Tag Archives: DARPA

Why Blockchain Matters to Insurers

First, a definition. Distributed ledger/blockchain technology, increasingly abbreviated as “DLT,” transfers value in a decentralized, consensus-based and immutable manner using cryptographic tools and is different from technology today because it offers transactions occurring between unknown counterparties that are mathematically trusted in real time. DLT is at once a network and a database that can host applications like Smart Contracts, with the potential to be interoperable across trade ecosystems. This technology seems tailor-made to help administer the claims end of insurance.

Let’s talk about claims. It is well known that insurance claims are the storefront of an insurance business. Claims processing and resolution provide touchpoints for extended customer engagement, and a bad experience can poison an insurer in a customer’s mind, which can affect policy renewal. The claims experience should be seamless and easy to manage for all.

Imagine if you could smooth out your claims process so that it is more accurate, frictionless and cost-efficient and can even provide easy access to data for benchmarking and analysis to improve your customer’s digital experience.

See also: What Blockchain Means for Insurance  

I had my “aha” moment when I first learned about DLT technology. I was struck with an immediate vision of how things could be made better within the insurance industry. As a prior general counsel of an insurer, and now a consultant specializing in the strategic use of this technology, I understand how it can be implemented (once fully developed) and can envision how it can change and improve business from end to end.

Practically speaking, on the claims side, at the very least, the industry would never again have to suffer “the dog ate my homework” excuse for lost documents, duplicate or other document mishaps and related lawsuits. Claims provenance could be automatically established and adjudicated by so-called “smart contracts” (in the most general sense, they are protocols that have deterministic outcomes) in real time with an easily auditable and immutable trail. Identity proof would be less onerous. Those developments alone go a long way to reducing fraud and risk and their associated costs.

While modernizing claims processes is not a “sexy” thought, it is one that directly affects all insurers and their bottom lines by reducing risk. A small shift in the actuarial calculation based on a risk reduction goes a long way. There is not a business person on earth who does not want to increase revenue.

While there is a lot of hype, I believe we are only seeing the beginning of its potential. Education is needed. Imagination is needed. And innovation and execution are needed. The financial services industry has looked at this technology over the past year and is engaging with it, and some practical applications are expected to go into production in 2017. Insurers/asset managers should take notice. For instance, Delaware will begin using blockchain technology for UCC filings powered by Symbiont. Financial industry regulators, both domestically and internationally, are evaluating this technology and are listening and learning. In part, we owe the financial services sector a debt of gratitude for creating awareness overall.

Generally speaking, insurers have been slow to the table to learn about this technology, but it is imperative that they engage as early as possible because DLT has the potential to be very valuable for them. Some reinsurers already understand this and are experimenting. The diamond industry understands this and is experimenting with digital representation of hard assets on a blockchain for asset management and insurance purposes through Everledger. Other insurers have made some attempts to test similar concepts.

Indeed, the insurance industry can benefit on more than just the claims side.

We all know customer acquisition is the most uncertain and expensive part of the process in any business. Well-designed digital processes can prove invaluable in customer acquisition and retention. On the front end of the insurance industry, smart contracts can aid in creating easy-to-manage customer policies, which can be fed into databases and tailored and segmented in any way that makes business sense. Data management and security can be enhanced using blockchain technology. In fact, the Estonian company Guardtime has embraced the cyber security end of this technology and evolved a keyless signature infrastructure (KSI) that DARPA is verifying.

See also: Blockchain: What Role in Insurance?  

Blockchain/DLT technology is not a panacea for all. But it is worth exploring as the technology evolves. We are at an inflection point in the development of this technology—a point in time where insurers and others can have a say in how it evolves. Once standards emerge and practical applications are in production, it may be too late.

Time to get on board, insurers, and weigh in! All you need do is participate to make sure your interests are heard and accounted for.

To the insurance industry, I ask you: How do you see this technology affecting insurance?

What Liabilities Do Robots Create?

The intersection of humanity and robots is being transported from the human imagination and formed into a tangible reality. Many books and movies like iRobot and Her have analyzed various potential impacts of that intersection, but the complete intersection will actually be that of humanity, robots and liability.

It is insufficient, however, to know that advanced robotics and liability will intersect. Advanced robotics is going to thrust upon insurers a world that is extremely different from the one they sought to indemnify in the 20th century. Already, drones and autonomous vehicles are forcing some parts of the insurance sector to try to determine where responsibility exists so that liability can be appropriately assigned, and those efforts will continue for at least the next decade.

The liability created by the combination of robots operating with humanity now falls on commercial, and especially professional, insurers to engineer robotic liability products to provide clients and the global economy with stability, while providing insurers a valuable stream of revenue.

