Category Archives: Forecasts

AI and the Future of Work

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Partner Content – WIRED Insider
By WIRED Brand Lab for Accenture

 

While no one knows what artificial intelligence’s effect on work will be, we can all agree on one thing: it’s disruptive. So far, many have cast that disruption in a negative light and projected a future in which robots take jobs from human workers.

That’s one way to look at it. Another is that automation may create more jobs than it displaces. By offering new tools for entrepreneurs, it may also create new lines of business that we can’t imagine now.

A recent study from Redwood Software and Sapio Research underscores this view. Participants in the 2017 study said they believe that 60 percent of businesses can be automated in the next five years.

On the other hand, Gartner predicts that by 2020 AI will produce more jobs than it displaces. Dennis Mortensen, CEO and founder of x.ai, maker of AI-based virtual assistant Amy, agreed. “I look at our firm and two-thirds of the jobs here didn’t exist a few years ago,” said Mortensen.

In addition to creating new jobs, AI will also help people do their jobs better — a lot better. At the World Economic Forum in Davos, Paul Daugherty, Accenture’s Chief Technology and Innovation Officer summed this idea up as, “Human plus machine equals superpowers.”

For many reasons, the optimistic view is likely the more realistic one. But AI’s ability to transform work is far from preordained. In 2018, workers are not being adequately prepared for their futures. The algorithms and data that underlie AI are also flawed and don’t reflect the diverse society it’s meant to serve.

How AI Could Grow Jobs: Inventing New Ones, Empowering Existing Ones

While AI will certainly displace some jobs, such displacement has occurred long before AI was on the scene. In the past century, we’ve seen the demise or diminishment of titles like travel agent, switchboard operator, milkman, elevator operator and bowling alley pinsetter. Meanwhile, new titles like app developer, social media director, and data scientist have emerged.

Daugherty and Jim Wilson, managing director of Information Technology and Business Research at Accenture Research have co-authored a book titled Human+Machine: Reimagining Work in the Age of AI. In their view, future (and current) jobs include trainers and explainers. Trainers will teach AI systems how to perform and mimic human behaviors. Explainers will liaise between machines and human supervisors.

Trainers

Chatbots have recently emerged as a new communications conduit for brands and consumers. It’s no secret though that they have often been stiff and offered inappropriate responses. For instance, we might say “It’s raining again. Great,” and humans would recognize the sarcasm. A machine wouldn’t.

Understanding language is one component of perfecting chatbots. Another is empathy. A new wave of startups is injecting the emotional intelligence into chatbot-based communication.

Eugenia Kuyda, cofounder of Replika, said empathetic chatbots like hers rely on human trainers. “In the future I think one of the most interesting areas of knowledge will be knowing human behavior and psychology,” she said. “You have to build chatbots in a way that makes people happy and want to achieve their goals. Without a certain amount of empathy, it’s not going to happen.”

In addition, companies like Facebook and Google use humans to moderate content. Facebook currently employs around 7,500 people for this purpose. Google parent company Alphabet also recently said it planned to have 10,000 people moderating YouTube content.

Explainers

Trainers bring a human element to AI systems, but “explainers” will bridge the gap between the new systems and their human managers.

C-suite executives, for instance, will be uneasy about basing decisions on “black box” algorithms. They will need explanations in plain English — delivered by a human — to ease their concerns.

Legislation is another impetus. The European Union’s General Data Protection Regulation, which goes into effect this year, includes the “right to explanation.” That means consumers can question and fight any decision made on an algorithmic base that affects them.

Such explainers will perform “autopsies” when the machines make mistakes. They will also diagnose the error and help to take steps to avoid similar mistakes in the future.

Empowering Workers, Businesses and Industries

Rather than replacing workers, AI can be a tool to help employees work better. A call center employee, for instance, can get instant intelligence about what the caller needs and do their work faster and better. That goes for businesses and industry too. In another example, in life sciences, Accenture is using deep learning and neural networks to help companies to bring treatments to market faster.

In addition to helping existing businesses, AI can create new ones. Such new business include digital-based elder care, AI-based agriculture and AI-based monitoring of sales calls.

Finally, automation can be used to fill currently unfilled jobs. As Daugherty noted recently, there is a shortage of 150,000 truck drivers in the U.S. right now. “We need automation to improve the productivity of the drivers, the lifestyle of the drivers to attract more people to the industry,” he said.

Changes We Need To Make Today

It will likely take a decade or so until some AI technologies become the norm. While that provides plenty of lead time for the transition, few companies are taking action now to train their workers. Another little-noticed problem is that the AI systems themselves are being created with data and algorithms that don’t reflect the diverse American society.

