Tag Archives: driverless cars

What a Safer World Means for Brokers

On Nov. 20, 2018, Insurance Journal reported an article suggesting auto insurance premiums will decrease by $25 billion by 2025. To put that in perspective, that is approximately 5% of all U.S. P&C premiums. Think you’ve seen a soft market before? Just wait.

The article continued to state that new coverage lines will more than make up the difference, according to the report author, Accenture. It proposed that businesses in particular will buy $81 billion more in other lines. This means woe for the personal lines carriers and agents who have achieved far more personal lines premium growth in the last 10 years than commercial (an average annual rate increase of approximately 3.3% vs. -.1%, 2005-2017, inclusive).

The authors argue that driverless cars will make the roads safer but increase the need for product liability. I am not sure about this because it has been reported that some manufacturers are planning to forego product liability insurance on their driverless cars. Maybe they had a change of mind or the authors are providing insights missing from press releases the Securities and Exchange Commission might want to review. Or maybe the manufacturers’ contracts will place all liability on their vendors or others (like the owners who do not read their software agreements).

The authors suggest consumers, companies and governments will quickly buy much more cyber coverage. They probably do need to quickly buy more, but, with as many as 3,000 cyber forms floating around in the U.S. alone (according to a recent Rand Corp. study), what cyber is actually being purchased? The Rand study is important to understanding future cyber purchases because, as it suggests, some of the forms may not be intended to pay claims, some companies’ actuarial models may be shots in the dark and clearly some companies’ forms indicate they really do not know what they are doing (at least this is my impression of Rand Corp.’s conclusion). These are big issues that put into doubt what the cyber insurance market really even is, and what happens with the inevitable shakeout? If some companies do not really know what they are insuring (reading some companies’ forms suggest they really do not know what they are insuring) and are taking shots in the dark on pricing (and reserving maybe?), there may be a problem of stronger and smarter companies not achieving adequate market share until the shakeout occurs.

See also: Cybersecurity for the Insurance Industry  

Add to this confusion the fact that explaining cyber insurance, and explaining exactly what the different cyber forms are insuring, is very difficult. Agents need to try doing this to understand that increased cyber sales are not magically going to happen. Beware the agent who pretends that all cyber forms are the same or that, just because an insured has purchased a cyber policy, they now have “cyber” coverage. The insured may think it has much broader coverage than the carrier interprets (which will be interesting for those companies less sure of what they are even insuring; see the Mondelez v. Zurich suit for a great example). Also, after asking dozens and dozens of agents what they are even insuring when they sell a cyber policy, I’m often met with blank stares or statements that they do not understand cyber so they don’t sell cyber.

Product liability sales may increase. Product liability has been one of the most volatile major lines of P&C insurance over the last 20-plus years, so any prediction specific to this line seems problematic. Since 1996, NPW specific to product liability per A.M. Best (author’s calculation) has only increased 35%. Private passenger auto has increased 106%. In the last 10 years, NPW has actually declined 11%. I am not suggesting these results are rational, because the combined ratio for product liability is an abysmal 129% over the last 10 years. Its worst combined ratio was 159% in 2011, and its best was 84% in 2006. The volatility is absurd and does not really correlate well with NPW growth. This combination of volatility and lack of charging more premium for really horrible combined ratios makes predicting this line’s future problematic.

I hope experts’ predictions are correct regarding other lines taking up the slack. Even if correct, though, personal lines agents and personal lines carriers are going to suffer if they do not begin writing commercial. Small commercial will be hurt, too, because small commercial will lose the auto, clients seem reluctant to buy quality cyber coverage and they do not usually need product liability.

The winners, if the study’s authors’ predictions are correct, will be carriers and agents/brokers writing large, complex commercial accounts.

If the authors are wrong about companies and consumers purchasing a lot more insurance but of a different line, then the entire industry suffers mightily.

Another article in the same edition published a report from Minnesota’s Department of Labor that the state’s workplace injury and illness rate decreased in 2017 to its lowest rate since the state first began measuring it. I suspect Minnesota’s results are similar to other states. The significant advances in safety and the reduced need for employees to work in more dangerous environments relative to total employment support the probability that workplaces should be safer than ever, even in a booming economy. The workplace will become even safer, with more modular construction, better safety devices and monitoring and continuing emphasis on safety. A safer environment means less rate in this line, too.

See also: Leveraging AI in Commercial Insurance  

Maybe the industry needs to offer more law school scholarships to future plaintiff attorneys to take up the slack. Otherwise, most signs point strongly to the devaluation of insurance. Insurance is more important in a risky world than a safer world.

