The Nature of Work in the 21st Century Will Be Unlike Anything in the Past

September 4, 2017 – Yesterday I wrote about how a chatbot legal program could decrease dramatically billable hours and the number of people practicing law in the near future. Today I’m going to describe the nature of work for humans as this century continues to unfold.

Automation is Inevitable

It’s not robots that will put humans out to pasture, it is pattern recognition computing technology in all its forms. Pattern recognition covers a wide range of artificial intelligence capabilities including regression analysis, clustering, genetic algorithms, principal component analysis, decision trees, and neural networks. We as a species are good at this from our ability to pick up language at a very early age, to learn to read, to master games like chess and Go, to develop celestial mathematics to send spacecraft to nearby planets and moons, and to develop the mathematics that explains the intricacies of the subatomic world.

It shouldn’t be surprising that our mastery of pattern recognition has led us to endow computers and other machines with similar skills. Hence we can create autonomous vehicles capable of making nanosecond decisions while operating a 2-ton vehicle in heavy traffic, and be doing this without our intervention. It should, therefore, follow that at the most fundamental level, the machines we have invented to emulate our thinking will be more than capable of doing much of the heavy lifting that has characterized human labour through the centuries.

The machines we are creating now are designed to follow patterns, to do repetitive, mundane tasks equal to if not better than most of us, and we can continue to expect that the years ahead will see many of these types of machines (see Baxter below) take over pattern-dependent jobs, those on assembly lines, or warehouse sorting, picking and packing.

In a decade or so even more sophisticated pattern recognition machines will take on more complex tasks such as autonomous transportation systems that will include individual cars, truck convoys, transit operations, and commercial aviation.

 

Baxter is a multi function robot that learns repetitive, patterned tasks from human trainers and can then work beside them in warehousing and assembly line operations.

 

Artificial Intelligence Opens Up a World of New Possibilities

If it weren’t for the fact that our world population is estimated to grow to 10.5 billion by mid-century, I believe we could create new jobs for the 2 billion or more who will be displaced from the work they do by pattern recognition machines. Even then I’m more optimistic than most that humanity by mid-century will not be idle, that there will be plenty of interesting and exciting work whether it is with the technologies we are creating or maintaining, or with the explosion in knowledge that will lead to new opportunities.

There is no doubt that technical talent will be needed in an automated world. Many will be needed to ensure that the machine never stops working for us. Many of us will become proficient technicians capable of maintaining and enhancing our automated world. Others will move artificial intelligence forward by enhancing the algorithms that define it.

If we think STEM education is in our present, it certainly will be central to our children’s future. What is STEM? It is is an interdisciplinary curriculum focused on educating students about science, technology, engineering, and mathematics, covering both research and application. One of STEMs components is coding.

Coding will be a necessary fundamental skill in the 21st-century world of humans and machines working together. It will take prominence along with language facility. This coding will not resemble the coding of old, the writing of lines of programmable instructions. No, instead it will resemble interactive training, sometimes cerebral and sometimes physical. Machines and humans will learn by communicating using natural language or physical movement. They will learn from us and we will learn from them. This will speed up education and make it possible for humans to take on new responsibilities, and to develop new skill sets, all with machine partners to provide a wealth of information from a global database.

Natural Language Interfaces are the Key

Humans love storytelling. We learn from stories. And because so much of what we know will be inside the machines we create, they will become not just partners in the working world of the 21st century, but also storytellers and teachers. A pattern recognition machine with access to a global knowledge database, along with natural language skills both in listening and talking, will, in fact, be able to teach and tell stories better than most humans. It will have access to more information and with its ability to relate its knowledge in the context of its interaction with it human partners, help them gain new insights and skills to lead to new jobs.

Instead of humans taking four years to become academically qualified in a particular field, they will continuously work and learn, with technology capable of organizing vast amounts of knowledge and structuring it to help create experts. I know this seems fanciful, but the reality is, the marriage of artificial intelligence, complex pattern recognition, and natural language processing and interfaces, is today, just underway. In a decade we will see the fruits of efforts by companies like IBM with its Jeopardy-famed Watson, and with Google, and Microsoft, with their work in neuromorphic computing and neural networks. What these companies develop will lead to the learning revolution I described at the beginning of the paragraph. A doctor won’t need 6 years to become proficient in detecting, diagnosing and treating illness. Instead, the doctor to be will work alongside an artificial intelligence partner who will serve to be both a knowledge base and guide to help sharpen the cognitive as well as the hands-on skills needed to serve patients.

Teaching Machines Right from Wrong

There will be a place for linguists, psychologists, sociologists, philosophers and even anthropologists in this mid-21st-century world as artificial intelligence grows ever more knowledgeable about the world and us. For machines to be better partners to humanity they will need a strong dose of the humanities. They will need to understand not just the raw meaning of words, but the subtleties that go along with them, the body language, the cultural backgrounds of those with which they interact. Beyond hard wiring, a morality code, our pattern recognition, natural language interacting, artificial bits of intelligence will need to be able to evolve socially and psychologically. Sounds like, those studying the humanities in the middle of the century will have important jobs to keep synergy in the combined humanity and machine world we have mutually created.


Len Rosen lives in Toronto, Ontario, Canada. He is a researcher and writer who has a fascination with science and technology. He is married with a daughter who works in radio, and a miniature red poodle who is his daily companion on walks of discovery.
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