Regarding the former, Accenture research shows business leaders don’t think that their workers are ready for AI. But only 3% of those leaders were reinvesting in training. At a Davos meeting held by Accenture, Fei-Fei Li, an associate professor at Stanford University and director of the school’s AI lab, suggested using AI to retrain workers. “I think there’s a really exciting possibility that machine learning itself would help us to learn in more effective ways and to re-skill workers in more effective ways,” she said. “And I personally would like to see more investment and thought going into that aspect.”

Another issue to address in 2018 is the lack of diversity among the companies creating AI. As Li noted, this lack of diversity “is a bias itself.” Recent research from MIT has underscored this point. MIT Media Lab researcher Joy Buolamwini said she found evidence that facial recognition systems recognizing white faces better than black faces. In particular, the study found that if the photo was of a white man, the systems guessed correctly more than 99 percent of the time. But for black women, the percentage as between 20 percent and 34 percent. Such biases have implications for the use of facial recognition for law enforcement, advertising and hiring.

As such research illustrates, AI may present itself as an alien force of disruption, but it’s actually a human invention that reflects its creator’s flaws and humanity. “The effect of AI on jobs is totally, absolutely within our control,” Cathy Bessant, chief operations and chief technology officer, Bank of America, said in her Davos chat. “This isn’t what we let AI do to the workforce, it’s how we control its use to the good of the workforce.”

This story was produced by the WIRED Brand Lab for Accenture.

Behold the IoT Invasion: Eight Reasons to Plug In (Slideshow)


John McDonald, CEO, ClearObject | Mar 12, 2019 for IndustryWeek

An IoT integrator shares what big trends to capitalize on in the next few years

 

By 2021 consumer spending on digital products and services is predicted to double, and the Internet of Things (IoT) space grew just as fast in 2018. Every industry is looking for new, advanced ways to meet production and consumer demands in a world of instant gratification. These trends are some of the things we see as an IoT systems integrator that will continue in the forefront of 2019 and beyond.

IoT and data are critical for today’s operations in any industry. It’s no longer feasible to ignore the benefits for efficiency, productivity and customer satisfaction that are results of using advancements in IoT and data. Each and every industry must adopt new and inventive methods like IoT and machine learning to analyze transactions and data in any form whether it’s a car that can detect driver fatigue, preventive maintenance sensors, or nanotechnology to monitor food sources.

Click on Start Slideshow for eight areas that should see serious growth in the next few years:

Start Slideshow

John McDonald is the CEO of Fishers-based ClearObject and chair of the Indiana Technology and Innovation Policy Committee.

The World Wide Web Turns 30. Where Does It Go From Here?

Sir Tim Berners-Lee invented the World Wide Web in 1989.- Tristan Gregory/Redux

By Tim Berners-Lee, Inventor of the World Wide Web – Opinion – 03.11.19  05:00 PM for Wired

 

Today, 30 years on from my original proposal for an information management system, half the world is online. It’s a moment to celebrate how far we’ve come, but also an opportunity to reflect on how far we have yet to go.

The web has become a public square, a library, a doctor’s office, a shop, a school, a design studio, an office, a cinema, a bank, and so much more. Of course with every new feature, every new website, the divide between those who are online and those who are not increases, making it all the more imperative to make the web available for everyone.

And while the web has created opportunity, given marginalized groups a voice, and made our daily lives easier, it has also created opportunity for scammers, given a voice to those who spread hatred, and made all kinds of crime easier to commit.

Against the backdrop of news stories about how the web is misused, it’s understandable that many people feel afraid and unsure if the web is really a force for good. But given how much the web has changed in the past 30 years, it would be defeatist and unimaginative to assume that the web as we know it can’t be changed for the better in the next 30. If we give up on building a better web now, then the web will not have failed us. We will have failed the web.

To tackle any problem, we must clearly outline and understand it. I broadly see three sources of dysfunction affecting today’s web:

  • Deliberate, malicious intent, such as state-sponsored hacking and attacks, criminal behavior, and online harassment.
  • System design that creates perverse incentives where user value is sacrificed, such as ad-based revenue models that commercially reward clickbait and the viral spread of misinformation.
  • Unintended negative consequences of benevolent design, such as the outraged and polarized tone and quality of online discourse.

While the first category is impossible to eradicate completely, we can create both laws and code to minimize this behavior, just as we have always done offline. The second category requires us to redesign systems in a way that changes incentives. And the final category calls for research to understand existing systems and model possible new ones or tweak those we already have.

You can’t just blame one government, one social network, or the human spirit. Simplistic narratives risk exhausting our energy as we chase the symptoms of these problems instead of focusing on their root causes. To get this right, we will need to come together as a global web community.