Maybe insurance companies will get desperate and begin insuring previously unthinkable, uninsurable perils and fill the gap that way. Whatever happens, though, insurance sales are going to change significantly. The industry is at an inflection point for carriers and distributors both. This is not a point of despair, but it is a time that requires true strategic thinking and planning to identify the opportunities that exist and to plan for those opportunities, without getting too far ahead and losing what one already has. This is hard work. It requires quite a balance, which is why dedicated strategic planning is truly required.

You can find the article originally published here.

Rapid Evolution of Autonomous Vehicles

The 2008 animated Pixar movie “Wall-E” follows the refuse-based adventures of a sentient, autonomous trash compactor whose primary function was to clean an abandoned city on a now-deserted planet Earth, long ago having been abandoned by humanity. The movie highlights some of the issues that would likely occur from human beings’ over-reliance on an automated lifestyle – issues such as waste management, obesity and human environmental impact, to name a few. “Wall-E” is set hundreds of years in the future, but some of those issues ostensibly exist in the world we inhabit today.

The transportation sector around the globe is a multitrillion-dollar industry. There’s money and mistakes to be made. While we are probably a ways off from sentient automobiles, the age of vehicle autonomy is well upon us. Every week, another company releases some update, patch or application that nudges autonomous tech in a new direction.

There have been some setbacks – name me a sector that doesn’t have any – but cars that are less reliant on humans are here to stay. This is almost universally viewed as positive, with many examples given to support this position, such as:

  • Fewer accidents.
  • A move away from owned to rented vehicles, lessening the need for parking garages.
  • A productivity increase during commuting time.
  • A reduction in traffic congestion.

There are many more, but the age of connectivity comes with risks. One must exercise caution with any kind of new technology. What happens when things go wrong? Computers malfunction sometimes; we’re all familiar with Windows’ blue screen of death.

See also: Autonomous Vehicles: ‘The Trolley Problem’  

You are turning over your most precious commodity – your family – to a computer. And if that computer fails when you are trusting it not to – let’s say when it is in full autonomous mode – how will that fail affect things? In what manner will it fail? It will likely fail however the lowest-bidding subcontractor designed it to fail.

Even if it does not fail, a computer still needs to be told what to do, at least initially. Computers can learn things and eventually make better iterative decisions based on this learning, but what do you tell a computer it should do when faced with a myriad of input data?

Autonomous vehicles (ones that fly) have been around a long time. Most commercial airliners are autonomously piloted more than 90% of the time. Aircraft, along with the routes they take, are heavily regulated. They essentially all report in to the same system around the world. There is a reason all pilots around the world must communicate in English. There has to be one universal language to avoid miscommunication and errors.

Autonomous automobiles have none of that. There is no central control, no clearing house and no standardization, to the extent that even the levels of autonomy differ by manufacturer. They can, though, roughly be classified in the following manner:

Level 0 — Nothing

The baseline since Gottlieb Daimler traded horse power for horsepower. Level zero applies to all vehicles that rely solely on humans to dictate driving actions. That is my car, and almost every car that has come before it. At best it has cruise control, but it is the “dumb” version that will crash you into a wall if you let it. Example: my 2009 Honda Ridgeline truck.

Level 1 — Driver Assistance

What does this level offer us? Some automation, but not much. For level one, you are looking at adaptive cruise control or lane departure tech to come as standard on your vehicle. While the human driver still supervises everything, the vehicle is capable of some decisions on its own. Example: your eco-friendly neighbor’s 2016 Toyota Prius.

Level 2 — Partial Automation

We get a step up from driver assistance in level two. This combines multiple automated functions such as lane assist, automatic braking and adaptive cruise control to ensure they work in a smooth, coordinated fashion. Anticipating traffic signal changes, lane changes and scanning for hazards are still the domain of the driver. Example: the Audi your boss drives that has Traffic Jam Assist as standard.

Level 3 — Conditional Automation

A car running level three automation can take full control of the vehicle during certain parts of a journey under certain conditions and within certain parameters. The vehicle will, however, turn control back over to the human driver when it encounters a situation it cannot handle or when it cannot interpret input data. The onus is, therefore, on the driver to stay alert because the vehicle may prompt the driver to intervene at any moment. The incident in Tempe, AZ, in March 2018, involving a pedestrian fatality involved a vehicle running level three autonomy. Example: Tesla’s Autopilot.

Level 4 — High Automation

An auto at level four automation does not require a human to ride along during certain journeys, subject to geographic and road-type limitations. These are currently being tested, and we should see them within the next 18 months. Think Amazon last mile and pizza delivery vehicles. Example: Johnny Cab, from the original “Total Recall.”

