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Lightening the load: how future technologies could support work coach effectiveness

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The emergent technologies of big data and artificial intelligence (AI) have produced anxieties about change and potential job losses. But can we see these advanced technologies as assisting and enhancing our jobs? In this article, we look at how new technologies could enhance the effectiveness of job coaches.

Debate continues to rage about whether robots will ‘steal our jobs’ or provide support, enhance effectiveness and increase productivity, job satisfaction and more. It is a question of attitude. We can understand improvements in automation, for example, as technology taking job tasks away from humans. Alternatively, we can see this as freeing up time spent on repetitive and unrewarding administration, to be used with greater effect and satisfaction on more creative, complex or caring aspects of our work. Technological innovation offers continuous opportunities to reshape the way we work, improving our experience and that of those we serve.

Robots are already being trialled for use in primary education, police work and in the service industry, while algorithms are eliminating unconscious bias from hiring. Emerging new technologies could be used to great benefit in employability, supporting the work of human work coaches to effectively help jobseekers into work. Here are some of the ways they could be implemented.

Natural language processing and claimant contracts

Data analysis offers myriad opportunities to improve how we work. Developments in machine learning have made it easier to pick up on patterns. For example, it could be used to determine the most effective time of day for work coaches to issue their clients with important reminders.

However, most data analysis systems have been created to work with structured text, such as the wording found in drop down menus and check boxes. Unstructured data is more complex to analyse. This is free text, the kind you would find in a jobseeker’s claimant contract. It often has a more narrative style, uses shorthand and assumes a certain amount of prior knowledge and context. Using computers to analyse and extract insights from free text is an evolving art form.

A research group at King’s College London is currently exploring the use of natural language processing, machine learning and artificial intelligence to analyse the unstructured data hidden in medical records. Advances in this work could have benefits in employability. Written records such as claimant commitments for Universal Credit are highly personalised and rich in information. Being able to systematically analyse these could improve outcomes, for example by identifying patterns between particular claimant profiles and effective interventions. These insights could be used to inform continuous improvement in employability.

Virtual reality and soft skills training

Virtual reality (VR) is already being used across industries to deliver hard skills training, such as teaching pilots how to fly. However, until recently, training in soft skills training, such as resilience, leadership and so on, has remained the remit of in-person sessions. As the pandemic has limited in-person contact across industry, businesses have had to stall the delivery of much-needed soft skills training.

Similarly, in employability, aside from the current need to maintain distance, work coaches’ increasing caseload limits the time they have with their clients. Yet work coaches are in the best position to recognise the soft skills that will enhance the job prospects of their clients. Being able to prescribe training sessions through VR could enhance work coach effectiveness and improve outcomes, without adding unrealistic expectations on what they can achieve with their limited time.

PwC conducted a study to determine if soft skills, like hard skills, could be delivered effectively via VR. They found that learners in a virtual environment learnt faster, concentrated more, felt more confident and had a stronger emotional connection to content than they would in a traditional classroom setting or when learning online. And faster training saves money, an aid to tightening budgets: PwC calculated that two hours of classroom training can be delivered in just 20 minutes using VR.

This research has interesting ramifications across countless different settings, including employability. Using VR technology to conduct interview simulations, for example, could increase candidate confidence and therefore the likelihood of being hired.

And this technology could also be used to deliver onboarding and ongoing training for work coaches. Such training could help improve communication skills, develop leadership abilities and team management techniques, or best practice for data analysis. In turn, this will help to boost employment results, increase job satisfaction and minimise staff turnover. 

Digital badges to recognise and accelerate progress

Completed employability training could be recognised using a digital badge system. Digital badges are badges of achievement that can be displayed online.

Digital or open badges are already being used in innovative schemes such as Cities of Learning, an initiative which fosters inclusive, lifelong learning in urban spaces. And IBM piloted the use of digital badges in a business environment, finding that they increased value in every area measured including motivation, engagement and confidence.

Although not a particularly complex technology, digital badges have the potential to further increase jobseekers confidence and sense of achievement throughout their job search, while enhancing the ability of work coaches to deliver great results for clients and employees.

Socially assistive robots in job centres?

Socially Assistive Robots (SAR) are robots designed to help people through individual, non-contact assistance in convalescence, rehabilitation, training and education. A research paper put together by Skills for Care assessed the potential to enhance and improve social care through the use of AI and robotics. Their aim was to evaluate whether the implementation of AI and robotics could help to free up frontline staff to focus more of their time on human tasks such as providing emotional support.

If this technology has the potential to decrease workload pressures in social care, it follows that comparable technology could be useful to help work coaches cope with increasing caseloads.

While Skills for Care’s research ultimately called for greater research, the technology does show promise for use in the sector. The authors identified that:

“The main hurdle to overcome initially is in terms of cultural change and addressing the reluctance and scepticism from the care workforce on the ability of AI and robotics to assist them in their role, rather than being a threat to their jobs.”

While robots may be a little further off, the digital training, analytics and recognition technologies we’ve explored here are much closer to implementation. But before they can be embraced to their full potential, work coaches need to be equipped with an understanding of how new technologies will be introduced into their work and why this will benefit them. Training will be fundamental to allow work coaches to effectively and confidently make the most of new technologies.

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