At pivotal moments, generations before us have stepped up to work together for a better future. With the Universal Declaration of Human Rights, diverse groups of people have been able to agree on essential principles. With the Law of Sea and the Outer Space Treaty, we have preserved new frontiers for the common good. Now too, as the web reshapes our world, we have a responsibility to make sure it is recognized as a human right and built for the public good. This is why the Web Foundation is working with governments, companies, and citizens to build a new Contract for the Web.

This contract was launched in Lisbon at Web Summit, bringing together a group of people who agree we need to establish clear norms, laws, and standards that underpin the web. Those who support it endorse its starting principles and together are working out the specific commitments in each area. No one group should do this alone, and all input will be appreciated. Governments, companies, and citizens are all contributing, and we aim to have a result later this year.

Governments must translate laws and regulations for the digital age. They must ensure markets remain competitive, innovative, and open. And they have a responsibility to protect people’s rights and freedoms online. We need open web champions within government—civil servants and elected officials who will take action when private sector interests threaten the public good and who will stand up to protect the open web.

Companies must do more to ensure that their pursuit of short-term profit is not at the expense of human rights, democracy, scientific fact, or public safety. Platforms and products must be designed with privacy, diversity, and security in mind. This year, we’ve seen a number of tech employees stand up and demand better business practices. We need to encourage that spirit.

And most important of all, citizens must hold companies and governments accountable for the commitments they make, and demand that both respect the web as a global community with citizens at its heart. If we don’t elect politicians who defend a free and open web, if we don’t do our part to foster constructive, healthy conversations online, if we continue to click consent without demanding our data rights be respected, we walk away from our responsibility to put these issues on the priority agenda of our governments.

The fight for the web is one of the most important causes of our time. Today, half of the world is online. It is more urgent than ever to ensure that the other half is not left behind offline, and that everyone contributes to a web that drives equality, opportunity, and creativity.

The Contract for the Web must be not a list of quick fixes but a process that signals a shift in how we understand our relationship with our online community. It must be clear enough to act as a guiding star for the way forward but flexible enough to adapt to the rapid pace of change in technology. It’s our journey from digital adolescence to a more mature, responsible, and inclusive future.

The web is for everyone, and collectively we hold the power to change it. It won’t be easy. But if we dream a little and work a lot, we can get the web we want.

This story was co-published with the World Wide Web Foundation.

The Future of the Network: Get More or Get Smart

When planning for the future of the network, we can do what we have always done or we can “Get Smart.”

 

craig

By Craig Mathias, Principal, Farpoint Group | Oct 29, 2018 for ITPro Today

 

I recently did a presentation for an FCC advisory committee that’s looking into how the increasing volume of computing at the edge of the Internet is driving demand for network bandwidth. I opened my talk with a chart from the Cisco Visual Networking Index, an online document that forecasts network bandwidth demands over the next few years. So, let me cut to the chase: Cisco sees aggregate annual global bandwidth demand on the order of 292 exabytes in 2019. That’s 292 times the IP traffic volume–combined fixed and still-rapidly growing mobile–of 2000, with demand still growing and mostly driven by streaming video. The immediate conclusion is that we need to get started on adding bulk to the Internet–and our own organizational networks–to handle this load.

As it turns out, there are two key schools of thought on how to approach the network-capacity challenge. I call them Get More and Get Smart. Let’s look at each.

Get More

Get More is the obvious direction for dealing with the growing capacity challenge, and it’s really what we’ve been doing with networks all along to enhance capacity–more of the same, but faster, better and cheaper.

Get More has historically been a very reliable strategy, based on the benefits that accrue from improvements in basic technologies (primarily chips and protocols) that regularly and reliably appear at lower prices or at least with constantly improving price/performance ratios. This is the faster/better/cheaper noted above.

All we need to do, then, is simply add more of the components we already know, love and understand–like Wi-Fi access points, Ethernet switches and WAN capacity–as required, either to address growing demand or to take advantage of those newer technologies or, really, both. This path, then, really is easy: Buy what you need; add more as you need more; realize better value without much (if any) effort beyond writing a check and installing the gear (including new software, like management and analytics); and overprovision, as we must always to assure the headroom required for day-to-day growth and time-bounded traffic, as well as end user productivity. Indeed, what could be easier?

Get Smart

To be fair, the alternate strategy, Get Smart, really isn’t easier today. However, it might be much easier, and cheaper, over the long run, as the technologies involved mature. Get Smart is based on taking advantage of new technologies that present themselves in the form of paradigm shifts–getting the same job (networking) done, but in new and more productive ways.