Level 5 — Full Automation

At level five, absent inputting the destination, which will probably be done via your phone beforehand, there is no driver involvement. You will enter the vehicle, turn on your movie or laptop and that is it until you reach your destination. Example: KITT from “Knight Rider.”

Level 6 — Beyond Full Automation

Well, there is no level six – at least yet. What would level six look like if it did exist? A teleporter? Something that transports you from your bedroom, via the bathroom and kitchen, straight to the office? A flying car? We have returned to Wall-E territory. Example: The Jetsons’ Aerocar.

Technology in vehicles is designed to assist us and make us safer. For good reason, a few of the car and tech companies working on autonomous driving have said they do not want to release anything below level four. Either force people to drive, or let the machine do all of the work. Partial implementation runs the risk of scaring people away from the technology. The more reliant you are on tech, the tougher it is when you do not have it. When, in an instant, the computer turns full control back to you because its inputs are confusing, are you ready?

See also: Autonomous Vehicles: Truly Imminent?  

What does the future look like? We should expect a reduction in the frequency of accidents, but, given the complicated nature of what is now hidden under a fender, accidents will likely cost more (increased severity).

Software updates can be problematic. They do not work well on airplanes, for example. You would not release beta software for an airliner. A recent over-the-air software update by Tesla reportedly disabled the autopilot system. Too much automation in the cockpit or car, and things can go bad when the computer gets an input it does not understand.

Walt Disney promised us self-driving cars back in 1958. They are here – somewhat – but 60 years is a long time to wait in line. As a juxtaposition to that, with robotaxis already hitting our roads, the future has arrived more quickly than most people anticipated.

15 Hurdles to Scaling for Driverless (Part 3)

This is the third part of a three-part series. You can finds part 1 here and part 2 here.

Successful industrialization of driverless cars will depend on getting over many significant hurdles. Failure only requires getting tripped up by a few of them. In part two of this series, I outlined seven key hurdles to industrial-size scaling of driverless cars. Overcoming hurdles to scaling is not enough, however.

In this concluding article, I explore the challenges to broader market acceptance. I outline eight additional hurdles related to trust, market viability and managing secondary effects. All must be overcome for driverless cars to truly revolutionize transportation.

Trust. It is not enough for developers and manufacturers to believe their AVs are good enough for widespread use, they must convince others, too. To do so, they must overcome three huge hurdles:

8. Independent verification and validation. To date, developers have kept their development processes rather opaque. They’ve shared little detail about their requirements, specifications, design or testing. An independent, systematic process is needed to verify and validate developers’ claims of their AVs’ efficacy. Many are likely to demand this, including policy makers, regulators, insurers, investors, the public at large and, of course, customers. The best developers should embrace this—it would limit liability and distinguish them from laggards and lower-quality copycats.

9. Standardization and regulation. Industry standards and government regulation cover almost every aspect of cars today. Industrialization of driverless cars will require significant doses of both, too. Standards, especially those enforced by government regulation, ensure reliability, compatibility, interoperability and economies of scale. They also increase public safety and reduce provider liability.

10. Public acceptance. Most new products take hold by attracting early adopters. The lessons and resources from that initial success help developers “cross the chasm” to mainstream success. The industrialization of AVs will depend on much earlier and broader public acceptance. AVs affect not only the early-adopting customers inside them, but also every non-customer on and near the roads those AVs travel. Without widespread acceptance—including by those who would not choose to ride in the AVs—industrialization is not likely to be allowed.

See also: Where Are Driverless Cars Taking Industry?  

Market Viability. The next three hurdles deal with whether AV-enabled business models work in the short term and the long term, both in beating the competition and other opponents.

11. Business viability. Analyses of AV TaaS business models are generally optimistic about the possibility of providing service for much less than the cost of human-driven services or personal car ownership. Current cost-per-mile estimates are nowhere near long-term targets, however. Most players are also underestimating the cost to scale. It remains to be seen whether rosy market plans will survive contact with the marketplace.

12. Stakeholder resistance. As the old saying goes, one person’s savings is another’s lost revenue. The industrialization of driverless cars will require overcoming the resistance of a large host of potential losers, including regulators, car dealers, insurers, personal injury lawyers, oil companies, truck drivers and transit unions. This will not be easy, as the potential losers include some of the most influential policy shapers at federal, state and local levels.

