A global study finds several new categories of human jobs emerging, requiring skills and training that will take many companies by surprise.

The threat that automation will eliminate a broad swath of jobs across the world economy is now well established. As artificial intelligence (AI) systems become ever more sophisticated, another wave of job displacement will almost certainly occur.

It can be a distressing picture.

But here’s what we’ve been overlooking: Many new jobs will also be created — jobs that look nothing like those that exist today.

In Accenture PLC’s global study of more than 1,000 large companies already using or testing AI and machine-learning systems, we identified the emergence of entire categories of new, uniquely human jobs. These roles are not replacing old ones. They are novel, requiring skills and training that have no precedents. (Accenture’s study, “How Companies Are Reimagining Business Processes With IT,” will be published this summer.)

More specifically, our research reveals three new categories of AI-driven business and technology jobs. We label them trainers, explainers, and sustainers. Humans in these roles will complement the tasks performed by cognitive technology, ensuring that the work of machines is both effective and responsible — that it is fair, transparent, and auditable.

Trainers

This first category of new jobs will need human workers to teach AI systems how they should perform — and it is emerging rapidly. At one end of the spectrum, trainers help natural-language processors and language translators make fewer errors. At the other end, they teach AI algorithms how to mimic human behaviors.

Customer service chatbots, for example, need to be trained to detect the complexities and subtleties of human communication. Yahoo Inc. is trying to teach its language processing system that people do not always literally mean what they say. Thus far, Yahoo engineers have developed an algorithm that can detect sarcasm on social media and websites with an accuracy of at least 80%.

Consider, then, the job of “empathy trainer” — individuals who will teach AI systems to show compassion. The New York-based startup Kemoko Inc., d/b/a Koko, which sprung from the MIT Media Lab, has developed a machine-learning system that can help digital assistants such as Apple’s Siri and Amazon’s Alexa address people’s questions with sympathy and depth.

8 Comments On: The Jobs That Artificial Intelligence Will Create

  • Michael Zeldich | March 24, 2017

    The robots will be not concurrents for workers if they will be belong to them.
    That switch is requiring changes in model of industrial business.
    The relation in industrial businesses should be remodeled after agricultural businesses.
    That will convert all employees into self-employees responsible for all the business connected expenses and living on profit from trade of their activity result.
    That remodelling will open a way for increasing productivity of economical system and help to return labor back.

  • Tinko Stoyanov | March 24, 2017

    Please do not forget professions such as researchers and developers of AI-based systems, designers, maintaining personnel, etc. Those guys will be at the “genesis” of such systems. There are not many of them in the industry now. And the demand for such professionals will be skyrocketed soon.

  • Aik Koon Wee | March 26, 2017

    Will the AI become their own trainers, explained etc?

  • Kenneth Martin | April 1, 2017

    Human behavior is complex and we are still learning more about it and the unknown hazards and risks associate with it. So, when combining two complex systems together such as AI and human behavior there will be many unknowns regarding the effects. If a system is complex then it cannot be measured. Please find link to article on the Benefits & Risks of Artificial Intelligence: https://futureoflife.org/background/benefits-risks-of-artificial-intelligence/

  • ANA MERCEDES GAUNA | April 4, 2017

    Eu espero que isso jamais aconteça. As pessoas são bem mais importantes do que essa inteligência artificial, do que esses robots. As pessoas tem que emprego e trabalho, as pessoas tem que sustentar o pai e a mãe (quando idosos), as pessoas tem que sustentar os filhos, tem que sustentar a esposa ou o marido, tem que sustentar a familia. Essas máquinas (inteligência artificial / robots) jamais devem ser criados para prejudicar o ser humano. Essas máquinas tem que ser criadas é para ajudar as pessoas (seres humanos). Quem raciocina é o ser humano, não são essas máquinas (robots).
    Translation (portuguese to english):
    I hope this never happens. People are far more important than this artificial intelligence, than these robots. People have to work and work, people have to support the father and the mother (when they are elderly), the people have to support the children, they have to support the wife or the husband, they have to support the family. These machines (artificial intelligence / robots) should never be created to harm the human being. These machines have to be created is to help people (human beings). Those who reason is the human being, are not these machines (robots).

  • Munyaradzi Mushato | May 3, 2017

    Indeed AI is the new normal or will be very soon and the early birds will certainly enjoy a first mover advantage. On the issue of new skills and behaviors to drive the AI age, its for industry and learning institutions, especially tertiary, to increase levels of research-based collaboration that should see an emergence of entirely new curriculae and qualifications set to meet the emerging skills demand in Industry. So, the AI wave can indeed wipe out professions, jobs and whole learning institutions who soon discover that their degrees have no takers anymore. In fact, innovation in non-AI technologies at industry level is already leading industry and commerce away from traditional knowledge and behaviors obtained in tertiary learning institutions. Ernest & Young has taken a lead in that phenomenon by announcing that they have scraped degrees from their minimum entry requirements after rightly observing the low prediction of degrees on job performance. folhttp://www.huffingtonpost.co.uk/2016/01/07/ernst-and-young-removes-degree-classification-entry-criteria_n_7932590.htmllow this link for more :

  • Munyaradzi Mushato | May 3, 2017

    Indeed AI is the new normal or will be very soon and the early birds will certainly enjoy a first mover advantage. On the issue of new skills and behaviors to drive the AI age, its for industry and learning institutions, especially tertiary, to increase levels of research-based collaboration that should see an emergence of entirely new curriculae and qualifications set to meet the emerging skills demand in Industry. So, the AI wave can indeed wipe out professions, jobs and whole learning institutions who soon discover that their degrees have no takers anymore. In fact, innovation in non-AI technologies at industry level is already leading industry and commerce away from traditional knowledge and behaviors obtained in tertiary learning institutions. Ernest & Young has taken a lead in that phenomenon by announcing that they have scraped degrees from their minimum entry requirements after rightly observing the low prediction of degrees on job performance. http://www.huffingtonpost.co.uk/2016/01/07/ernst-and-young-removes-degree-classification-entry-criteria_n_7932590.htm

  • Randy Crawford | June 16, 2017

    These three roles assume a lot of stability in how AI is used within the enterprise. It presumes the presence of commercial (third party) AI software that plays a deep role in the critical path of a company’s operations.

    I know few industries or companies like that today, even where non-automated software implements a company’s daily processes (other than software development). Perhaps it best would portend companies whose practices have been mostly or fully automated, so subsequently all of the company’s processes could be subsumed by an AI-driven application.

    But can we really foresee this state of affairs with any fidelity yet? Don’t we first need to see examples of companies which are implemented mostly via software, but done manually (with an eye to being automated and tuned by AI and machine learning)?

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