Tag Archives: Ray Kurzweil

How the Nature of Risk Is Changing

Back in 2001, famed technologist and futurist Ray Kurzweil boldly proclaimed that the human rate of progress was doubling. He added that, by the time the 21st century ends, the progress would feel like 20,000 years’ worth of transition instead of 100.

At the time, Kurzweil’s statement sounded a bit dubious. But with how rapidly technology has transformed over the last two decades, it now seems that the world’s ability to change quickly was drastically underestimated.

We live in an age defined by acceleration, and this incredible pace of change has exceeded many industries’ capacity to handle it. Changes that once took an entire generation for people to adapt to now takes 10 years. The possibilities of this rapidly changing landscape are endless, and so is the risk that comes with it.

The Far Reaches of Risk

It should come as no surprise that risk evolves alongside technology transformation. Advancement is a double-edged sword. It can simultaneously create a greater level of safety for the status quo and change the very nature of risk, forcing insurers to build new coverage solutions to address previously unforeseen concerns.

For instance, autonomous vehicles might be safer drivers than humans, but they’re also vulnerable to cyberattacks and malware. In many cases, driverless cars are blurring the lines of established risk categories. For proof, just take a look at the sharing economy. It’s less than a decade old, yet it’s raised major questions in terms of how coverage works. Are Uber or Lyft vehicles classified as work or personal? And does the coverage shift throughout the day as drivers turn their ride-sharing service on and off? Insurance companies have to find answers for these types of problems on a daily basis.

See also: How to Adapt to the Growing ‘Risk Shift’  

It’s an understandably complex and intimidating concept for many insurance leaders. However, while progress may be rapid, it’s not entirely unpredictable. The future can be bright for those who remain engaged with the changing landscape of risk. Here’s what those leaders can expect:

1. Humans will gain a deeper understanding of risk.

While technology’s race toward the future provides ample opportunity for confusion, it also provides the tools to parse that confusion and come to a better understanding of risk. Telematics, machine learning, data analytics and more all give insurers much greater insight into how risk touches every aspect of life.

Commercial auto insurers are testing the waters of telematics to explore how they can be applied to evaluate individual driving behaviors. Companies can examine individual driving habits to see how those routines inform the kinds of services and discounts they can offer customers. Instances like these are only going to become more common. This type of granular data sharing will have a direct impact on how coverage is constructed and provided in the future.

2. The way humans and technology relate to risk will change.

As automation continues to be integrated into daily life, coverage will have to properly account for and balance the effect computers and humans each have on rates.

Amazon has more than 100,000 automated and robotic systems integrated into its operations working with human employees to maintain efficiency. The online retailer has almost certainly had to consider how to provide coverage for its employees while they work in tandem with heavy machinery, something companies in similar situations will also have to consider.

Regulation for this is still being crafted. Insurers will need to make sure they continue to stay up-to-date on how and when machines can take over from humans and how that will affect risk.

3. Customer service will look a little different.

Thanks to the Internet of Things, insurers will be able to learn about incidents in real time and process claims before a policyholder even gets involved. These instantaneous notifications are clearly useful for insurance companies, but, used correctly, they can also be a major selling point for consumers.

Machine learning could have a similar impact on customer service. It can be used to pinpoint a highly customized plan for every individual without the customer having to do most of the groundwork.

See also: Insurers Grappling With New Risks  

This age of acceleration is intimidating, and it certainly shows no signs of slowing down. Leadership, however, should look at all this innovation as an opportunity, not a threat. Insurers can leverage tech to improve the customer experience from quote to claim, and, as technology advances, so will the tools that help insurers understand risk.

There’s no denying that infrastructure, demographics and risk are all changing at breakneck speed. To keep up, insurers must not just follow change — they need to grab it by its horns and embrace the new before it becomes old hat.

AI’s Promise Is Finally Upon Us

We have been hearing predictions for decades of a takeover of the world by artificial intelligence. In 1957, Herbert A. Simon predicted that within 10 years a digital computer would be the world’s chess champion. That didn’t happen until 1996. And despite Marvin Minsky’s 1970 prediction that “in from three to eight years we will have a machine with the general intelligence of an average human being,” we still consider that a feat of science fiction.

The pioneers of artificial intelligence were surely off on the timing, but they weren’t wrong; AI is coming. It is going to be in our TV sets and driving our cars; it will be our friend and personal assistant; it will take the role of our doctor. There have been more advances in AI over the past three years than there were in the previous three decades.

Even technology leaders such as Apple have been caught off guard by the rapid evolution of machine learning, the technology that powers AI. At its recent Worldwide Developers Conference, Apple opened up its AI systems so that independent developers could help it create technologies that rival what Google and Amazon have already built. Apple is way behind.

The AI of the past used brute-force computing to analyze data and present them in a way that seemed human. The programmer supplied the intelligence in the form of decision trees and algorithms. Imagine that you were trying to build a machine that could play tic-tac-toe. You would give the computer specific rules on what move to make, and it would follow them. That is essentially how IBM’s Big Blue computer beat chess Grandmaster Garry Kasparov in 1997, by using a supercomputer to calculate every possible move faster than he could.