Here are the leading Get Smart directions today:

  • SDN, SD-WAN and SD-LAN: Software-defined networking enables networks to adapt intelligently to changes in traffic patterns, security challenges and overall growth. Think “softer networks”–both wireless and wired–coupled with improved management.
  • NFV: Network Functions Virtualization moves many networking functions into high-performance but otherwise traditional computers, substituting the flexibility of software for the specialized hardware that, again, needs to be replaced via upgrades from time to time. NFV is analogous to that more familiar form of virtualization, virtual machines, that makes better use of computer power that might otherwise go to waste. You’ll frequently see SDN and NFV mentioned–and, increasingly, implemented–together, as software is at the core of each.
  • Extreme Virtualization: Indeed, the only real hardware required in most networks in the future will be Wi-Fi access points, Ethernet switches to interconnect and power those APs and what few wired elements remain, and a WAN interface device (which will almost certainly be implemented using SDN and NFV) that is analogous to today’s router but much more configurable and flexible. Everything else–most notably, management, analytics and other operational support, but also traffic management, controllers and even security–is virtualized, along with computing and storage, into the cloud.
  • Desktop Virtualization: We will likely also move much end user processing and data to the server side of the link, and again into the cloud, and thus minimize the amount of traffic we’ll need to move in the first place. Lightweight protocols implementing the remoting of screen and other user I/O, like RDP and VDI, are much more efficient, in most cases, than simply implementing client/server in the cloud. Some processing will of course be done on mobile devices, but the essentially shared and collaborative nature of today’s IT solutions minimizes the amount of computing power really required in handsets, tablets and notebooks–many of which will be thin clients, like Chromebooks.
  • AI and ML: Artificial intelligence and machine learning are going to yield far-reaching benefits across all of IT and applications in general, but in networks we’ll see much more powerful and proactive analytics engaged via a feedback link between multi-tenant cloud-based analytics and management consoles. All of this will enable most problems to be resolved automatically, even before operations pros are aware of them. Network operations will center on policy specification, rather than the low-level tweaking of router settings via a CLI.

So, how can IT management decide which of these two strategies–Get More and Get Smart–will be the best alternative in their own individual cases? Begin with the information central to operations, and how and thus where this data is most efficiently and productively stored and processed. Then think about how the creation, distribution and management of this information will evolve over time and how IT can best carry out this mission.

It’s also important to conduct a financial analysis of the two options.

Ideally, Get Smart will improve the productivity of network operations staffs, whose associated costs are a huge chunk of operating expense (OpEx). And, unlike the capital expense (CapEx) at the heart of Get More that improves over time in the form of enhanced price/performance, OpEx only grows as people get more expensive (but not necessarily more productive) over time.

This is why Get Smart is so interesting and why, we believe, this strategy will become the dominant of the two choices. Add in improved performance, reliability, security and availability, and Get Smart can’t lose–over the long run, anyway.

The right tools and techniques for any given case derive from a complete consideration of the above elements. In many cases, just more of the same will work fine. After all, that’s what most end user organizations have always done, and, as long as end users are happy with network performance and budgets remain bounded, all really is well.

But, in an increasing number of situations, adding intelligence and not just bulk will yield, we believe, far greater returns over time–in the form of improved reliability, availability, costs, capacity and productivity–especially that of end users–included in the bargain. Smart, after all, always triumphs over brute force. It just takes a while.

The power of “and”

Former GM executive Larry Burns discusses how Detroit and Silicon Valley both look to have critical roles in the future of mobility

By Dennis Pankratz, Research Manager, Center for Integrated Research, Deloitte Services LP for Deloitte Insights

Auto executive and adviser Larry Burns sees the future of mobility filled with driverless cars, with a wide range of customers, uses, and market segments—and plenty of room for innovation in both Detroit and Silicon Valley.

Few people are as deeply familiar with both the automotive industry and the technology community as Larry Burns, who spent more than three decades at General Motors, ultimately serving as corporate vice president for research, development, and planning. He is also an academic and a longtime adviser to Waymo, Alphabet’s self-driving car program. Burns’ recent book, Autonomy, offers an inside account of the efforts to develop self-driving vehicles.1 In a wide-ranging discussion, he shared his views about the future of mobility.

Derek Pankratz: You’ve been thinking about changes in transportation for a long time. Looking back at what you believed or expected 10 or 15 years ago, what has surprised you?