13. Private ownership. AV TaaS services are only a waypoint on the path to transformation of the private ownership market. If AVs are to revolutionize transportation, they will have to appeal to consumers who have long preferred to own their own cars. Privately owned cars account for the vast majority of all cars and all miles driven.

Secondary Effects. Technology always bites back. The industrialization of AVs could induce huge negative secondary effects. Most will unfold slowly, but two consequences are already concerning and must be addressed as part of the industrialization process.

14. Congestion. Faster, cheaper and better transportation will deliver greater economic opportunity and quality of life—especially for those who might otherwise not have access to it, like the poor, handicapped and elderly. But, it might also cause a surge in congestion by driving up the number of vehicles and vehicle miles traveled. This happened with ride-hail services, including Uber and Lyft. According to a recent study by the San Francisco County Transportation Authority, for example, congestion in the densest parts of San Francisco increased by as much as 73% between 2010 and 2016. The ride-hail services collectively accounted for more than half of the increase in daily vehicle hours of delay.

15. Job loss. Some argue that the history of technology, including transportation technology, shows that new services will create more jobs, not less. Few argue, however, that the new jobs go to those who lost the old ones. There’s no getting around the fact that every AV Uber means one less human Uber driver—even if other jobs are created for engineers, maintainers, dispatchers, customer service reps, etc. The same holds true for AV shuttles, buses, trucks and so on. Early AV TaaS providers will operate under an intense spotlight on this issue. Providers will have to anticipate and ameliorate potential public and regulator backlash on job loss.

* * *

There’s an old saying in Silicon Valley that one should never mistake a clear view for a short distance. The revolutionary potential of AVs is clear. Yet, we are still far from the widespread adoption needed to realize their benefits.

Don’t mistake a long distance for an unattainable goal, though. As a close observer, I am enthusiastic (and pleasantly surprised) by the progress that has been made on AV technology. Leading developers like Waymo, GM Cruise, nuTonomy and their diaspora have raced to build AVs and progressed faster than many, just a few years ago, thought possible.

See also: Driverless Cars and the ’90-90 Rule’  

Industrialization is a marathon, not a sprint. It depends on overcoming many hurdles, including the 15 I’ve laid out. The challenges of doing so are great—likely greater than many current players (and their investors) perceive and are positioned to address. New strategies are needed. A shakeout is likely.

That’s how innovation and market disruption work. That is why most contenders fail and why outsized rewards go to those who succeed. Whoever thought that a phone maker or a search engine company could be worth a trillion dollars? Is it outlandish to believe, as I still do, that driverless cars would be worth multiple trillions?

15 Hurdles to Scaling for Driverless (Part 2)

Will driverless cars (AVs, for autonomous vehicles) live up to the revolutionary potential imagined by many, including me? In part one of this series, I asked whether AVs might develop like the Segway personal transporter and be relegated to narrow niche applications. To avoid going the way of the Segway, AV developers must overcome significant hurdles to scaling, trust, market viability and managing secondary effects.

In this article, I outline the challenges to scaling. Building and proving an AV is a big first step. Scaling AVs into industrial size and strength business operations delivering transportation as a service (TaaS) is an even bigger step. Here are seven giant hurdles related to scaling:

1. Mass production. Hand crafting or retrofitting a few thousand cars with AV technology is good enough for development and testing. Industrialization will require producing hundreds of thousands of cars at scale. But, as Tesla learned the hard way, building cars at scale is more complicated than it looks.

2. Electric charging infrastructure. Almost all AV efforts are being developed on top of electric vehicle (EV) platforms. Before EV fleets can operate at scale in any market, a whole new electric charging infrastructure must be built. This will take time and lots of money.

3. Mapping. The industrialization of the detailed, high-definition (HD) maps on which AVs depend limits where AVs can operate. Even though the cars are loaded with sensors, cameras and software, they need up-to-date maps to figure out where they are and what to do.

See also: Driverless Cars and the ’90-90 Rule’  

4. Fleet management and operations. Industrialization will require flawless maintenance and efficient operation of tens of thousands of AVs widely distributed across large metropolitan service areas. Doing so will entail much more than cleaning windows and vacuuming carpets. It will entail maintaining complex computers on wheels. It will require complex predictive analytics to recharge, dispatch and load balance in response to spiky customer demand. Both public safety and business viability depend on this.

5. Customer service and experience. AV TaaS services are like a hospitality business built on a fleet of mobile hotel rooms with no on-property staff. Even the shortest trip can become arbitrarily messy and unruly—especially because there will be no human supervision in the car. Acceptable service and experience will have to extend to non-customers, as well, because AVs must interact with pedestrians, cyclists, other drivers, emergency personnel, other companies’ AVs and a host of other actors outside the car.

