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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.

Who Is Leading in Driverless Cars?

Imagine if you could pick between Uber drivers based on their driving experience. Would you hire an experienced driver who has logged hundreds of thousands of road miles or one who has driven just a few hundred miles? I’ll bet you’d go with the experienced driver.

Now apply the same question to driverless cars. How would you pick? The same logic applies: Go with experience.

By the miles-driven heuristic, recent reports released by the California Department of Motor Vehicles show that Waymo (the new Alphabet spinout previously known as Google’s Self-Driving Car program) is running laps around its competitors. As with human drivers, experience matters for driverless capabilities. That’s because the deep learning AI techniques used to train driverless cars depend on data—especially data that illuminates rare and dangerous “edge cases.” The more training data, the more confidence you can have in the results.

See also: How to Picture the Future of Driverless  

In 2016, Waymo logged more than 635,000 miles while testing its autonomous vehicles on California’s public roads compared to just over 20,000 for all its competitors combined.

As the W. Edwards Deming principle that is popular in Silicon Valley goes, “In God we trust, all others bring data.” The data shows that Waymo is not only 615,000 miles ahead of its competitors but that those competitors are still neophytes when it comes to proving their technology on real roads and interacting with unpredictable elements such as infrastructure, traffic and human drivers.

Now, there are lots of ways to cut the data and therefore a lot of provisos to the simple test-miles-driven heuristic.

Waymo also leads the others in terms of fewer “disengagements,” which refers to when human test drivers have to retake control from the driverless software. Waymo’s test drivers had to disengage 124 times, or about once very 5,000 miles.

Other companies were all over the map in terms of their disengagements. BMW had one disengagement during 638 total miles of testing. Tesla had 182 disengagements in 550 miles. Mercedes-Benz had 336 disengagements over 673 miles. Fewer miles might mean fewer edge cases were encountered, or it might mean that those companies tested particularly difficult scenarios. But, low total miles driven casts doubt on the readiness of any system for operating on public roads. Until other contenders ramp up their total miles by a factor or 1,000 or more, their disengagement statistics are not statistically relevant.

Tesla fans could rightly point to the more than two hundred million miles that Tesla owners have logged under Tesla’s Autopilot feature. Those miles are not considered here. (Autopilot is not defined as autonomous under California law, so Tesla is not required to report disengagements to the California DMV.) But, no doubt, all those miles means that Tesla’s Autopilot software is probably very well trained for highway driving.

What do those highway miles tell us about Tesla’s ability to handle city streets, which are more complex for driverless cars? Not much, but the 550 miles that Tesla did spend on public road autonomous testing speaks volumes about its dearth of experiential learning on city streets. (Ed Niedermeyer, an industry analyst, recently argued that most of Tesla’s 550 miles were probably logged while filming one marketing video.)

See also: Novel Solution for Driverless Risk  

It should also be noted that the reported data applies only to California; it does not account for testing in other active driverless hubs—such as Waymo’s test cars in Austin, TX, Uber’s driverless pilots in Pittsburgh or nuTonomy’s testing in Singapore (just to name a few). It is safe to guess, however, that a significant percentage of all autonomous testing has been logged in California.

Notably missing from the reports to the California DMV are all other Big Auto makers and suppliers—and other players cited or rumored as driverless contenders, like Apple and Baidu. They might well be learning to drive on private test tracks or outside of California. But, until they bring data about their performance after significant miles on public roads, don’t trust the press releases or rumors about their capabilities.

Waymo’s deep experience in California does not guarantee its victory. Can it stay ahead as others accelerate? That remains to be seen, but it is clear from the California DMV reports that Waymo is way ahead on the driverless learning curve.

Insurtech: The Approaching Storm

Customer-centricity and mobile engagement: the next wave of innovation to disrupt the insurance industry?  

The individual customer has to be at the center of the marketing strategy of every company that wants to succeed. A customer-centric marketing approach starts with the realization that there is no “average” customer. Customers have different behaviors and preferences — and this presents rich opportunities to move past a “one-size-fits-all” marketing approach. Customer-centric marketing teams think of their customer base as their greatest long-term investment.

A customer-centric approach means targeting the right customer through the right channel and sending the right message — at the right time. It also helps teams align around a strategy that will drive long-term value to the business, acquiring high-value customers and keeping them coming back.

The consumption habits have deeply changed in a competitive environment where the customers face information overload.

The smartphone has become the primary reference when searching for information, comparing products, finding the best deals and connecting with a brand/organization. The smartphone has become the first screen, the reference for our daily activities.

“Mobile is the future.” With these very words in 2010, Eric Schmidt, the then-CEO of Google and now chairman of Alphabet, gave us a glimpse of what was going to happen. And he hit the target!

As citizens and customers, we live surrounded by dozens of different devices, and the screen of the smartphone has become the main reference for all our activities. Mobile is not just another channel, it is a proxy of the customer — an entirely new lifestyle.

The awareness that the rhythm of our existence is marked by the mobile revolution is certified by three common stats:

15: The minutes between when we wake up and when we turn on our smartphones.