See also: AI: Everywhere and Nowhere (Part 2)

Today’s AI uses machine learning, in which you give it examples of previous games and let it learn from those examples. The computer is taught what to learn and how to learn and makes its own decisions. What’s more, the new AIs are modeling the human mind itself, using techniques similar to our learning processes. Before, it could take millions of lines of computer code to perform tasks such as handwriting recognition. Now it can be done in hundreds of lines. What is required is a large number of examples so that the computer can teach itself.

The new programming techniques use neural networks — which are modeled on the human brain, in which information is processed in layers and the connections between these layers are strengthened based on what is learned. This is called deep learning because of the increasing numbers of layers of information that are processed by increasingly faster computers. Deep learning is enabling computers to recognize images, voice and text — and to do human-like things.

Google searches used to use a technique called PageRank to come up with their results. Using rigid proprietary algorithms, they analyzed the text and links on Web pages to determine what was most relevant and important. Google is replacing this technique in searches and most of its other products with algorithms based on deep learning, the same technologies that it used to defeat a human player at the game Go. During that extremely complex game, observers were themselves confused as to why their computer had made the moves it had.

In the fields in which it is trained, AI is now exceeding the capabilities of humans.

AI has applications in every area in which data are processed and decisions required. Wired founding editor Kevin Kelly likened AI to electricity: a cheap, reliable, industrial-grade digital smartness running behind everything. He said that it “will enliven inert objects, much as electricity did more than a century ago.  Everything that we formerly electrified we will now ‘cognitize.’ This new utilitarian AI will also augment us individually as people (deepening our memory, speeding our recognition) and collectively as a species.There is almost nothing we can think of that cannot be made new, different or interesting by infusing it with some extra IQ. In fact, the business plans of the next 10,000 start-ups are easy to forecast: Take X and add AI. This is a big deal, and now it’s here.”

See also: AI: The Next Stage in Healthcare  

AI will soon be everywhere. Businesses are infusing AI into their products and helping them analyze the vast amounts of data they are gathering. Google, Amazon and Apple are working on voice assistants for our homes that manage our lights, order our food and schedule our meetings. Robotic assistants such as Rosie from “The Jetsons” and R2-D2 of Star Wars are about a decade away.

Do we need to be worried about the runaway “artificial general intelligence” that goes out of control and takes over the world? Yes — but perhaps not for another 15 or 20 years. There are justified fears that rather than being told what to learn and complementing our capabilities, AIs will start learning everything there is to learn and know far more than we do. Though some people, such as futurist Ray Kurzweil, see us using AI to augment our capabilities and evolve together, others, such as Elon Musk and Stephen Hawking, fear that AI will usurp us. We really don’t know where all this will go.

What is certain is that AI is here and making amazing things possible.

6 Technologies That Will Define 2016

Please join me for “Path to Transformation,” an event I am putting on May 10 and 11 at the Plug and Play accelerator in Silicon Valley in conjunction with Insurance Thought Leadership. The event will not only explore the sorts of technological breakthroughs I describe in this article but will explain how companies can test and absorb the technologies, in ways that then lead to startling (and highly profitable) innovation. My son and I have been teaching these events around the world, and I hope to see you in May. You can sign up here.

Over the past century, the price and performance of computing has been on an exponential curve. And, as futurist Ray Kurzweil observed, once any technology becomes an information technology, its development follows the same curve. So, we are seeing exponential advances in technologies such as sensors, networks, artificial intelligence and robotics. The convergence of these technologies is making amazing things possible.

Last year was the tipping point in the global adoption of the Internet, digital medical devices, blockchain, gene editing, drones and solar energy. This year will be the beginning of an even bigger revolution, one that will change the way we live, let us visit new worlds and lead us into a jobless future. However, with every good thing, there comes a bad; wonderful things will become possible, but with them we will create new problems for mankind.

Here are six of the technologies that will make the change happen.

1. Artificial intelligence

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There is merit to the criticism of AI—even though computers have beaten chess masters and Jeopardy players and have learned to talk to us and drive cars. AI such as Siri and Cortana is still imperfect and infuriating. Yes, those two systems crack jokes and tell us the weather, but they are nothing like the seductive digital assistant we saw in the movie “Her.” In the artificial-intelligence community, there is a common saying: “AI is whatever hasn’t been done yet.” People call this the “AI effect.” Skeptics discount the behavior of an artificial intelligence program by arguing that, rather than being real intelligence, it is just brute force computing and algorithms.

But this is about to change, to the point even the skeptics will say that AI has arrived. There have been major advances in “deep learning” neural networks, which learn by ingesting large amounts of data. IBM has taught its AI system, Watson, everything from cooking, to finance, to medicine and to Facebook. Google and Microsoft have made great strides in face recognition and human-like speech systems. AI-based face recognition, for example, has almost reached human capability. And IBM Watson can diagnose certain cancers better than any human doctor can.

With IBM Watson being made available to developers, Google open-sourcing its deep-learning AI software and Facebook releasing the designs of its specialized AI hardware, we can expect to see a broad variety of AI applications emerging because entrepreneurs all over the world are taking up the baton. AI will be wherever computers are, and it will seem human-like.