Larry Burns: There were a couple of really big surprises. When we finished the [Defense Advanced Research Projects Agency, or DARPA] Urban Challenge in 2007,2 we asked the head of DARPA, “What’s next?” And he said, “Well, you’ve proven this is viable. It’s really up to the commercial sector to run with it.” So all of us expected that everyone would be knocking on the doors of these young engineers to go make driverless cars happen—and quite honestly, except for Google launching its self-driving car program in 2009, very little happened. I was really surprised that the commercial sector didn’t jump at it. So I’d say my biggest surprise was how long it took for a lot of people to accept that this was real and was possible, especially the auto industry, which is so significantly impacted by what’s going on. And now there’s this stampede. Suddenly everybody’s an expert.

One other thing in terms of my own journey. When I left GM, I went to Columbia University and led a program for sustainable mobility. We looked at what you could do with a driverless, electric, shared vehicle model, and the results were pretty remarkable in terms of the number of vehicles required and the cost per mile.3 But the reality is there are almost 200 million cars and trucks in the United States,4 and a lot of people who want to have their own. So I’ve given thought to the idea of an autonomous vehicle that can be personal-use as well as shared-use, because I think the future is going to be both of those.

DP: It’s an interesting challenge. I know Deloitte’s surveys suggest that the biggest reservation people have about shared mobility is exactly that: It’s the issue of personal space and not wanting to share a confined area with somebody else.5

LB: I don’t think people will be owning their car like we do today—I expect it will be more like a lease or subscription. If you have an autonomous vehicle for your own personal use, you’ll likely want to be picked up at your door and dropped off at your door. And you won’t want to be hassled with parking your vehicle—you’ll want that vehicle to be smart enough to go somewhere and refuel or recharge and wait for you. I think that vehicle would get a lot more usage than my personal car now: When I arrive at work, it drops me off at the door, and then I could dispatch it in the middle of the day to go pick up my dry cleaning, and I could dispatch it again to go get takeout dinner and then go pick up my kids and then pick me up at work and take me back home. This whole world of a robotic personal valet is very intriguing to me; I think it’s going to eliminate the need for owning a second and third car initially and, ultimately, owning a car altogether.

Some worry that additional road miles from both shared and personal usage will cause more congestion, but for those people who are taking trips they couldn’t before—due to their age or a disability, for example—and are now able to participate more in society and the economy, that’s a good thing. We should be celebrating those miles. It’s also worth keeping in mind that if vehicles are operated as a fleet, you’re going to be optimizing the use of that fleet. Ride-hailing providers don’t operate like a fleet—they are a bunch of individual agents trying to get matched up with a ride. Our work at Columbia showed that you want to simultaneously have very high fleet utilization and very low empty miles—miles with no passengers in the car. The business reality of fleet management will help us on the congestion front.

DP: I think about that personal-valet model a lot. I live in a fairly rural area in Colorado where a shared fleet model doesn’t seem to make sense. There are all of these small and medium towns where it’s hard to see how you get the utilization to make it worthwhile, so the dedicated-use approach seems natural.

LB: Fifty-three percent of Americans say they live in suburbs, and 21 percent in those rural towns that you’re talking about, which is a nontrivial slice of the population. And that’s what’s so exciting about the future autonomous electric vehicle market. There are going to be a lot of market segments, and that provides great opportunities for innovative companies to define their brands, find their niches, and deliver real value tailored to those opportunities.

DP: You briefly mentioned electric vehicles. When you were working on the AUTOnomy concept car at GM in the early 2000s, you built around hydrogen fuel cells.6 My impression today is that there is a lot more activity around battery electric vehicles. Any thoughts on the pros and cons of those two different types of power sources and their future prospects?

LB: If I could change one thing in my public rhetoric in my role at GM, I probably would never have uttered the words fuel cell. I would have called it a hydrogen battery instead, because to be honest, they’re very similar. And progress on hydrogen storage, production, and distribution and fuel cells has been very impressive. Germany just announced that it’s going to have trains operating on hydrogen fuel cells,7 and there are over-the-road trucks being developed that use hydrogen fuel cells.8 So I think this is not battery or fuel cell. I think it’s an and. You’re going to have a lot of synergy in the propulsion system around that and; depending on which market you’re dealing with, hydrogen and fuel cells are going to find their role.

DP: That and point is really interesting, because it’s always presented as one versus the other.

LB: One of my biggest lessons is the power of and. A lot of business leaders get trapped thinking they have to select between A or B. And they forget to ask the question, “What about A and B?” What I have found over the years is that “A and B” often beats A or B by themselves. I think it’s hugely important to find the power of and.

DP: Another topic that’s often posed as a dichotomy: the role of vehicle-to-vehicle [V2V], vehicle-to-infrastructure [V2I], and vehicle-to-everything [V2X] communication. Some people say it’s critical and we’ve got to have it in some form. Others say it’s actually superfluous, or that it would be nice to have but is too expensive and takes too long to build out, so we’re going to keep everything onboard the vehicle.

