Tag Archives: artificial intelligence

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.

The Hype Cycle of Insurance Disruption

The research firm Gartner has a great model for showing the relative maturity of different technologies. It’s called the Hype Cycle, and it looks like this:

hype

Source: https://en.wikipedia.org/wiki/Hype_cycle

There are five phases. First, a technology emerges, triggering a myriad of ideas for potential applications. Startups are founded, commentators predict it will change everything, incumbents include it in the SWOT (strengths, weaknesses, opportunities and threats) analysis section of their annual strategic plan. These expectations reach a peak and then start to decline as technical limitations, barriers to consumer adoption and regulatory concerns emerge. Chastened, new technologies then slowly regain credibility as people focus on how they can be applied to create real value in the here and now. Finally, they achieve mainstream adoption and acceptance.

So what would the hype cycle of insurance disruption look like, in 2016? I think something like this:

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The hottest topics of discussion in insurance right now are those left-most on the chart. We can expect the next 12 months to see seed-stage angel and VC investments in start-ups addressing the insurance implications of IoT/connected home (Domotz), blockchain (Everledger), drones (Drox) and maybe even artificial intelligence (Brolly).

Meanwhile, insurance industry incumbents will continue appointing chief digital officers, opening digital garages and launching venture funds and start-up incubators with the aim of getting a stake in the next generation of InsurTech companies. It will be a few years before we see whether these investments are creating value.

On the other side of the peak of inflated expectations, there is a deepening malaise around peer-to-peer (P2P) insurance. New York’s Lemonade may have just raised a $13 million seed round, but it has a long hard road ahead. The company’s somewhat hubristic claim to be the world’s first P2P insurer suggests executives aren’t aware of Friendsurance or Guevara and the challenges these admirable businesses have faced in creating a value proposition that consumers can understand and buy into.

P2P insurance remains intellectually exciting to insurance industry insiders but deeply unappealing to ordinary people. Do you want to feel social pressure from your friends not to make a home insurance claim if you spill paint on the carpet? No, neither do I. It will take a radically different articulation of the P2P consumer proposition for it to gain more traction — probably one that doesn’t focus at all on the product mechanics.

If the appeal of P2P insurance is in decline, big data is in the trough. There is even a bot that substitutes the phrase “chronic farting” in any tweet that mentions it. Consolidating a global insurer’s data assets on a single platform and then powering the whole organization with advanced analytics seems about as realistic as boiling the ocean.

But away from these grandiose projects, there are specific insurance use cases where big data has tangible value today. Underwriting using Twitter data is already as powerful as traditional question sets. At Bought by Many, we’ve analyzed the anonymized search data of 3 million U.K. Internet users to identify where the biggest gaps are between consumer demand for insurance and the products being supplied by the industry. Meanwhile, social media data, particularly from Facebook, is hugely powerful for insurance distribution – not just for targeted advertising but for understanding and serving people’s unique insurance needs.

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There is also a number of technologies that are mainstream in other sectors but still haven’t been fully adopted in insurance – programmatic advertising, even web analytics. The most egregious example is mobile. 75% of U.K. adults now use mobile Internet, and yet encountering a mobile-optimized or responsively designed insurance quote and buy process is still a pleasant surprise. Perhaps this reflects insurance companies’ bad experiences of developing apps that no one downloaded during the earlier phases of smartphone adoption; but surely getting mobile sorted should be a higher priority for insurers than launching an incubator. Mobile-first insurance startups like Worry + Peace and Cuvva can provide inspiration.

When it comes to technology, insurance isn’t a leader, it’s a follower. So it’s in the smart application of maturing technologies that the biggest opportunity for insurance disruption lies.

What’s in Store for Blockchain?

Blockchain, blockchain, blockchain! What does that mean for insurance? No one knows yet, but that doesn’t stop blockchain from being one of the hottest topics in the insurance industry right now. This week, I take a look at the direction this puck is heading.

