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radioMal Fletcher comments on social robots working in care homes.
"I call him religious who understands the suffering of others," wrote Mahatma Gandhi. We might fairly substitute for "religion" the word "human".
Academics from two British universities are part of an international team to develop social robots for work in UK aged care homes.
The so-called "Pepper" robots are being manufactured by Softbank, the group which has provided similar machines to care facilities throughout Japan.
As a social futurist who is constantly researching changes in technology and attitudes to it, I know the awesome power of modern machines.
Much is now written about machine (or artificial) intelligence, yet one big question remains. Can robots develop emotional intelligence and particularly the ability to empathise?
A few years ago, Sony couldn't get a robot to walk. Now robots can run, climb stairs and even play a rudimentary form of football. The new generation of sexy-sounding "social bots" are so named because their programming allows them to respond to human emotion.
A visit to a mobile phone store in Tokyo will often mean being greeted by a social bot. It will "read" your emotions through biometrically scanning your facial expressions and muscle movements. It will then respond in kind, according to a series of pre-programmed reactions.
It's not surprising then to learn that Japanese aged care homes have been utilising robots for a few years now. They have proven particularly helpful in assisting clients who have emotional or dementia-related mental health issues.
A survey of one thousand such care homes found that the vast majority of clients preferred the robotic carers to the human variety.
The new breed of robot is indeed remarkable, as are "Smart Age" machines generally. There is evidence that machines can, in a sense, learn. This may seem a little too sci-fi to some observers, but let's remember that wi-fi was sci-fi not that long ago.
Already, in the growing field of Big Data Analytics, machines are processing huge amounts of information in a way - or at least a timeframe - that would be impossible for even huge human networks.
Speedily identifying patterns within screeds of data allows machines to predict such things as economic shifts, political voter patterns and consumer trends. On a very practical level, this predictive analysis is now being used in the design of furniture, buildings, streetscapes and even cities. It is also proving invaluable in the creation of new prisons and crime prevention programmes.
A lesser known product of Big Data is that it allows machines to improve on their own programming. In this sense, machines like IBM's Watson computer - it's actually a network of computers - are able to improve themselves, to "learn".
I use quotation marks here because our common usage of the word "learn" is in the human sense - denoting learning as people do it. We can't apply that word fully to machines, partly because we still don't fully understand how learning actually happens within the human mind.
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Having worked for years as an agency nurse, across the whole spectrum of nursing practice, and from neonatal to aged care, I can already hear alarm bells ringing. On the one hand, most areas within the health profession are low-staffed, and existing staff are therefore pushed for time. This means that contact time with patients is limited. Added to this, nursing training these days takes place in the classroom, where teaching is geared towards a degree in nursing. Practical experience usually consists of working under supervision over the Christmas holiday break (if you're lucky) and is both limited and narrow in scope.
Added to this is the heavy workload of existing nursing staff, where patient contact is often impersonal and limited to the giving of medications, the carrying out of routine medical procedures, and administration of hygiene. Already there is a serious lack of empathy and human touch involved. In fact, having a meaningful conversation with a patient is often frowned upon.
If robots are introduced, workloads of staff may well be reduced, but it is highly doubtful that any time saved would be spent with patients. When you are seriously ill, simple things such as a listening ear, meaningful touch and expressions of empathy carry enormous significance. No robot is able to deliver these as effectively as a caring human being. Certainly medical robots can ease the burden on staff by carrying out rote tasks of all kinds. But we need to leave the caring and empathy to those who understand and empathize, just because they are human.