150: How many times we check, on average, our smartphones during the day.

177: The minutes we spend, on average, every day looking at the screen of our mobile devices.

Customers today do not go online. They live online.

Better yet, they experience an endless sequence of moments — in a nonlinear balance between the online and offline worlds.

See also: Top 10 Insurtech Trends for 2017  

Your customers are ready to buy. They are ready to buy from you. They are just asking for one simple thing: that they can receive relevant information on their smartphone when it is the right time.

According to Google research on “micro-moments” that offer memorable experiences to customers, a retail brand must develop and cultivate three qualities:

Be There: The ability to show up when and where the customer has a need or desire.

Be Useful: The ability to be there with relevant content and to become a primary reference.

Be Quick: The ability to think and act fast. Speed is essential across all stages of the customer journey.

At the core, the brand-new customer is driven by technology.

The super-shoppers are tech-savvy, and you cannot even remotely think to engage and monetize them as you did with the clients in past decades. If you do not speak the new shoppers’ language, you will never capture their attention, and, ultimately, you will lose all relevance.

What does it mean to be relevant in the mobile age? Easy. Rethink the marketing strategy, how to connect with customers (online and in-store) and how to convey contents and values.

In a few words, you must use technology to establish your brand as a trustworthy source of information and inspiration. And you must do it not once and for all, but improving day after day after day.

Study and understand the super-shopper; be present in the micro moments that matter; stay relevant; and be epic. Only then you will conquer shoppers’ hearts and minds.

Shopping in the era of micro moments often starts when people have a need or desire to purchase a product. Once they feel this need, they start looking for ideas, a search that will lead them to online communities, social networks, video tutorials and company blogs. Only then will they evaluate the different options and eventually decide what (and where) to buy.

In these moments, you have to be there and be useful to win trust and loyalty.

“Be there” means you must identify the most important micro moments and commit to being there, whenever and wherever a shopper is searching, especially on mobile.

“Be useful” means you must provide valuable contents when your customers need them, on any channel — social media, point of sale, advertising, blog, social commerce, etc.

“Be quick” means you must provide the required and valuable information at the right time and in the right manner.

Has the moment come for an old-style industry like insurance to turn the page? Several experts, managers, entrepreneurs and investors engaged in the insurance space consider that 2017 will be the year of insurtech. Some strongly believe that every successful insurance company will be insurtech soon!

An intelligent use of the technology in this industry can generate opportunities to close the protection gap, reduce the anti-selection issue, optimize loss ratio with personalized proposals and reduce overall processing cost. All this in a customer-centric approach.

The Internet of Things and artificial intelligence are undoubtedly two main drivers of the evolution in the industry, and we have seen several interesting applications already on the market. A lot of insurtech startups are investing all around the world in these technologies, which enable insurance carriers to propose innovative and customized coverage to their customers while  “blue ocean” opportunities are appearing.

See also: 10 Predictions for Insurtech in 2017  

Traditionally, the insurance industry business model is focused on:

  • Identifying the pool of customers that might have risks assessed;
  • Targeting those customers and assessing the risk for each class;
  • Selling differently priced policies and spreading the risks over the pool of customers; and
  • Trying to retain those customers as long as possible, offering lower price for longer contracts.

This approach is, by definition, based on the concept of “standardization” — the opposite of “customized” from a marketing point of view — and, even if it was one of the golden rules of the insurance business for several decades, it has become obsolete nowadays.

The insurance industry has always been data-rich, but, traditionally , it is quite unstructured, or, at least, the models used are quite old and simple.

Being connected has become the talk of the town, and insurance companies are one of the main interested parties in this discussion — some of them even being actual promoters of change and innovation.

Consumers are becoming more and more connected, whether it is at home, at work, behind the wheel, when they engage in sports or leisure activities and so on.

The surrounding environment is becoming smart and is being incorporated in the connected ecosystem, thus creating opportunities for insurance companies — opportunities that must be managed appropriately to maximize value. Here, big data analytics play a huge role, as the quantity of collected data and variables is getting higher and higher.

The IoT real-time data collection and sharing power will create significant opportunities in finer product segmentation and more specialized pools of risk and predictive modeling to better assess risk, as well as improving loss control and accelerating premium growth.

The IoT is the network or system of related computing devices and sensors, and it can communicate with other devices on the network. These objects, or “things,” are capable of transmitting data.

In the end, for insurance carriers to harness the power of the IoT, each will have to first think creatively about what data to gather and how to use it.

A system based on IoT and big data analytics can identify patterns and provide optimized solutions based on real-time input. Up-front: A seamless user-friendly interface can transform the way companies communicate with policy holders.

The IoT’s impact within insurance is coming fully into focus. At the highest level, better use of IoT and sensor data means insurers have the opportunity to:

  • Establish direct, unmediated customer relationships;
  • Gain more granular and precise understanding of who their customers are and how their needs change over time; and
  • Individualize offerings of products and features.