There are some ground rules that must be considered before bringing robotic liability to life. First, what is the definition of a robot? For the purposes of this paper, Professor Ryan Calo’s definition of a robot will be used. According to the professor, a robot can sense, process and act on its environment. There is also the realization that currently it may be beyond human ability to create a unified robotic liability doctrine for insurance purposes. This is largely due to the environments in which robots will exist, as well as the ramifications of those environments from a legal, physical and practical standpoint. After all, drones capable of sustained flight are inherently going to exist in a different realm from ground-based autonomous vehicles, and the same is true for robots capable of sub-orbital and intra-planetary flight. Therefore, this paper is going to focus on a discrete part of robotic liability: those robots used in agricultural fields. Another reason for focusing on one area of robotics is to keep things simple while exploring this uncharted part of the insurance sector.

See also: Here Comes Robotic Process Automation

The farmer, the field and the harvest, the most commonplace of settings, provide an area where dimensions of robotic liability can be easily analyzed and understood. Plant husbandry draws on thousands of years of human knowledge, and it is already using aerial drones and big data analytics to maximize crop yields. Additionally, the agricultural arena has a high likelihood of being an area wherein robots cause significant shifts in multiple areas of the economy.

Within the next two or three years, a robot, like this paper’s fictional AARW (autonomous agriculture robotic worker), will be created and sent to the fields to begin to replace human labor when it comes time to harvest a crop. There are multiple reasons for this belief, starting with the advance of robotic technology. In 2015 the DARPA Robotics Challenge was held, and it demonstrated the deployment of an array of robots that will be the ancestors of a robot like AARW. In that competition, robots were required to walk on uneven terrain, accomplish tactile tasks and even drive a traditional vehicle. While the robots in that challenge were not largely or fully autonomous, they are the undeniable major step toward productive autonomous robots.

There are already simple machines that can perform a variety of functions, even learning a function by observing human movements, and the gap between the drawing board and reality is being quickly eroded with the tremendous amount of computer hardware and software knowledge that is produced by both private and public institutions each month.

Moreover, there are strong labor and economic incentives for the introduction of robots into the agricultural field. Robots are able to work non-stop for 12 hours, are free from any form of health and labor laws and can have life expectancies in the five- to 15-year range. Crops are, more often than not, planted in fields with straight rows and require only the robotic ability to pickup an item, like a watermelon, take it to a bin, deposit the melon in the bin and then repeat the same steps on the next watermelon. All this requires only a modest amount of know-how on the robot’s part.

If AARW is built to industrial quality standards, then it will only require a minimal amount of maintenance over the course of each year. And if AARW is powered using solar panels, then the cost of its fuel will be included in the robot’s purchase price, which means that the minor maintenance cost along with a possible storage cost will be the only operating costs of AARW. With its ability to work non-stop and with no overhead costs for complying with human health and labor laws, AARW will be a cheaper alternative to human workers, providing a strong economic incentive for farmers to use robots in the field.

An agricultural robot will, however, create unique exposures for a farmer, and those exposures will cultivate the need for robotic liability. Arguments can be made for completed operations/product liability and technology E&O exposures with AARW in the field. However, there are multiple reasons why it would be unwise to try to relegate liability for AARW to any current product.

First and foremost, there is a strong expectation among scholars and legal experts that robots are going to do unexpected things. Imagine: At harvest time, the farmer brings AARW to the field to collect the crop of watermelons. The field happens to be near a highway on which big rigs travel, and part of the field lies next to a blind corner in the highway. As AARW successfully harvests one row after another, the farmer’s attention drifts, and she begins talking with a neighbor. Suddenly, there is a screech of tires and a loud bang as a big rig slams into AARW, which, for an unknown reason, walked into the highway.

Who should bear responsibility for the untimely demise of AARW?

If AARW were a cow, then the insurer of the big rig would have to reimburse the farmer for the loss of one of her cows. In certain respects, AARW and a cow are the same in that they can sense, process and act upon their environment. However, a cow has what is often described as a mind of its own, which is why insurance companies and the law have come to place the fault of a rogue cow on the unwitting vehicle operator instead of the aggrieved farmer.

AARW, though, is not a cow. It is a machine created to harvest produce. Does the software that controls the robot’s actions equate to the free will of an animal, like a cow? The farmer who lost the cow does not demand her money back from the rancher who sold her a reckless bovine product. Why should the creator of the robot be expected to reimburse the farmer for the loss of AARW? How does it make sense for product liability to come into play when the rancher shares no blame for the indiscreet cow? Technology companies have been extremely successful at escaping liability for the execution of poorly crafted software, so the farmer is unlikely to find any remedy in bringing a claim against the provider of the software, even if it is a separate entity from the one that assembled AARW.