Hype or reality?

Last September, the World Economic Forum published a report titled, Deep Shift – Technology Tipping Points and Societal Impact. The report is based on surveys with more than 800 executives and experts about new technologies and innovations. The point of the report is to identify deep shifts in society that result from new technologies. These include areas such as 3D printing, driverless cars, wearables and artificial intelligence.

I was drawn to shift No. 16, simply called “Bitcoin and the blockchain.” By 2025, 58% of these experts and executives believed we would hit the tipping point for Bitcoin and blockchain. This was defined as:

“10% of global gross domestic product will be stored on blockchain technology.”

To put that into context, the total worth of Bitcoin today in the blockchain is about 0.025% of today’s $80 trillion global GDP.

Also of interest, especially given that it looks like Tunisia will be the first country to issue a digital currency on a blockchain, shift No. 18 was called “Governments and the blockchain.” Here, almost three out of four in the survey group expected that “governments would collect tax via a blockchain by 2023.”

It’s a reality then!

It’s certainly looks that way. And $500 million of venture capital money in 2015 can’t be wrong, can it?

The prospect of a seismic shift on a par with the impact of the Internet is compelling. That explains all the attention, predictions and excitement about blockchain. But, if we use the evolution of the Internet as a benchmark, the development of blockchain today for commercial use is equivalent to the Internet in, say, the mid-1990s, at best.

The debates on Bitcoin, on whether private or public blockchains will be used, on Sybase vs Oracle (oops, wrong century) are yet to play out. The ability of the Bitcoin blockchain to scale to handle massive volumes at lightning speed remains unproven.

Now, just as it was in 1995, blockchain technology is at an embryonic stage. Still finding its way, it has yet to prove it is a viable, industrial-strength, large-scale technology capable of solving world hunger.

That is why I am going to focus on the use case for insurance rather than the technology itself. (For one explanation of how blockchain works, go to Wired.)

The smart insurance contract

This is getting the most attention right now. The notion of automating the insurance policy once it is written into a smart contract is compelling. The idea that it will pay out against the insurable event without the policyholder having to a make a claim or the insurer having to administer the claim has significant attractions.

First, the cost of claims processing simply goes away. Second, the opportunity for fraud largely goes away, too. (I hesitate here simply because it is theoretical and not yet proven.) Third, customer satisfaction must go up!

One example being used to illustrate how these might work came from the London Fintech Week Blockchain Hackathon last September. Here, a team called InsurETH built a flight insurance product over a weekend on the Ethereum platform.

The use case is simple. In the 12 months leading up to May 2015, there were 558,000 passengers who did not file claims for delayed or canceled flights in and out of the UK. In fact, fewer than 40% of passengers claimed money from their insurance policy.

InsurETH built a smart contract where the policy conditions were held on blockchain. Using the Oraclize service to connect the blockchain with the Internet, publicly available data is used to trigger the insurance policy.

In this case, a delayed flight is a matter of fact and public record. It does not rely on anyone’s judgement or individual assessment. It is what it is. If a delayed flight occurs, the smart contract gets triggered, and the payout is made, automatically and immediately, with no claims processing costs for the insurer and to the satisfaction of the customer.

Building on this example and applying it to motor, smart contracts offer a solution for insurers to control claims costs after an accident. A trigger that there has been an accident would come to the blockchain via the Internet from a smartphone app or a connected car. Insurers are always frustrated when customers go a more expensive route for repairs, recovery and car hire. So, with a smart contract, insurers could code the policy conditions to only pay out to the designated third parties (see related article by Sia Partners).

So long as the policy conditions are clear and unambiguous and the conditions for paying are objective, insurance can be written in a smart contract. When the conditions are undeniably reached, the smart contract pays. As blockchain startup SmartContract put it, “Any data feed trusted by a counterparty to release payment or simply complete an agreement can power a smart contract.”