Within IoT applications, artificial intelligence is also helping (or disrupting, depending on how you see the matter) the sector in different ways.

The abundance of data can be used to refine customer segmentation and provide personalized offers based on personal features.

Artificial intelligence offers predictive recommendations that are backed by complex algorithms and data and have the ability to analyze process flows for bottlenecks, improving overall company and customer satisfaction. Algorithms compare answers and information provided by customers to make appropriate recommendations for each risk scenario.

The algorithms are constantly at work to better understand humans and their thought processes through machine learning, which allows AI to analyze human behavior and provide predictive consulting based on each individual’s wants and needs.

So, AI can help increase customer engagement and retention with personalized offers delivered at the right time, in the right way, at the right price.

Why Trump’s Travel Ban Hurts Innovation

Silicon Valley exports technology and imports the world’s best talent. That is how it has helped grow America’s economy and boosted its competitive advantage. President Trump’s executive order banning immigrants from some Muslim countries sent shock waves through the tech industry over the weekend because it was a loud and clear message to the world that America’s doors are now closed, and that xenophobia and bigotry are the new rules of law.

It is no wonder that executives at almost every major technology company, including Alphabet, Facebook and Apple, have made statements defending immigrants and distancing their companies from the president. These companies are worried about their survival and the future of the country.

Let there be no doubt that immigrants are essential to our economic present and future. These newcomers start a disproportionate number of U.S. businesses, particularly in advanced technologies. Immigrants and foreign-passport holders occupy a growing majority of places in graduate education programs in computer science, mathematics, physics and other hard sciences. They play an outsize role in U.S. research and innovation.

See also: An Open Letter to the Trump Administration  

A 2012 research paper I co-wrote, “America’s New Immigrant Entrepreneurs: Then and Now,” documented that 24% of U.S. engineering and technology startup companies and 44% of those based in Silicon Valley were founded by immigrants. My research also determined that immigrants contributed to more than 60% of the patent filings at innovative companies such as Qualcomm, Merck, General Electric and Cisco Systems. And surprisingly, more than 40% of the international patent applications filed by the U.S. government had foreign-national authors.

Study after study has found that immigrants are more likely to start job-creating businesses, not only in tech but across the economy. In 2014, 20% of the Inc. 500 companies had immigrant founders. That’s despite immigrants accounting for less than 15% of the U.S. population. According to research by economist Robert Fairlie for the Small Business Administration, immigrants are more than twice as likely to found businesses as non-immigrants, and 7.1% of immigrant-founded businesses export their products outside the U.S. as compared with only 4.4% of non-immigrant-founded businesses.

Clearly, blocking the path of immigrants into the U.S. cuts off the exact economic growth serum that has made America great. Creating an atmosphere where immigrants are fearful and uncertain about their future will reduce their incentives to open businesses here and stay. This is becoming even more so as other countries increasingly court educated immigrants and entrepreneurs. Those who support the president’s executive order say that the intent is to block people from countries where terrorism is sourced. But it’s not so simple.

By blocking entrance based on passport or country of birth rather than objective criteria, the executive order paints all immigrants from those affected countries and possibly dual passport holders with the same scarlet letter. What if the next Mark Zuckerberg happens to be Iranian? Or if an Einstein happened to be born in Libya? Let’s not forget that Steve Jobs’s father was Syrian — and he would have been banned from entering the U.S. under Trump’s dictate.

Yes, it is true that the affected countries are not the largest sources of immigrant entrepreneurs. But setting a precedent like this can mean that a politician can use this weapon against other countries that have become critical in supplying talent to fuel U.S. innovation. What if a frustrated president elected to block immigrants with Mexican, Chinese or Indian passports? The scenario, totally unthinkable a few months ago, is today entirely plausible.

In my 2012 book, “The Immigrant Exodus: Why America Is Losing the Global Race to Capture Entrepreneurial Talent,” I documented the stories of numerous immigrant entrepreneurs who were forced to leave the country because of shortages of skilled immigrant visas, called green cards. It wasn’t that we didn’t want these people here; American politics was caught in a political quagmire on skilled immigration. As a result, the country began suffering a brain drain, with highly skilled foreign-born doctors, engineers and scientists returning home.

With this executive order, Trump has made it clear that immigrants will have to worry about being singled out even after they have become lawful permanent residents; that their religion and place of birth may be the deciding factor in whether they are allowed to reenter the U.S. after going abroad. This will no doubt turn the trickle of skilled workers permanently leaving the country into a flood. Entrepreneurs who had wanted to come here will have now second thoughts.

See also: What Will Trump Mean for State Regulation?  

Whether or not the courts uphold the legality of the executive order, the damage has been done. Already, the number of billion-dollar technology startups, commonly called “unicorns,” that are located outside the U.. has been increasing dramatically. Fifteen years ago, almost all were in the U.S., while today 86 of the 191 unicorns are in countries such as China and India. We can expect this trend to accelerate because the Trump administration has just added fuel to the fire of innovation abroad and handicapped our own technology industry.