LB: It’s another beautiful example of the power of and. For two cars to talk to each other, both need to have enabling hardware and communications technology. For V2I, the infrastructure is pretty expensive to deploy. But in time, as we get to Gen-2, Gen-3 autonomous systems, I think you’re going to see V2V and V2I become a way to reduce cost and perhaps even improve performance. I’ve learned to never rule out any technology. I dedicated my book Autonomy to engineers. Engineers make what’s possible real; that’s what we do.

DP: Let’s talk about yet another apparent binary choice between developing advanced driver assist features like automatic emergency braking or lane departure correction, and aiming for “fully” autonomous systems that don’t anticipate a human taking control. How do you see Level 2 and 3 automation playing into this whole picture?9

LB: I’ve been an adviser to Waymo, Google’s self-driving car project, since January 2011, and they made a really important decision that they were going to develop autonomous systems for only where there’s no human involved at all. If our goal is to eliminate over 90 percent of crashes, we really need to go for Level 4 and Level 5, full autonomous. I believe the right thing to do is to get the driver out of the loop altogether: The situational-awareness challenge of asking someone to reengage in the driving task when they’ve been sitting there not driving for 20 or 30 minutes is a tougher problem to solve than getting the system to autonomously handle 99.99 … percent of the stuff that happens in the world. With that said, I think it’s useful to be developing emergency braking systems, full-speed adaptive cruise control, lane keeping, stability control. That’s been good for safety purposes. But at the end of the day, I believe the objective should be to get to Level 4, starting in a geo-fenced area that’s big enough to have commercial value.10

DP: It seems safe to say that you’re a believer in the opportunities around autonomous vehicles. What do you see as the biggest hurdles to widespread adoption? Is it technological, social, regulatory, or something else?

LB: My biggest fear is that people will make premature judgments about what we’re doing, whether out of fear or just not knowing. Have you had a chance to ride in a driverless car?

DP: I have.

LB: So you have a different experience than someone who hasn’t. My first ride on public roads was in late 2010. I engaged the system. My hands were shaking over the steering wheel. My feet were nervous over the pedals. But within five minutes, I was relaxed; I realized this car was doing everything I would do as a driver and even better. And I suddenly realized I had no desire to change lanes and try to get ahead of somebody in front of me because I had my time to myself. I think this is all about people understanding what’s possible in their lives and what’s possible with the technology. I worry about people coming to a premature judgment and therefore resisting. And I very much worry about players who have a strong vested interest in the existing roadway transportation system.

I’m not worrying about the technology—I have not seen anything come up yet that says we’ve hit the wall and that we can’t keep finding solutions to those driving challenges that are the most difficult that we face today as humans.

DP: It’s another and moment, although maybe one that could slow progress. You can imagine hesitance or uncertainty by the public combined with a variety of vested interests that are able to capitalize on a moment where there’s no broad popular support.

LB: It’s going to play out with a tipping point. There’s this tendency to want to look into the future to know how big it’s going to be and when, to predict market shares and penetrations. That’s impossible. I focus more on that magical moment when market value exceeds price and price exceeds cost. The technology is proven, the customer value is proven, the business opportunity is proven, the regulatory barriers are not there, and it becomes clear this is now just a question of scaling through a series of generational deployments. That magical moment is within a three-to-five-year window, unless these vested interests push back so hard that they slow things down.

DP: Related to the hurdles, I’m personally very interested in the psychology or sociology of car ownership, particularly in the United States. Car culture is deeply embedded in a lot of places. The car is more than just a way to get around—it’s a longstanding symbol of who we are and who we want to be.11 Is that a significant barrier?

LB: Another very good question. I think about it through the lens of my two daughters, who are 30 and 27. My coming of age was when I got my driver’s license and my first car. Their coming of age was their first cellphone, not their first car. Over the last 10 or 15 years, I’ve asked them what would you give up first—your cellphone or your car? And they say they’d give up the car before they’d give up their handheld device. Younger generations are expressing themselves in a much different way than just through car ownership.12

DP: What about some of the nightmare scenarios or unintended consequences of these new mobility innovations? Many cities are already dealing with an influx of ride-hailing vehicles, and you mentioned sending your self-driving car to pick up your dry cleaning. You’ve done detailed modeling on a number of cities looking at what shared autonomous vehicle adoption could look like. Any insights?

