How AI Is Being Used to Deliver Care Training Among Care Staff

Artificial intelligence, or AI, has numerous applications. Computer scientists have been using algorithms to work out problems that humans might take years to solve for some time, of course. The difference between a conventional algorithm – essentially, a list of instructions – and AI is that the former does not have the capacity to learn while AI does. This means that it can be given a task that has not necessarily been fully thought-through already but will be able to complete it by looking for additional information it might need. As such, AI works much more like a human brain – with the capacity to ‘think outside of the box’, as it were – than conventional computer programs.

It is in this regard – the capacity for solving ill-defined problems – that AI can be of such use in that most human of activities, care provision. Although various attempts have been made to provide AI companions for people who might be socially isolated over the years, the current thinking among computer scientists isn’t to create robots who can administer care but to make AI tools that help people to provide better care instead. These days, AI and virtual reality tools are used in many areas of adult education and training from helping astronauts to carry out repair procedures on Earth that they might have to do one day in space to helping people learn to drive. So, how is AI shaping the way that modern care training is carried out?

Firstly, it should be noted that AI training for carers takes place in two fields already, medical practice and social care provision. Although the two professions are linked, they are necessarily different when it comes to practical applications. A hospital or residential nursing home, for example, would want different sorts of outcomes from AI-based training sessions compared to an in-home domiciliary care provider, for example.

Indeed, one Essex-based care provider, Anglian Care, says that it uses AI to help educate care workers in ways that are specifically adapted to its current training requirements, something that might change from month to month depending on the number of dementia sufferers it happens to be looking after at any particular time. Being an adaptive method for delivering training AI is very good at offering this sort of flexibility, even if key training methods might be very similar at their core. For example, AI-led handwashing and sanitation training might function on the same principles whether a nurse or a care worker is being trained but the contexts and settings would necessarily need to alter if the training session is to be most beneficial.

One of the key benefits of AI-based training methods in the care sector is that they can predict outcomes. When someone learns how to administer a drug or to carry out a personal care task, AI doesn’t simply tell them whether they did it in the prescribed way or not. It will also be able to extrapolate ahead given its huge number-crunching capacity to say what the outcome is likely to be. This way, care workers don’t simply learn how to achieve the minimum bar of acceptable standards but to work in a way that optimises outcomes. In a world with an ageing population and more demands on carers than ever before, this has to be something we can all agree is desirable.