Tomorrowland is the name of a money-losing 2015 science-fiction adventure film starring George Clooney, the final episode of the fourth season of Mad Men in which Don Draper takes his children and his Secretary, Megan, on a vacation to Southern California and, most famously, is one of the themed lands at Disney’s theme parks. The original Disneyland Tomorrowland built in 1955 gave visitors a view of the National Interstate System that was to be built in the future and in 1957 the Monsanto House of the Future was opened, a plastic house with four wings cantilevered from a central plinth featuring conveniences such as picture phones and television remote controls, and it introduced many people to their first microwave oven. https://en.wikipedia.org/w/index.php?title=Tomorrowland&oldid=735338724
And today’s Tomorrowland…I opened the Wall Street Journal a couple of weeks ago to see two articles facing each other on the front page of the Technology Section. On the left side was an article describing how China was replacing workers with robots with small motor skills and on the right side was an article describing Ford Motor Company’s push into building autonomous cars.
As an example of robots with small motor skills, Butchery, was long considered the sort of skill that machines would struggle to develop, because of the need for careful hand-eye co-ordination and the manipulation of non-uniform slabs of meat. But robots cut the fat off meat much more efficiently than humans, thanks to the use of cheaper and more responsive sensors. “It’s becoming economically feasible to use machines to do this because you save another 3 or 4 per cent of the meat — and that’s worth a lot on a production line, where you can move quickly.” See http://on.ft.com/1Uj5NOp Or see this article from last May 25th in the BBC, “Apple and Samsung supplier Foxconn has reportedly replaced 60,000 factory workers with robots.” See http://www.bbc.com/news/technology-36376966
As for lawyers, a 2005 study compared a human review team against an automated document assessment system to search for relevant documents to respond to discovery in litigation. While the humans identified only 51% of relevant documents, the automated system identified more than 95%. Back then, a senior attorney had to be involved in training the system. The senior attorney would have to review and code hundreds or thousands of random documents until the system stabilized. Today, however, through a process known as “continuous active learning,” the review team can simply begin reviewing documents and the system will continuously learn from coding calls and improve its results. See http://www.lawtechnologytoday.org/2015/11/history-technology-assisted-review/ A big part of the training of first-year lawyers in large law firms was once pouring through boxes of corporate documents, learning their client’s or the Defendant’s business, as well as evidentiary concepts such as relevancy as they learned what documents to pull and what not to pull. Now those first-year associates largely watch as automation has taken over that part of their job.
And call centers; the call-centre explosion has been a colossal boon for Filipinos who speak good English. With so many employers to choose from, they can demand gyms, cafés and computer-games rooms, as well as higher pay. Experienced workers can often find managerial jobs. And though the night shift is hard, it is far better than being a maid in Saudi Arabia. Much of the call-handling and data-processing work sent overseas is basic and repetitive, says Pat Geary of Blue Prism, a British technology firm. When somebody challenges a gas-meter reading or asks to move an old phone number to a new SIM card, many databases must be updated, often by tediously cutting and pasting from one to another. Such routine tasks can often be done better by a machine. Blue Prism makes software “robots” that carry out such repetitive tasks just as a person would do them, without requiring a change to underlying IT systems—but much faster and more cheaply. The firm has contracts with more than 100 outfits. Increasingly, Western companies prod customers to get in touch via e-mail or online chat. Software robots can often handle these inquiries. The cleverest systems, such as the one Celaton, another British firm, has built for Virgin Trains, refer the most complex questions to human operators and learn from the responses. The longer they run, the better they get. Software is also making call-centre workers more efficient. It can quickly retrieve and display customer data on their screens, reducing the need to transfer callers to other departments. Software robots are only going to become faster, cleverer and cheaper. Sarah Burnett of Everest, a research firm, predicts that the most basic jobs will vanish as a result. Call-centre workers will still be needed, not for repetitive tasks, but to coax customers into buying other products and services. That is a harder job, demanding better language skills. So automation might mean fewer jobs, or at least less growth, in India and the Philippines, but more jobs in America and Europe. See http://econ.st/1mga7Q6