6. Security. Computer security is a challenging issue, in general, and networked armadas of computers on wheels will be attractive hacking targets. There are physical security issues, too. Physical security involving disgruntled drivers and bystanders, pranksters, thugs and others could also create security issues for both passengers and the public at large.

7. Rapid localization. How much of what Waymo and others are learning on the well-marked, well-lit, well-laid-out and relatively polite streets of Phoenix is transferable to the not-so-polite paved cow paths and roundabouts of Boston or the congested, pedestrian-filled city centers of New York, Paris and Beijing? Much—but not all. That is why every developer tests in multiple regions, to understand the peculiarities of local infrastructure, weather, cultural norms, etc. How fast and how well such localization can be done is another hurdle to scaling.

See also: How to Adapt to Driverless Cars  

In part three of this series, I’ll explore the challenges to market acceptance. I will discuss eight industrialization hurdles that deal with trust, market viability and secondary effects.

15 Hurdles to Scaling for Driverless Cars

Will the future of driverless cars rhyme with the history of the Segway? The Segway personal transporter was also predicted to revolutionize transportation. Steve Jobs gushed that cities would be redesigned around the device. John Doerr said it would be bigger than the internet. The Segway worked technically but never lived up to its backers’ outsized hopes for market impact. Instead, the Segway was relegated to narrow market niches, like ferrying security guards, warehouse workers and sightseeing tours.

One could well imagine such a fate for driverless cars (a.k.a. AVs, for autonomous vehicles). The technology could work brilliantly and yet get relegated to narrow market niches, like predefined shuttle routes and slow-moving delivery drones.  Some narrow applications, like interstate highway portions of long-haul trucking, could be extremely valuable but nowhere near the atmospheric potential imagined by many—include me, as I described, for example, in “Google’s Driverless Car Is Worth Trillions.”

For AVs to revolutionize transportation, they must reach a high level of industrialization and adoption. They must enable, as a first step, robust, relatively inexpensive Uber-like services in urban and suburban areas. (The industry is coalescing around calling these types of services “transportation as a service,” or TaaS.) In the longer term, AVs must be robust enough to allow for personal ownership and challenge the pervasiveness of personally owned, human-driven cars.

See also: Where Are Driverless Cars Taking Industry?  

This disruptive potential (and therefore enormous value) is motivating hundreds of companies around the world, including some of the biggest and wealthiest, such as Alphabet, Apple, General Motors, Ford, Toyota and SoftBank, to invest many billions of dollars into developing AVs. The work is progressing, with some companies (and regulators) believing that their AVs are “good enough” for pilot testing of commercial AV TaaS services with real customers on public roads in multiple markets, including SingaporePhoenix and Quangzhou.

Will AVs turn out to be revolutionary? What factors might cause them to go the way of the Segway—and derail the hopes (and enormous investments) of those chasing after the bigger prize?

Getting AVs to work well enough is, of course, a non-negotiable prerequisite for future success. It is absolutely necessary but far from sufficient.

In this three-part series, I look beyond the questions of technical feasibility to explore other significant hurdles to the industrialization of AVs. These hurdles fall into four categories: scaling, trust, market viability and secondary effects.

Scaling. Building and proving an AV is a big first step. Scaling it into a fleet-based TaaS business operation is an even bigger step. Here are seven giant hurdles to industrialization related to scaling:

  1. Mass production
  2. Electric charging infrastructure
  3. Mapping
  4. Fleet management and operations
  5. Customer service and experience
  6. Security
  7. Rapid localization

Trust. It is not enough for developers and manufacturers to believe their AVs are good enough for widespread use, they must convince others. To do so, they must overcome three huge hurdles.

  1. Independent verification and validation
  2. Standardization and regulation
  3. Public acceptance

Market Viability. The next three hurdles deal with whether AV-enabled business models work in the short term and the long term, both in beating the competition and other opponents.

  1. Business viability
  2. Stakeholder resistance
  3. Private ownership

See also: Suddenly, Driverless Cars Hit Bumps  

Secondary Effects. We shape our AVs, and afterward our AVs reshape us, to paraphrase Winston Churchill. There will be much to love about the successful industrialization of driverless cars. But, as always is the case with large technology change, there could be huge negative secondary effects. Several possible negative consequences are already foreseeable and raising concern. They represent significant hurdles to industrialization unless successfully anticipated and ameliorated.

  1. Congestion
  2. Job loss

I’ll sketch out these hurdles in two more parts to come.