There is a lot of discussion now about how or when AI will replace Humans. Well if we take a step back and review the chain of events over the decades, we will remember that Technology replacing certain humans in jobs is nothing new.

First let us review the history.

Industrial Revolution – 1760

This was when technology started replacing manual human labour. Machines started replacing some tasks in agriculture, manufacturing and skilled crafts like hand weaving.

Office Automation and Computers – Mid 1900s

Advancements of mainframe and personal computers in offices started automating clerical and repetitive tasks.

Post World War 2 – 1945 to 1980

Major developments in farm technologies replaced manual human labour with significant agricultural changes.

Modern Robotics and Automation – 1950s to Present Day

Starting with the first programmable arms, followed by advancements in AI and computer technology then the rise of machine learning.

With advancements come changes and these changes should be seen as progress. Just like with the Internet, we should all embrace AI and the changes that come with it. This article from 2016 looked at where machines could and couldn’t replace humans.

AI will be perfect for the repetitive tasks which would free people to work on strategic problem solving activities. Just like Doctors experienced with voice dictation helping to reduce reporting time.

Another article, this time from HBR describes how we should see it. AI should be seen as augmenting not replacing humans. There are many things that AI cannot do, well currently anyway. AI lacks social skills and adaptability to be able to replace humans in areas requiring empathy or interaction.

We should all pay attention to AI developments and see how we can “adjust and retrain” accordingly to the new world.

I am currently working on a Predictive Analytics Project so uncovered some facts that you may find useful.

Let me start by explaining what Predictive Analytics is.

It is a field of data analytics that uses sophisticated algorithms, machine learning and artificial intelligence to analyze vast amounts of data to make predictions about trends or future events.

In a healthcare setting since the institutions have access to and can use data from Electronic Health Records (EHR) and Insurance claims, they can use real-time and historical data to forecast future heath trends and patient needs which would help the organization run more efficiently.

So how exactly does Predictive Analytics benefit the institution.

Prediction or Early Detection

The models can analyze patient data, lab results and risk factors which can help to identify individuals at risk of developing specific diseases. Their providers are notified and can intervene with preventative measures.

Personalization

The models can help develop treatment plans specific to the patients needs based on the medical and genetic data.

Resource Planning

Analytics can help the organizations predict and plan for a surge in demand for specific services and develop plans to resource as required allowing for more efficient resource utilization.

Readmission Reduction

By reviewing patterns, it can be used to identify patients more likely to be readmitted. Clinicians can then intervene and implement programs to avoid this happening.

Operational Benefits

It can be used to predict systems failures, allowing the maintenance teams to address issues early.

Seems like a win win for all doesn’t it.