Machine learning emotions: Can we automate empathy?

Can machines learn empathy?

Healthcare is one of the most important areas of concern for humanity. As with many aspects of modern labor, doctors’ abilities can be replaced by smarter, faster machines. Advanced AI is being developed to help with diagnosis, reaching conclusions faster than trained doctors. Machines are helping patients move, meaning even physical therapists might not be necessary. Now, there might be machine learning that can replace empathy – what many might consider a purely human response. The question is: What does this look like and what will it mean for healthcare?

What is machine learning?

Machine learning is becoming central to all studies in artificial intelligence and its application in the real world. As nVidia points out, machine learning “is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world”.

This is different to software that’s been hand-coded with commands to complete tasks. Instead, the machine itself is trained to parse large amounts of data and algorithms that give it the ability to learn how to perform the task.

What makes machine learning impressive is that there’s no limit to what can be accomplished, the more complicated it becomes. As noted, AI is already diagnosing patients thanks to learning from a large number of data points. Who knows where it could take artificial intelligence and robot behavior next. And this is where automating empathy comes in.

What is automated empathy?

Though the term sounds complicated, the results are simple. As CNN reported on automating empathy involving “helping doctors stay in touch with patients before and after medical procedures — cheaply and with minimal effort from already overextended physicians.” For example, if you operate on 500 patients in a year, it will take enormous resources, time and energy to do follow-ups on each one.

As any healthcare professional will tell you, checking in on patients is essential. It prevents them undoing the medical procedure and interventions already performed, prevents readmission, and thus saves on resources. Patients themselves appreciate being checked up on and knowing their particular requirements are being handled, even if it is simply by a machine. Further, as CNN notes, hospital administrators benefit, since “high satisfaction scores and low readmission rates mean higher reimbursements from Medicare.”

There’s even a Siri with empathy focusing on mental health, reports Forbes: “tech startup Mindbin are building an intelligent virtual assistant, Booost, where users can chat with in-app avatars which track and assess mental wellbeing.”

There’s no limit to what smart machines and smart engineers can do.

This is the future

Automated healthcare might make it sound cold and distant, but people said the same thing about SMS and email. Yet, people have developed entire relationships via these mediums (even before the internet, love letters still existed). Regardless of it appearing cold, health care being efficient matters more and putting it in the robotic hands of smart machines could do wonders for society.

As we’ve highlighted before, even messaging tech like SMS can offer numerous benefits to healthcare organizations. Automating empathy by sending regular checks can only take this further, particularly if it’s linked to learning machines.

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