The challenge we face today is not a “world without work” but a world with rapidly changing work.

The pace of progress in AI and machine learning is accelerating rapidly. In the past month alone, these are just a few of the news items I’ve seen:

  • DeepMind Technologies Ltd. in London, U.K., has developed a system to scan 1 million images from eye scans and is training itself to spot early signs of degenerative eye conditions.
  • Rethink Robotics Inc. of Boston, Massachusetts, founded by former MIT AI Lab director, Rodney Brooks, made massive upgrades to its Sawyer robots to help nonexperts program routines that instruct the robot how to carry out complex tasks.
  • H&R Block’s tax preparers began using IBM’s Watson computer system to maximize customer deductions. Watson “knows” thousands of pages of federal tax code and will continually update changes as they occur.
  • NuTonomy Inc. of Cambridge, Massachusetts, a startup developing self-driving cars based on technology from MIT, has launched a small fleet of autonomous taxis in Boston.
  • Forward, a San Francisco, California, startup founded by Google’s former special projects director, is attempting to shift traditional health care away from immediate and reactive care procedures, to proactive care through the use of AI and wearable sensors.

Deep learning and neural networks have dramatically improved in effectiveness and impact, leading to human-level performance in many aspects of vision, conversational speech, and problem-solving. As a result, industries are in the midst of a major transformation and more is on the way.

But there’s also a backlash brewing. Median income in America is lower now than in the past 15 years, and wealth is concentrated at the highest levels. As seen in the recent U.S. elections, there is dissatisfaction with the uneven distribution of the benefits of technological progress. IDE research bears out the chasms many are feeling.

Rumblings about robots replacing more and more human work have been heating up — with legitimate concerns. In 2014 when I published The Second Machine Age with Andrew McAfee, we anticipated much of this progress, but the pace has accelerated beyond expectations. This isn’t the first time automation has transformed factories, of course, but with today’s robust AI technologies, automation is starting to creep into fields that require less repetitive manual labor and once seemed immune to this shift, such as law, education, and journalism. Today’s advances are augmenting human minds, not just muscles.

In the midst of all these wonders, it is important to remember that there’s no shortage of important work that can be done only by humans. And that will remain true for many years. The challenge we face today is not a “world without work” but a world with rapidly changing work. The response, then, isn’t simply replacing income for workers being displaced by technology, but preparing them to do new jobs that are desperately needed in education, health care, infrastructure, environmental cleanup, entrepreneurship, innovation, scientific discovery, and many other areas.

How? Too many business and labor leaders, as well as politicians, have become complacent. They fear a future that will disrupt current models and economies. But the solution to disruption isn’t to protect the past from the future or to freeze the old ways of doing things. That’s guaranteed to fail. The best path forward is to adopt emerging tools and models that not only create goods and services but overall prosperity.

Developing AI products and services in a timely, competitive way, doesn’t have to conflict with deploying — and re-deploying — the workforce. Instead of thinking of AI as a zero-sum game, or a way to automate existing jobs and services, forward-thinking executives recognize that technology adds value by expanding jobs and boosting productivity. When technology complements human workers, makes them more productive, and also cuts costs, businesses and employees are better off.

Remember that historically, technology has both destroyed and created jobs. We need to shift today’s conversation more toward job-creation solutions where automation is more than just replacing current labor with capital investments.

Two examples from the IDE’s 2016 Inclusive Innovation Challenge illustrate how this might be done: At 99Degrees Custom Inc., based in Lawrence, Massachusetts, regional “speed factories” use robotics and lean and agile development tactics to help the young apparel company respond to demand, reduce inventory, and innovate ahead of competitors. At the same time, it trains a skilled, local workforce, pays better wages, and invests in the career advancement of its workers.

In a very different case, the giant German software company, SAP, launched Africa Code Week two years ago to empower young Africans with coding skills. Last year, more than 430,000 youth in 30 countries in Africa and four countries in the Middle East took part in Africa Code Week and Refugee Code Week. SAP says that in the long term, the effort will “help close the information and communication technology skills gap in the regions,” spurring economic growth and stability. It is also an integral part of SAP’s vision to help improve people’s lives.

There are many approaches to thriving in the evolving AI world, but all require determination and resourcefulness. Some efforts might focus on areas where humans still have the advantage over machines — intangible characteristics and interpersonal skills such as creativity, empathy, teamwork, planning, problem-solving, and leadership. Others might build sensor-based systems to help us reduce energy use through greater efficiency and lower cooling bills, or to enrich our cultural life. All are part of what 20th century economist Joseph Schumpeter called “creative destruction.”

The emerging AI future will be a far cry from today’s business as usual — but it doesn’t have to be a time of panic. With a clear commitment to sharing the prosperity of the digital economy, and with confident investments in a rapidly emerging future, the next few decades will be the best in human history, for the many, not just the few.

5 Comments On: How to Thrive — and Survive — in a World of AI Disruption

  • Michael Zeldich | March 4, 2017

    There is better way than make improvement in software.
    We are have to switch to design of the artificial subjective systems, which did not require any further programming and able to accrue a professional skills as we are.
    That quantum lip will open the way to make men free from necessity to work for food.


  • Michael Zeldich | March 24, 2017

    Erik Brynjolfsson and many others could be not to worry about a danger from AI systems.
    Any programmed system cannot impose a systematic danger on the human race.

    Situation will be different if one will find out how to design of the artificial subjective systems, and design them as an independent living synthetic person.
    If that will happen, there will be no place for any consumers of nonrenewable resources.
    Control of such systems by imposing human set of moral rules on them cannot be successful because such systems will not recognize humans as members of their society.
    The only way to make such systems safe is in designing them so, that they will not have opportunity to have their own, egoistic, interests.
    I have to find that way by myself, but recently I pointed to the fact that this solution was found milleniums ego. Djinnis, in mythical literature, did not to do anythings till not motivated by masters.

  • Laurence Stevens | March 26, 2017

    These initiatives are not designed for ordinary people. When millions of American drivers lose their jobs in the next decade, we’re not turning them into coders (or nurses, for that matter).

    Think of the 50,000 people who overdosed in 2015, more than died from cars and guns combined. Their numbers are exploding. It’s the people at the bottom, especially those who just landed there, whom we need to reach. How do we do that?

  • Javier Acosta | December 8, 2017

    AI to automates the tedious tasks of engineering (drawing check, drawing generation, model check, model generation), freeing time for the fun and creative stuff.


  • Top SEO | March 24, 2018

    This is a very informative discussion about ” How to Thrive — and Survive — in a World of AI Disruption ”

    Thanks for sharing

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