To understand this better, I asked Joshua Davis, the technical architect and co-founder at blockchain p2p InsurTech Dynamis, to explain. He said:

“You need well-qualified oracle(s) to establish what ‘conditions’ exist in the real world and when they have been ‘undeniably reached.’  An oracle is a bridge between the blockchain and the current state of places, people and things in the real world.  Without qualified oracles, there can be no insurance that has any relation to the world that we live in.

“As far as oracles go, you can use either a single trusted oracle, who puts up a large escrow that is lost if they feed you misinformation, or many different oracles who don’t rely on the same POV [point of view] or data sources to verify that events occurred.

“In the future, social networks will be the cheapest and most used decentralized data feeds for various different insurance applications.  Our social networks will validate and verify our statements as lies or facts.  We need to be able to reliably contact a large enough segment of a claimant’s social network to obtain the truth.  If the insurance policy can monitor the publishing or notification of our current status to these participants and their responses accurately confirm it, then social networks will make for the cheapest, most reliable oracles for all types of future claims validation efforts.”

Is this simply too good to be true?

Personally, I don’t think it is. Of course, a smart contract doesn’t have to be on the blockchain to deliver this use case.

However, what the blockchain offers is trust. And it offers provenance. The blockchain provides an immutable record and audit trail of an agreement. The policyholder does not have to rely on the insurer’s decision to pay damages because the insurer has broken its promise to keep the client safe from harm. As the WEF report states, this is an “unbreakable escrow.” The insurer will pay before it even knows what happened.

There’s another reason for going with the blockchain: cybersecurity!

With the blockchain sitting outside the corporate firewall and being managed by many different and unconnected parties, the cyber criminal no longer has a single target to attack. As far as I’m aware, blockchain is immune to all of the conventional cyber threats that corporations are scared of.

What happens when you put blockchain and P2P insurance together?

In December, I published a two-part article on Peer 2 Peer Insurance (here are Part 1 and Part 2). When you put the P2P model together with the blockchain, this creates the potential for a near-autonomous, self-regulated insurance business model for managing policy and claims.

Last year, Joshua Davis wrote an interesting white paper called “Peer to Peer Insurance on the Ethereum Blockchain.” He presents the theory behind blockchain and the creation of decentralized autonomous organizations (DAO). These are corporate entities with no human employees.

The DAOs would be created for groups of policyholders, similar to the P2P group model with the likes of Guevara and Friendsurance. No single body or organization would control the DAO; it would be equally “controlled” by policyholders within each group. All premiums paid would create a pool of capital to pay claims.

And because this is a self-governing group with little or no overhead, any float at the end of the year would be distributed back among the policyholders. Arguably, this makes the DAO a non-profit organization and materially increases the capital reserve for claims costs.

The big question mark for this model is regulation. There still is no answer to who will maintain the blockchain code within each DAO when regulations change. But, what does seem a dead certainty is that someone, somewhere is figuring out how to solve this.

Blockchain offers the potential for new products and services in a P2P insurance model. It should also open insurance to new markets, especially those on or near the poverty line.

For now, we must watch to see what comes from the likes of Dynamis, which is using smart contracts to provide supplementary employment insurance cover on Ethereum.

Innovation will come from new players

It has been my belief for some time that, in the main, incumbent insurance firms will not be able to materially innovate from within. As with Fintech, the innovation that will radically change this industry will come from new entrants and start-up players, such as:

Dynamis

SmartContract

Rootstock

Everledger (see previous article on Daily Fintech)

Tradle

Ethereum Frontier

Codius (Ripple Labs) (update: Codius discontinued)

This is particularly true with blockchain in insurance. These new age pioneers are unencumbered by corporate process, finance committees, bureaucracy and organizational resistance to change.

Besides, the incumbent insurance CIOs have heard this all before. For decades, software vendors have promised nirvana with new policy administration, claims and product engines. So, why should they listen to the claims that blockchain is the panacea for their legacy IT issues? But,  that is a subject for another post … watch this space!

