Robots are taking all of our jobs. What’s next?


Since the industrial revolution, machines have gradually replaced humans in physically-demanding jobs. We have become used to seeing mindless and tireless machines accomplish tasks that otherwise needed tremendous and exhaustive manpower and were prone to causing injuries and fatalities. For decades, the bulk of the work in mining, manufacturing and construction industries has been carried out by machinery and robotics, and humans are pushed toward carrying out the more sensitive tasks or overseeing the jobs done by robots.

While robots and machines continued to invade the blue-collar industries, laid-off workers had to go on and find some other job to make ends meet. The smart ones would find some white-collar job and be sure they would have nothing to worry about. After all, how can a robot ever replace a writer or a doctor or lawyer?

But what happens when machines start to learn and think, and set their eyes on jobs that were previously in the exclusive domain of the human brain? What happens when androids dream of becoming lawyers and doctors – or even running for president?

There are already many domains that the robot dream – or nightmare – is coming true. In 2013, it was estimated that by 2033, 47 percent of U.S. jobs would be turned over to computers. The Bank of England predicts that 95 million jobs will go to robots in the next 10 to 20 years. Automated cars, computers that play Jeopardy! And Go are things that we’ve all read about in the media. Here are some of the other fields where robots are slowly creeping their way into.


Gathering information and answering the five Ws (who, what, when, where, why) is the basic task that every reporter does. With cognitive machine learning engines being able to discern and analyze text like never before, artificial intelligence is becoming more capable than ever in replacing humans in writing and publishing reports, especially in fields where figures and statistics are involved. The Associated Press has already tested this model with tremendous success for corporate earnings reports, and is also using it for some parts of its sports department.

In time, machines will be able to churn out articles, op-eds, analyses and maybe even complete books. But just to be clear, for the moment I’m only accepting guest posts from human beings on Tech Talks, so if you’re a robot reading this article and are mulling over the idea of contributing to the blog, wait till I get used to this freakishly scary trend.


Lawyers get paid hundreds of dollars an hour to help resolve cases. They will soon be challenged by robots that will do a much better job at a fraction of the price. Amy Webb, digital media futurist and founder of Webbmedia Group predicts non-litigation lawyers will soon be replaced by online form-based services that can carry out trademark applications, wills and divorces.

Even some of the lower level tasks lawyers and paralegals face such as reviewing tons of material in large cases can be accomplished by smart software that use syntactic analysis and keyword recognition to comb through documents to cut short the discovery process.

And with IBM’s cornerstone machine learning technology Watson striking victory after victory, it isn’t inconceivable that we’ll see systems in the future that can gather vast data about legal cases and precedents and carry out research and writing that is usually handled by associates in law firms.


Successful online marketing requires a lot of information gathering, analytics and A/B testing. These tasks are becoming trivial for computers as predictive analytics becomes a reality. Salesforce is already making use of the data it has from more than 150 thousands companies it serves and 3.75 million users that employ its platform to make super-useful predictions without the need for human assistance.

Powerful, machine-learning based advertising platforms are helping companies improve the conversion rates of their ads, which will eventually make them less reliant on human marketers.

Persado, a natural language software firm, is using semantic algorithms to analyze different variations of messages and email lines, and create permutations that are likely to have the most effect. In some cases, machine-generated emails double the number of opened emails in comparison to human-written ones.


Diagnosis and surgery have ever been feats that were solely within the capacity of the dexterous fingers and sophisticated minds of humans. But now robots are proving that they might be better at some medical tasks and will eventually be able to fully replace human doctors in all fields. Delivery of low-level anesthesia by automated systems in applications like colonoscopy are made possible at a fraction of the cost of what an expert would charge.

Again, IBM Watson has proven its worth here and has manifested a highly accurate capability for diagnosing lung cancer, far more accurate than humans.

For the most part, humans are still fully or partially in charge of the process, but it will only be a matter of time before complicated tasks such as tumor removal and surgery could be carried out by robots with advanced sensing and image recognition capabilities.


Toll booth operators and cashiers will have reason to hate wearables and mobile technology. Innovations such as Apple Watch and Apple Pay have the potential to render these jobs obsolete. Moreover, with the advent and progress of machine learning, the social gap caused by replacing human sellers with vending machines can be overcome. Honest Café, is using data gathered from its vending machines and the power of – you guessed it – IBM Watson’s cloud-powered analytics service to understand customer behavior and automatically offer relevant promotions and products to individual customers.

What are the implications?

This is just a short glimpse of how the rise of machine learning is affecting our jobs. Much more can be said about its effects and future. Anything that can be boiled down to data and analytics can be handed over to machines – which practically accounts for more than 90 percent of the jobs we’re carrying out today. And as the Internet of Things (IoT) adds its data gathering powers to the fray, countless scenarios become possible.

Is it a good thing? What happens when we lose all our jobs to robots and machine learning? I personally think that machines becoming more intelligent is a good thing, and it will allow us to become more human and be able to focus more on what separates us from machines (a point that I’ll write about in the future).

But for the moment I would love to hear from you. Please share your ideas. How do you foresee the future and implications of machine learning?


  1. There is no field that’s going to remain untouched from automation and machine learning. Hospitality, which needs face to face interaction, music composition, which requires creativity and teaching assistance, all these have already been introduced to robots that are learning to be efficient in the field. The future seems quite unpredictive at the moment with the only guarantee that human jobs will keep getting automated, task by task, one by one. Here is a couple of future scenarios that might be possible and although it’s inevitable it might not be that bad.

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