Regardless of where blamed is assigned, the issue would be awkward for insurers that tried to force the liability for the robot’s actions into any current insurance product. At worst, the farmer would not be made whole (technology E&O), and, at best, changing existing laws would likely only partially compensate the farmer for the loss of AARW.

See also: The Need to Educate on General Liability  

The liability waters are already murky without robotic liability. Machine learning will likely create situations that are even more unexpected than the above possibility. Imagine if AARW imitated the farmer in occasionally giving free produce samples to people passing the field. In the absence of robotic liability insurance, who should be responsible for a mistake or offending action on the robot’s part?

It would be unfortunate to place all of the blame on AARW or the farmer. The situations also call into question the quality of programming with which the robot was created. In the paper by M.C. Elise and Tim Hwang, “Praise the Machine! Punish the Human!” historical evidence makes it unwise to expect liability to be appropriately adjudicated were a farmer to sue the creator of AARW.

With an autonomous robot like AARW, it is possible to bring into consideration laws related to human juveniles. A juvenile is responsible if she decides to steal an iPad from a store, but, if she takes the family Prius for a joyride, then the parents are responsible for any damage the juvenile causes. Autonomous robots will inherently be allowed to make choices on their own, but should responsibility apply to the robot and the farmer as it does in juvenile law for a child and a parent?

From the insurer’s standpoint it makes sense to assign responsibility to the appropriate party. If AARW entered a highway, the responsibility should fall on the farmer, who should have been close enough to stop it. Giving away produce, which could be petty thievery, is wrong and, because AARW incorrectly applied an action it learned, it remains largely responsible.

To more fairly distribute blame, it may be worthwhile for robotic liability to contain two types of deductible. One would be the deductible paid when 51% of the blame were due to human negligence, and such a deductible would be treble the second deductible that would apply if 51% of the blame were due to an incorrect choice on the robot’s part. This would help to impress on the human the need to make responsible choices for the robot’s actions, while also recognizing that robots will sometimes make unexpected choices, choices that may have been largely unforeseeable to human thinking. Such assignment of responsibility should also have a high chance of withstanding judicial and underwriting scrutiny.

Another disservice to relegating robots to any existing form of liability is in the form of underwriting expertise. Currently, most insurers that offer cyber liability and technology E&O seem to possess little expertise about the intersection of risk and technology. That lack hurts insurers and their clients, who suffer time and again from inadequate coverage and unreasonable pricing. It would be advantageous to create robotic liability that would be unencumbered by such existing deficiencies. By establishing a new insurance product and entrusting it to those who do understand the intersection of humans, liability and robots, insurers will be able to satisfy the demands of those who seek to leverage robots while also establishing a reliable stream of new revenue.

A 21st century product ought to be worthy of a 21st century insurance policy.

Another aspect of exposure that needs to be considered is in how a robot is seen socially, something that professor Calo discusses in his paper “Robotics and the Lessons of Cyberlaw.” Robots are likely to be viewed as companions, or valued possessions, or perhaps even friends.

At the turn of the last century, Sony created an experimental robotic dog named Aibo. Now a number of Aibos are enjoying a second life due to the pleasure people in retirement homes experience when interacting with them. One of the original Sony engineers created his own company just to repair dysfunctional Aibos.

While that particular robot is fairly limited in its interactive abilities, it provides an example of how willing people are to consider robots as companions instead of mechanical tools with limited value. It is more than likely that people will form social bonds with robots. And, while it is one thing to be verbally annoyed at a water pump for malfunctioning and adding extra work to an already busy day, mistreatment of a robot by its employer may be seen and felt differently by co-workers of the robot. Some people already treat a program like Apple’s Siri inappropriately. People to tell Siri that it is sexy, ask what it “likes” in a romantic sense and exhibit other behaviors toward the program, even in a professional setting, that are inappropriate. While such behavior has not resulted yet in an EPL (employment practices liability) claim, such unwarranted behavior may not be tolerated.

Consequently, the additional exposures created by a robot’s social integration into human society will more than likely result in adding elements to an insurance claim that products liability, technology E&O and other current insurance products would be ill-suited to deal with.

See also: Of Robots, Self-Driving Cars and Insurance

Advanced robotics makes some of the future murky. Will humans be able to code self-awareness into robots? Are droid armies going to create more horrific battlegrounds than those created by humans in all prior centuries? Are autonomous vehicles the key to essentially eliminating human fatalities?

However useful those kinds of questions are, the answer to each, for the foreseeable future, is unknown. What we do know for sure is that the realm of advanced robotics is starting to move from the drawing board and into professional work environments, creating unexplored liability territory. Accordingly, the most efficient way to go into the future is by creating robotic liability now because, with such a product, insurers have the ability to both generate a new stream of revenue while at the same time providing a more economically stable world.

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.