Easy Predictions on Future of Work

The trouble with our times is that the future is not what it used to be.”
– Ambrose Paul Valery – 1937

The Exaggerated Research Institute conducted a study to identify key trends that will be affecting the workforce in coming years. The research was based on interviews with leading psychics, astrologists, clairvoyants, precognitors, telepathics and other reliable sources.

FINDINGS

Future Workforce Demographics

  • The Rise of the Contingent Workforce. The future workforce will be largely composed of contingent workers, including temps, contractors, leased employees and consultants. Most of them will be kept cryogenically frozen in storage and thawed when needed.

There will be two primary categories of contingent workers:

  • Generalists will increasingly know less and less about more and more, until they know practically nothing about almost everything.
  • Specialists will know more and more about less and less until they know practically everything about nothing.
  • Workforce Diversity. By the year 2050, four generational cohorts of employees will be working together -Millennials, Centennials, Antennials and Perennials. Designing workplaces to meet all of their diverse needs will be a major challenge. For example:
    • The ideal Millennial workplace: Ping-pong tables, meditation booths, squash courts, refrigerators, nursing rooms, food courts with healthy food options.
    • The ideal perennial workplace: Mah jong tables, medication booths, shuffleboard courts, defibrillators, napping rooms, cafeterias with early bird specials.

The Future of Management Practices

  • Workforce Reduction. Companies will continue to release employees whose skills are considered unnecessary, only to end up contracting with them as consultants at greater expense. This practice will be known as dumb-sizing.
  • Workforce Terminology. The term human capital, an endearing euphemism for “people,” will evolve to primate widget.

Workforce Technology of the Future

  • The Rise of Intelligent Machines. Increasingly, automatons such as droids, robots or drones will do nearly all work currently done by human beings. Human beings will handle some work tasks that automatons consider too boring or dangerous. This shift will be fraught with controversy.
    • Humans will argue that automatons are heartless and soulless, and therefore inferior.
    • Automatons will point out that they don’t require compensation or benefits, breaks, food, vacation time, sick days or positive feedback, and that they work faster and less expensively without complaining or making mistakes. And with the right algorithms, they can fake empathy.
  • Manufacturing Technology. 3-D printers will eventually produce nearly everything, from engines to food to human body parts. Older employees will be able to print younger versions of themselves and have their brains transplanted to their reprinted bodies. Health insurance will not cover these procedures.
  • Industrial Technology. Advances in automation and software will revolutionize every industry. For instance:
    • Trucking companies will switch to driverless trucks. Truckers will be allowed to ride along, having complete control of the horn.
    • Most packages will be delivered via drones. Human employees will be used to crush and mutilate packages before shipping.
  • Communications Technology. Email will be replaced with Tmail, a system by which messages are sent telepathically into employees’ minds via tiny implanted devices. To reduce confusion with employees’ own thoughts, T-messages will be preceded by a voice announcing, “I’ve got mail!”
  • Office Technology. The typical office of the future will have only one machine, which will be a combination PC-speakerphone/vacuum cleaner/printer/scanner/fax/floor polisher/power stapler/beverage dispenser. This machine will frequently jam and run out of magenta ink. No one will know how to fix it or whom to call.
  • The Virtual Office. Many offices and factories will be completely virtual. Virtual employees will sit at virtual workstations, work in virtual teams, report to virtual managers and get virtually nothing done. Virtual managers above a certain pay grade will have virtual windows.
  • Computing Technology. The cloud will soon reach its storage capacity. From that point on, employees will store their data somewhere over the rainbow. Video goggles will replace desktop and laptop computer screens. Healthcare costs will escalate as goggled employees obliviously walk into traffic, fall down stairs and crash into furniture.
  • Commuting Technology. Inspired by George Jetson, many employees will commute to their workplaces in flying cars that transform into briefcases. GM’s flying cars will be recalled after several transform prematurely during flight.
  • The Paperless Office. By the mid 2040s, companies will realize that they have stocked millions of file cabinets containing unidentifiable documents and obsolete office supplies. To comply with auditing and risk management policies, all file cabinets will be permanently warehoused.

