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BRT has written copiously about AI, the open ended tech that promises to change everything in ways that cannot be predicted, is now coming for your job whether you like it or not.

SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X-rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition; there are large sets of labelled training data to crunch; and there is tremendous potential to make health care more accurate and efficient.

Dr Barani (who used to be an oncologist) points to some CT scans of a patient’s lungs, taken from three different angles. Red blobs flicker on the screen as Enlitic’s deep-learning system examines and compares them to see if they are blood vessels, harmless imaging artefacts or malignant lung nodules. The system ends up highlighting a particular feature for further investigation. In a test against three expert human radiologists working together, Enlitic’s system was 50% better at classifying malignant tumours and had a false-negative rate (where a cancer is missed) of zero, compared with 7% for the humans. Another of Enlitic’s systems, which examines X-rays to detect wrist fractures, also handily outperformed human experts. The firm’s technology is currently being tested in 40 clinics across Australia.

A computer that dispenses expert radiology advice is just one example of how jobs currently done by highly trained white-collar workers can be automated, thanks to the advance of deep learning and other forms of artificial intelligence. The idea that manual work can be carried out by machines is already familiar; now ever-smarter machines can perform tasks done by information workers, too. What determines vulnerability to automation, experts say, is not so much whether the work concerned is manual or white-collar but whether or not it is routine. 

In reading this, consider what is going to happen to healthcare, the most inefficient system in America save for the Pentagon where 

1. An office visit to a doc to deal with the flu costing $150 is replaced by purchasing a set of $2.00 labs on a chip, via Amazon, to be used at home, as needs warrant.
2. Said chip, with connects to the web and Dr. Watson, delivers blood sample data to Watson for realtime analysis.
3. Dr. Watson, after analyzing the sample, tells the patient what's wrong, prescribes, if necessary, the drug to deal with the condition in question and sets up a time for another visit as needs warrant. Price for said service, $1.00.
4. “If you want something new, you have to stop doing something old.” - Peter Drucker .

Yours truly knows a few GPs and they fear AI big time. The ortho guys, dentists or specialists dealing with serious illness like cancer, heart or diabetes, not so much though the push toward patient stem cell in situ organ regeneration is starting to encroach upon those areas as well.

Lawyers are also in the crosshairs as well as many other jobs that are, as per The Economist, routine in nature.

Addendum: A stunning 94 percent of the 9 million new jobs created in the past decade were temp or contract-based gigs.

Tech, like research and money, never sleeps. - Robert E.