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    Realizing more and more that the 4th Industrial Revolution gains momentum my word of the year for 2019 is – Deep –

    March 2019

    I am already ready to declare the word of the year for 2019 in connection with the 4th Industrial Revolution (4IR). The word is “deep”.

    But why?

    Because recent advances in the speed and scope of digitization, connectivity, big data and artificial intelligence (AI) are now taking us “deep” into places and into powers that we have never experienced before – and that governments have never had to regulate before. I’m talking about deep learning, deep insights, deep surveillance, deep facial recognition, deep voice recognition, deep automation and deep artificial minds. Some of these technologies offer unprecedented promise and some unprecedented peril – but they are all now part of our lives. Everything is going deep. Technology moves up in steps, and each step, each new platform, is usually biased toward a new set of capabilities. Around the year 2000 we took a huge step up that was biased toward connectivity, because of the explosion of fiber-optic cable, wireless and satellites. Suddenly connectivity became so fast, cheap, easy for you and ubiquitous that it felt like you could touch someone whom you could never touch before and that you could be touched by someone who could never touch you before.

    Around 2007, we took another big step up. The iPhone, sensors, digitization, big data, the internet of things, artificial intelligence and cloud computing molded together and created a new platform – the 4th Industrial Revolution – that was biased toward abstracting complexity at a speed, scope and scale we’d never experienced before. So many complex things became simplified. Complexity became so fast, free, easy to use and invisible that soon with one touch on Uber’s app for example you could page a taxi, direct a taxi, pay a taxi, rate a taxi driver and be rated by a taxi driver.

    Over the last decade, these advances in the speed of connectivity and the elimination of complexity have grown exponentially. Because as big data got really big, as broadband got really fast, as algorithms got really smart, as 5G got actually deployed, artificial intelligence got really intelligent. So now, with no “touch” – but just a voice command or machines acting autonomously – we can go so much deeper in so many areas. Scientists and doctors can now find the needle in the haystack of health data as the norm, not the exception, and therefore see certain disease patterns that were never apparent before. Machines can recognize your face so accurately that the Chinese government can punish you for jaywalking in Beijing, using street cameras, and you will never encounter a police officer. Indeed, with today’s facial recognition technology, I can dispense with the card reader my office’s security gate and instead use each employee’s face as an ID. And cars drive on their own.

    DeepMind, the artificial intelligence arm of Google’s parent, developed an A.I. program, AlphaGo, that has no defeated the world’s top human players of the ancient strategy game Go – which is much more complex than chess – by learning from human play. DeepMind “showed yet another way that computers could be developed to perform better than humans in highly complex tasks” and to “mimic the way the brain functions”. DeepMind’s next breakthrough, AlphaZero, did not even need to learn from humans. It learned even faster by repeatedly playing against itself!

    Today “virtual agents” – using conversational interfaces powered by artificial intelligence – can increasingly understand your intent when you call for example the bank, credit card company or insurance company for service, just by hearing your voice. It means machines can answer so many more questions that non-machines, also known as “humans”. The percentage of calls a chatbot, or virtual agent, is able to handle without turning the caller over to a person is called its “containment rate,” and these rates are steadily soaring. Soon, in my opinion automated systems will be so humanlike that they will have to self identify as machines. Bad guys, who are always early adopters, also see potential to go deep in wholly new ways. They can for example fake your face and voice so well that they can create a YouTube video that will go viral of you saying racists things or make it look like the president of the United States just announced a nuclear attack on Russia. They can use technology to fake a bank manager’s voice so well that it can call your grandmother, and, with a voice command, ask her to transfer 10,000 USD to an account anywhere in the world and she will do it – and you will never catch them in time. That is why the adjective that so many people are affixing to all of these new capabilities to convey their awesome power is “deep”.

    Unfortunately, we have not developed the regulations or governance, or scaled the ethics, to manage a world of such deep powers, deep interactions and deep potential abuses.

    When faced with evidence that for example fake news spread on Facebook influenced the outcome of the 2016 election, Zuckerberg dismissed that notion as a “pretty crazy idea”. It turns out that it was happening at an industrial scale and he later had to apologize. Regulations often lag behind new technologies, but when they move this fast and cut this deep, that lag can be really dangerous. I wish I thought that catch-up was around the corner. But honestly I don’t. So far it has created an opening and burgeoning demand for political, social and religious leaders, government institutions and businesses that can go deep – that can validate what is real and offer the public deep truths, deep privacy protections and deep trust. But deep trust and deep loyalty cannot be forged overnight. They take time. Not all, but many people, are desperate for trusted navigators. It is so far unsettling, and yet, there is no swimming back. We are, indeed, far from the shallow now.