The Future of Learning and Development

  • Preparation for the Working World. Trivial elementary school courses such as social studies, history, art and literature will be replaced with practical content on designing e-commerce apps, managing technology start-ups, seeking venture capital and launching successful IPOs.
  • Virtual Reality Training. All employee training will be delivered via fully integrated virtual-reality helmets that will simulate the real work environment. For example, in a realistic job preview, trainees’ virtual avatars will lose all of their self-esteem by being ignored, criticized, overlooked, disregarded, misunderstood, unappreciated, excluded, undercompensated and unrecognized.

The Future of Performance Management

  • Performance Reviews. Because of its inherent inaccuracies and biases, the dreaded annual performance review process will fall by the wayside. Instead, 360-degree feedback processes will be expanded to include feedback from employees’ relatives. Subsequently, employees will petition for the return of annual performance reviews.

The Future of Rewards

  • Most future companies will pay their employees with Bit-coin, a virtual currency. Most employees will find Bit-coins virtually impossible to understand, cash or spend, even though they will be accepted at virtually all new-age coffee shops. As a result, workers will collaborate to create a bartering economy in which, for example, groceries are traded for sheep.
  • The gap between top executive pay and average employee pay will continue to escalate from the current “You can’t be serious” to “You’re f****** kidding me.”
  • In a cost-saving measure, most companies will eliminate nearly all existing employee benefits. From that point on, benefits will refer to carpeting, windows, air conditioning and chairs.

The Future of Innovation

  • The Quality Movement will devolve into a mediocrity movement when it is discovered that mediocrity can be delivered consistently at lower expense. Companies that previously had mottos like “Quality is Job 1” will switch to slogans like “Feh, that’ll do.”
  • Change Management. Companies will stop the expense associated with continual change and institute change-avoidance initiatives. Employees will receive incentives for not trying anything new or different.

The Future of Employee Engagement

  • Employee engagement surveys, which will automatically import each worker’s employee ID, race, gender, age, level, job code, manager name, work location and tenure, will remain “anonymous.”
  • Employee engagement survey reporting will become continually faster. This will make it possible for managers to ignore employee feedback more frequently, and in real time.
  • Through Six Sigma improvement efforts, many companies will successfully reduce the time it takes for post-survey action plans to be ignored, forgotten and abandoned.

The Future Work Environment

  • Flexible Work Arrangements. The work from home (WFH) movement will evolve into a work from bed (WFB) movement, as WFH employees continue to try to further reduce their commuting time. Sleepworking will be a constant challenge for management, as will safety procedures for certain jobs, such as those that involve welding.
  • Workplace Design. To optimize workspace and reduce cost, most work cubicles will be double-deckered and sized based on each worker’s height and girth. Floors will be covered with torn newspaper and partitions replaced with chicken wire. Each cubicle will include a water tube and, in larger cubicles, a running wheel.

CONCLUSION

By the year 2050, the vision of the people-less office will become a reality, as automatons make all human employees redundant. Most former workers and their families will move to Western states, where they will live in log cabins, tents, abandoned vehicles, trailers and caves. They will live off the electrical grid, subsist on fishing and farming and have perfect work/life balance. They will practice the art of storytelling, spend endless time with their families and discover true happiness.

AI’s Huge Potential for Underwriting

For decades, the insurance industry has led the world in predictive analysis and risk assessment. And today, with the treasure trove of big data available from historical processes, IoT and social media, insurance companies have the opportunity to take this discipline to a whole new level of accuracy, consistency and customer experience.