LB: At Columbia, we asked the question: “To make all the one- or two-person trips that automobiles currently make, how many tailored-design driverless electric vehicles would you need?” In city after city that we studied, you could replace all of the cars with a fleet that’s 15 percent the size and still make all the trips that are being made. In simulations, those vehicles were picking people up in two to three minutes. We had empty miles on the order of 5 percent of loaded miles. How? It has to do with population density. In cities like Ann Arbor, the probability that somebody is requesting a trip nearby just as I am being dropped off is pretty high. So a properly managed, optimized fleet would take a lot of cars out of the system.

Now, not everybody’s going to want to share a car. I accept that. Let’s say I’m at home cooking dinner for friends, and I realize I forgot to buy wine. I dispatch my personal robotic valet to the wine store to pick up the wine and come back. Would you call that an empty mile? I still would have made that trip driving my own vehicle. Today we have a system that is not optimized for fleet utilization. It just isn’t. But if you’re in the fleet business providing transportation services, a penny per mile really matters.

DP: We’ve largely been focused on the movement of people, but there are big changes happening with the movement of goods as well.

LB: There are really two big opportunities with goods movement, and we may see commercially viable businesses at meaningful scale sooner with goods movement than people movement. The first opportunity is in long-haul trucking. The most recent numbers from the American Trucking Association indicate that an average driver makes about 73 cents a mile, wages and benefits.13 That’s 47 percent of the cost per mile for over-the-road trucking. But not only would self-driving trucks save the 73 cents a mile—you have the opportunity to expand your daily service area because you don’t have driver work rules; an autonomous tractor could conceivably go 24/7 or 23.5/7 based on maintenance. That’s really important for e-commerce. And when you think about all of the parts on a tractor that are there because there’s a driver—the windshield, doors, side windows, seats, air-conditioning, heating, driving controls—it’s easy to convince yourself that the pile of parts you no longer need will cost more than the parts you’re going to add to make the tractor autonomous.

On the other side is package delivery, and it becomes even more interesting when the vehicles doing local package delivery can be the same vehicles you’re using for moving people around, and they can have different temporal patterns throughout the day. Maybe more of the packages are getting delivered at night. That might improve fleet utilization and congestion in urban areas.

DP: Speaking of urban mobility, we talked about autonomous vehicles and changes to the car. We’re also seeing other kinds of micro-mobility popping up: bikesharing, e-scooters, micro-transit vans. How do you see those fitting into a world of shared autonomous fleets?

LB: Well I think it’s that key word again: and. This isn’t about picking one winner to replace the more than one billion cars in the world. I’m very excited by all of those modes that are cropping up, and I think they’re going to be enhanced by the ability to seamlessly interface with them via apps. My long-term vision is for one totally integrated transportation system where you’re able to coordinate the movement of people and goods using these different modes in a seamless way. Deloitte is doing some important work on that, and I think that’s where this is headed.

DP: We’re pretty bullish on the idea of digital mobility platforms for cities.

LB: I think you should be.

DP: We’ve talked here about some pretty momentous changes unfolding. What does all of this mean for players in various industries? You’re in a somewhat unique position in that you’re a longtime veteran of the automotive industry and also been closely involved with one of Silicon Valley’s most prominent projects in this area.

LB: The original subtitle for the book Autonomy was “The race to build the driverless car and how it will reshape our world.” Our editor suggested we change the word race to quest. It seems like a simple change, but we kicked off the book with a sense of Silicon Valley versus Detroit, and by the end of the book it’s Silicon Valley and Detroit. The tech community has brought enormous insight and value; they have been the catalysts to bring this change about. But in those early days, those tech players were not fully appreciating how hard it is to design, engineer, validate, and manufacture a car at the scale at which the auto industry operates. What’s reassuring to me now is that the auto industry is working with Silicon Valley on their autonomous R&D. And Silicon Valley has turned to the auto industry for the kinds of vehicles they need to keep learning. So I think you’re seeing it as an and.

People ask me a lot, “Who’s going to win?” I think you’re going to see an ecosystem emerge not unlike the one that emerged with the internet. I’m not at all convinced that there’s going to be a single vertically integrated player that emerges from this that can do the driving system, the vehicle, the transportation system operations, the brand building, and all of that. I think you’re going to see quite a bit of codependency emerge. But those who become dominant in certain parts of that ecosystem could do really well.

DP: And does seem to be the theme of a lot of things happening in mobility. Let’s focus in on the automotive industry. If you were in an automaker’s shoes today, what do you think they should be doing to be ready for the future to best position themselves?

LB: They’re in a tough position because they have to continue to keep their legacy business viable while trying to pivot to these new businesses where they don’t have the core competencies and they don’t have infinitely deep pockets. That’s a really, really tough puzzle to solve.