Fortunately, we don’t need to worry about superhuman AI yet; that is still a decade or two away.

2. Robots

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The 2015 DARPA Robotics Challenge required robots to navigate over an eight-task course that simulated a disaster zone. It was almost comical to see them moving at the speed of molasses, freezing up and falling over. Forget folding laundry and serving humans; these robots could hardly walk. While we heard some three years ago that Foxconn would replace a million workers with robots in its Chinese factories, it never did so.

Breakthroughs may, however, be at hand. To begin with, a new generation of robots is being introduced by companies—such as Switzerland’s ABB, Denmark’s Universal Robots, and Boston’s Rethink Robotics—robots dextrous enough to thread a needle and sensitive enough to work alongside humans. They can assemble circuits and pack boxes. We are at the cusp of the industrial-robot revolution.

Household robots are another matter. Household tasks may seem mundane, but they are incredibly difficult for machines to perform. Cleaning a room and folding laundry necessitate software algorithms that are more complex than those required to land a man on the moon. But there have been many breakthroughs of late, largely driven by AI, enabling robots to learn certain tasks by themselves and by teaching each other what they have learned. And with the open source robotic operating system (ROS), thousands of developers worldwide are getting close to perfecting the algorithms.

Don’t be surprised when robots start showing up in supermarkets and malls—and in our homes. Remember Rosie, the robotic housekeeper from the TV series “The Jetsons”?  I am expecting version No. 1 to begin shipping in the early 2020s.

3. Self-driving cars

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Once considered to be in the realm of science fiction, autonomous cars made big news in 2015. Google crossed the million-mile mark with its prototypes; Tesla began releasing functionality in its cars; and major car manufacturers announced their plans for robocars. These cars are coming, whether or not we are ready. And, just as the robots will, they will learn from each other—about the landscape of our roads and the bad habits of humans.

In the next year or two, we will see fully functional robocars being tested on our highways, and then they will take over our roads. Just as the horseless carriage threw horses off the roads, these cars will displace us humans. Because they won’t crash into each other as we humans do, the robocars won’t need the bumper bars or steel cages, so they will be more comfortable and lighter. Most will be electric. We also won’t have to worry about parking spots, because they will be able to drop us where we want to go to and pick us up when we are ready. We won’t even need to own our own cars, because transportation will be available on demand through our smartphones. Best of all, we won’t need speed limits, so distance will be less of a barrier—enabling us to leave the cities and suburbs.

4. Virtual reality and holodecks

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In March, Facebook announced the availability of its much-anticipated virtual reality headset, Oculus Rift. And Microsoft, Magic Leap and dozens of startups aren’t far behind with their new technologies. The early versions of these products will surely be expensive and clumsy and cause dizziness and other adverse reactions, but prices will fall, capabilities will increase and footprints will shrink as is the case with all exponential technologies. 2016 will mark the beginning of the virtual reality revolution.

Virtual reality will change how we learn and how we entertain ourselves. Our children’s education will become experiential, because they will be able to visit ancient Greece and journey within the human body. We will spend our lunchtimes touring far-off destinations and our evenings playing laser tag with friends who are thousands of miles away. And, rather than watching movies at IMAX theaters, we will be able to be part of the action, virtually in the back seat of every big-screen car chase.

5. Internet of Things

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Mark Zuckerberg recently announced plans to create his own artificially intelligent, voice-controlled butler to help run his life at home and at work. For this, he will need appliances that can talk to his digital butler: a connected home, office and car. These are all coming, as CES, the big consumer electronics tradeshow in Las Vegas, demonstrated. From showerheads that track how much water we’ve used, to toothbrushes that watch out for cavities, to refrigerators that order food that is running out, all these items are on their way.

Starting in 2016, everything will be be connected, including our homes and appliances, our cars, street lights and medical instruments. These will be sharing information with each other (perhaps even gossiping about us) and will introduce massive security risks as well as many efficiencies. We won’t have much choice because they will be standard features—just as are the cameras on our smart TVs that stare at us and the smartphones that listen to everything we say.

6. Space

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Rockets, satellites and spaceships were things that governments built. That is, until Elon Musk stepped into the ring in 2002 with his startup SpaceX. A decade later, he demonstrated the ability to dock a spacecraft with the International Space Station and return with cargo. A year later, he launched a commercial geostationary satellite. And then, in 2015, out of the blue, came another billionaire, Jeff Bezos, whose space company Blue Origin launched a rocket 100 kilometers into space and landed its booster within five feet of its launch pad. SpaceX achieved the feat a month later.

It took a space race in the 1960s between the U.S. and the USSR to even get man to the moon. For decades after this, little more happened, because there was no one for the U.S. to compete with. Now, thanks to technology costs falling so far that space exploration can be done for millions—rather than billions—of dollars and the raging egos of two billionaires, we will see the breakthroughs in space travel that we have been waiting for. Maybe there’ll be nothing beyond some rocket launches and a few competitive tweets between Musk and Bezos in 2016, but we will be closer to having colonies on Mars.

This surely is the most innovative period in human history, an era that will be remembered as the inflection point in exponential technologies that made the impossible possible.