The actuarial models that were once driven solely by large databases can now be fueled with tremendous quantities of unstructured data from social media, online research and news, weather and traffic reports, real-time securities feeds and other valuable information sources as well as by “tribal knowledge” such as internal reports, policies and regulations, presentations, emails, memos and evaluations. In fact, it is estimated that 90% of global data has been created in the past two years, and 80% of that data is unstructured.

A large portion of this data now comes from the Internet of Things — computers, smart phones and wearables, GPS-enabled devices, transportation telematics, sensors, energy controls and medical devices. Even with the advancement of big data analytics, the integration of all this structured and unstructured data would appear to be a monumental achievement with traditional database management tools. Even if we could somehow blend this data, would we then need thousands of canned reports, or a highly trained data analytics expert in every operating department to make use of it? The answer to this dilemma may be as close as our smartphones.

Apps that Unleash the Power

As consumers, we are no stranger to the union of the structured and unstructured datasets. A commuter, for example, used to rely on Google Maps to get from his office to his home. But with the advent of apps like Waze, not only can he get directions and arrival times based on mileage and speed data, but can also combine this intelligence with feeds from social media and crowd-sourced opinions on traffic. Significant advances in the power of in-memory processing, machine learning, artificial intelligence and natural language processing have the potential to blend millions of data points from operational systems, tribal knowledge and the Internet of Things — using apps no more complicated than Google Maps.

Using apps that harness the power of artificial intelligence and machine learning can provide far superior predictive analysis simply by typing in a question, such as: What are the chances of a terrorist act in Omaha during the month of December? Where is the most likely place a power blackout will occur in August? How many passenger train accidents will occur in the Northeast corridor over the next six months? What will be the effect on my fixed income portfolio if the Federal Reserve raises short term interest rates by .25 percentage point?

Using a gamified interface, these apps can use game theory such as Monte Carlo simulations simply by moving and overlaying graphical objects on your computer screen or tablet. As an example, you could calculate the likely dollar damages to policyholders caused by an impending hurricane simply by moving symbols for wind, rain and time duration over a map image. Here are some typical applications for AI app technology in insurance:

Catastrophe Risk and Damage Analysis

Incorporate historical weather patterns, news, research reports and social media into calculations of risk from potential catastrophes to price coverage or determine prudent levels of reinsurance.

Targeted Risk Analysis (Single view of customers)

With the wealth of individual information available on people and organizations, it is now possible to apply AI and machine learning principles to provide risk profiles targeted down to an individual. For example, a Facebook profile of a mountain climbing enthusiast would indicate a propensity for risk taking that might warrant a different profile than a golfer. Machine learning agents can now parse through LinkedIn profiles, Facebook posts, tweets and blogs to provide the underwriter with a targeted set of metrics to accurately assess the risk index of an individual.

Underwriting

Each individual assessor has his own predilection to assessing risks. By some estimates, insurance companies could lose hundreds of millions of dollars either through inaccurate risk profiling or through lost customers because of overpricing. AI apps provide the mechanics to capture “tribal knowledge,” thereby providing a uniform assessment metric across the entire underwriting process.

Claims Processing

By unifying unstructured data across historical claims, it is possible to establish ground rules (or quantitative metrics) across fuzzy baselines that were previously not possible. Claims notes from customer service representatives that would previously fall through the cracks are now caught, processed and flagged for better claims expediting and improved customer satisfaction. By incorporating personnel records when a major casualty event occurs, such as a severe storm or flood, you can now dispatch the most experienced claims personnel to areas with the highest-value property.

Fraud Control

Integrate social media into the claims review process. For example, it would be very suspect if someone who just put in a workers’ compensation claim for a severe back injury was bragging about his performance at his weekend rugby match on Facebook.

A Powerful Value Proposition

The value proposition of artificial intelligence apps for better insurance industry underwriting and risk management is too big to ignore. Apps have been transformational in the way we intelligently manage our lives, and App Orchid predicts they will be just as transformational in the way insurance companies manage their operations.