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The long shadow.

The incident that caused this anxiety was when UNIVAC, the first supercomputer, correctly predicted a 1952 presidential election landslide for Eisenhower after sampling only one percent of the voting population. Traditional pollsters had all predicted Adlai Stevenson would win. CBS, covering the elections, immediately declared UNIVAC’s prediction a huge mistake. Walter Cronkite later recalled,  “I don’t think any of us saw the long shadow.”

Fast forward more than 60 years, and once again, people are worrying that A.I. and machine learning will take their jobs.

We all know that robots are good at doing boring, repetitive jobs like working on assembly lines. But boring, repetitive jobs aren’t all in factories. Robots are now busy flipping burgers, driving cars, trading stocks, and scanning resumés. 

Have you heard about digital bus shelter posters?

They now evolve in response to our reactions. AdAge says in one test, the outdoor ads used facial expression tracking to determine the reactions of 42,000 viewers. It incorporated these learnings into the next iteration, changing text, headlines, colors, and images 1,540 times. It was the first time an advertisement has been let loose to write itself, based on what works, rather than just what someone thinks will work. CNBC said that within 72 hours, the system was creating posters in line with the current best practices in the advertising industry, which had been developed over decades of human trial and error. “We all have to be a little unnerved by this,” said an ad exec.

How many jobs will automation destroy?

It depends on who you ask. 

  • Oxford University says half of total employment is at risk. 
  • McKinsey says 400 million in one citation and 800 million in another. 
  • Futurist Thomas Frey says one billion. 
  • The International Federation of Robotics says zero.

All predictions of the future are mere conjecture, a French word meaning “interpretation of signs and omens.” When the best we can do is narrow down our estimates to somewhere between zero and a billion, our only real conclusion is that we have no idea how many jobs will be lost.

In 2004, MIT and Harvard economists said a computer would never be able to drive a car because of the enormous complexity of information involved.

In spite of that nugget of wisdom, we think you can go ahead and cross driving instructor off your list of jobs that will never be replaced.

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