With all of that said, autonomous vehicles won’t work without the vehicle, and the vehicles are hard to do. I think the big concern for the industry is that those vehicles are going to become more commodity-like. The engineering of the vehicle becomes much simpler down the road when it’s electrically driven, doesn’t require a human driver, and you get most of the crashes out of the system. And I don’t think the differentiator in the market is going to be chrome and fenders and fascia and the shape and the color. It’s going to be very much the overall experience that customers have, and that experience is going to be determined more by software and data and analytics than the traditional basis of competition in the auto industry. There are going to be some really tough portfolio decisions. Which parts of the traditional business do I want to hang with? Where is the profit? How do I pivot to this future of mobility that we’re talking about today? Can we attract the best talent to play in that race? Bottom line: The traditional players in the century-old roadway transportation system, including auto, energy, insurance, and finance companies, must get in front of the inevitable and make hard choices on “where to play” and “how to win” in the future.

DP: You’ve neatly framed the challenges of balancing today’s business with tomorrow’s needs. When you think about the future of mobility, what’s your greatest hope?

LB: My greatest hope is that we realize what I call the age of automobility—a convergence of autonomous electric vehicles deployed in transportation services—as fast and as soon as we possibly can with appropriate risk management. We shouldn’t lose sight of the fact that this is a once-in-a-century opportunity to simultaneously deal with 1.3 million fatalities worldwide per year on roadways, to deal with congestion, to deal with dependence on oil in transportation, to deal with the land use that comes with three parking spots per car in the United States, and to deal with equality of access. The deaths and injuries from crashes alone—it’s epidemic in scale. If I just created a cure for cancer and it held promise to save a lot of people with cancer but some could still die from the treatment, I think we’d get on with it; we’d find a way to manage that. We ought to look at autonomous vehicles as a cure for the roadway transportation epidemic and think about their deployment the way we test and deploy vaccines.

So I have this fixation: I want to get to the anticipated benefits. This convergence of technology and business models really can have a significant, meaningful impact and bring more transportation services at lower cost to more people. There’s an opportunity to have radically better services at radically lower consumer and societal costs.

Endnotes
  1. Lawrence D. Burns with Christopher Shulgan, Autonomy: The Quest to Build the Driverless Car—and How It Will Reshape Our World (HarperCollins, 2018). View in article
  2. The Urban Challenge was a 2007 competition sponsored by the Defense Advanced Research Projects Agency in which teams had to construct an autonomous vehicle able to navigate an urban environment, including merging, passing, parking, and crossing intersections. DARPA, “Urban challenge,” accessed October 15, 2018.  View in article
  3. For instance, see Benjamin Zhang, “This study revealed the staggering potential of self-driving cars,” Business Insider, June 2, 2014. View in article
  4. Bureau of Transportation Statistics, “Number of U.S. aircraft, vehicles, vessels, and other conveyances,” accessed December 10, 2018. Number cited is for light-duty vehicles, short wheel-base, 2016. View in article
  5. Deloitte Global Automotive Consumer Study 2019, forthcoming. View in article
  6. “AUTOnomy” was a GM 2002 concept vehicle built around hydrogen fuel cell motors, drive-by-wire technology, and a skateboard-like chassis. See Burns and Shulgan, Autonomy. View in article
  7. AFP, “Germany rolls out world’s first hydrogen train,” France 24, September 17, 2018. View in article
  8. Kristin Lee, “Toyota’s new hydrogen fuel cell truck has a 300-mile range,” Jalopnik, August 1, 2018. View in article
  9. The Society of Automotive Engineers has identified five levels of vehicle automation, which the National Highway Traffic Safety Administration (NHTSA) subsequently adopted. See the NHTSA, “Automated vehicles for safety,” accessed December 12, 2018. View in article
  10. David Roberts, “Here’s how self-driving cars could catch on,” Vox, May 9, 2018. View in article
  11. Robert Moor, “What happens to American myth when you take the driver out of it?,” New York Magazine, October 17, 2016; Brandon Tensley, “How will pop music adapt to autonomous cars?,” Slate, March 15, 2018. View in article
  12. Millennials may be only delaying car purchases rather than eschewing them, but their attitudes toward driving do seem distinct from those of previous generations. See Henry Miller, “How traveling by car is changing under millennials,” Matador Network, January 22, 2018; Mary Wisniewski, “Why Americans, particularly millennials, have fallen out of love with cars,” Chicago Tribune, November 12, 2018; and Kevin Drum, “Raw data: Kids and their cars,” Mother Jones, May 12, 2018. View in article
  13. American Transportation Research Institute, “An analysis of the operational costs of trucking: 2018 update,” October 2018. View in article
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