.

AI means that the audio can be transcribed and analysed for clarity of speech and proficiency in English. And AI also helps to analyse the visual elements through emotion tracking software and facial recognition. Another great use of AI in assessment!


Question 6

What challenges need to be overcome when using AI in assessment?

As well as the technological considerations of AI, there are four other challenges that must be addressed:

1. Defensibility. Standardised ‘plug-and-play’ AI systems are available - but they won’t differentiate your employer brand. If your competitors use the same systems, you’ll all be chasing the same talent. Also these systems utilise ‘deep learning networks’ which learn as they go. This sounds promising but actually it makes it very difficult to explain exactly why candidates were accepted or rejected. These systems therefore lead you to make selection decisions that you can’t defend, which leaves you vulnerable to litigation from disgruntled candidates. Only custom AI systems offer the ability to make transparent and defensible selection decisions.

2. Time. Custom AI systems mirror human behaviour and replicate the best practice of your assessors and raters. To achieve this, you have to pre-feed the system with relevant information. It can take up to six months to ‘train’ an AI system to assess candidates in exactly the same way that your assessors and raters would judge them. Managing this lead time will be a major challenge for organisations.

CHROs should therefore be forming project teams now to look at custom AI models for video interviewing and other recruitment processes. Otherwise you’ll always be six months behind those pioneering companies that have already invested in this technology.

3. Ethics. There is an ethical question around how much support you take from an AI system. For example, are you happy for an AI system to reject your candidates? Or would you prefer it to ‘flag up’ unsuitable candidates so you can review and check their details? How to use AI ethically will be a key consideration for many employers.

AI’s role should be restricted to providing additional information and enhancing efficiency. Recruiters should always set the objectives when hiring. AI can then deliver useful information, at various stages of the selection process, that will support a final decision

4. Data handling. AI excels at analysing massive amounts of data. However, when so much data is involved, the results can be misinterpreted or even deliberately abused. Good data handling practices will be essential not just for confidentiality but also for maintaining your organisation’s reputation. AI should be used carefully and honourably to help you predict which candidates will be effective in the role - and engaged by your organisation.

Question 7

How can you be sure that using AI in assessment is legally defensible?

The process of selecting candidates - be it for entry into the organisation or promotion within - must always be legally defensible. It must not be discriminatory nor favour a particular group of candidates based on gender, or race, or any of the other groups outline in equal opportunity legislation.

There are also the rights of the individual – and the right to be informed how assessment information is to be used. Under the General Data Protection Regulation, you need to make sure candidates know how and why assessment is being used including profiling to make decisions. But regardless of AI, this is good practice anyway.

Question 8

How is AI in assessment likely to develop?

We’ve come a long way applying AI in assessment contexts – and the progress will speed up and refine.

Assessment developers are already looking at the way in which AI can help the interpretation and understanding of open-ended questions in personality questionnaires and in some of the more progressive assessments such as those based around messaging apps. Real-time interviews could be carried out by an avatar over the internet, or with the avatar being the observer of a hiring manager’s interview.  

Using AI in assessment takes away admin and hassle from HR decision makers while making sure they are still in control. For candidates, AI in assessment means that they get to respond to assessment tools in a more ‘natural’ way, not restricted to just completing ‘written’ tests.


Want to use AI across your talent assessment?

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