And truck drivers; there are 3.5 million truck drivers in America. Autonomous trucks will obviously replace drivers, an estimated 3.5 million of them, but they will make the business that cater to drivers obsolete, too. Those 3.5 million truck drivers driving all over the country stop regularly to eat, drink, rest, and sleep. Entire businesses have been built around serving their wants and needs. Think restaurants and motels as just two examples. So now we’re talking about millions more whose employment depends on the employment of truck drivers. But we still can’t even stop there. Those working in these restaurants and motels along truck-driving routes are also consumers within their own local economies. Think about what a server spends her paycheck and tips on in her own community, and what a motel maid spends from her earnings into the same community. That spending creates other paychecks in turn. So now we’re not only talking about millions more who depend on those who depend on truck drivers, but we’re also talking about entire small town communities full of people who depend on all of the above in more rural areas. With any amount of reduced consumer spending, these local economies will shrink. See http://gizmodo.com/self-driving-trucks-are-going-to-kill-jobs-and-not-jus-1705921308 Otto, a San Francisco start-up is developing autonomous big rigs and is looking for 1,000 truckers to volunteer to have self-driving kits installed on their cabs, at no cost, to help fine-tune the technology. See http://www.cbc.ca/1.3585523 and there is even a proposal for an autonomous vehicle corridor from Mexico to Canada. See http://www.cbc.ca/1.3086215 Last April 7th six convoys of self-driving trucks traveled from as far away as Sweden and Southern Germany to the Dutch port of Rotterdam utilizing “Truck platooning.” “Truck platooning” involves two or three trucks that autonomously drive in convoy and are connected via wireless, with the leading truck determining route and speed. The advantage of truck platooning was that you had trucks driving at a consistent speed, which would help traffic flow on heavily congested roads in Europe. See https://www.theguardian.com/technology/2016/apr/07/convoy-self-driving-trucks-completes-first-european-cross-border-trip
And, as for the self-driving car, “In the future, you’ll simply reach for your smartphone or another connected device and call for a self-driving car whenever you need it. Rather than spending 90 percent or more of their time parked, cars will see much higher utilization rates. That change alone would unleash a real-estate revolution in cities. Vast stretches of space now earmarked for parking would become available for other uses. To be sure, self-driving cars would still need to be stored somewhere when not in use, but there would be no need for random egress; the cars could be packed end-to-end. If you call for a car, and there isn’t already one on the road close to your location, you’ll simply get the next vehicle in line…. If the sharing model does prevail, higher utilization for each car would, of course, mean fewer vehicles relative to the population. Environmentalists and urban planners would likely be overjoyed; automobile manufacturers not so much. Beyond the prospect of fewer cars per capita, there could also be a significant threat to luxury automotive brands. If you don’t own the car and will use it for only a single trip, you have little reason to care what make or model it is. Cars could cease to be status items, and the automobile market might well become commoditized.” See http://gizmodo.com/the-rise-of-automated-cars-will-thousands-of-jobs-and-n-1702689348 On August 18th Bloomberg reported, “Starting later this month, Uber will allow customers in downtown Pittsburgh to summon self-driving cars from their phones, crossing an important milestone that no automotive or technology company has yet achieved.” See http://bloom.bg/2bzThsU
What does this have to do with intellectual property? Intellectual property may include inventions, innovations, improvements, developments, methods, designs, trademarks, service marks, trade dress, logos, slogans, trade names, Internet domain names, patents, copyrightable works, mask works, trade secrets and confidential business information (including ideas, research and development, know-how, formulas, compositions, products, manufacturing and production processes and techniques, technical data, designs, drawings, specifications, customer, provider, vendor and supplier lists, pricing, cost and benefit information, and business and marketing plans and proposals), as well as computer software (including source code, executable code, data, databases, and related documentation). Included in these listed ingredients are those which make robots, discovery software and autonomous vehicles run. And as we as a country have shown, from IBM’s glory days to the present day of Facebook, Snapchat, Google, Instagram and What’sApp, we are very good at creating those ingredients and mixing those ingredients into a brew.
But what does that brew mean to society? Neither of our candidates for President are addressing how we are going to live in Tomorrowland, a land that, as the above examples note, is visible just above the horizon. They talk about climate change, medical care, war and peace but what happens to our automobile industry when the personal car disappears, to our rural economy when truck drivers disappear and their vehicles just roll on past the small towns of America, when even skilled factory jobs are replaced by robots and skilled professional jobs, like lawyers, are reduced by the introduction of labor-saving software? How much new infrastructure will be required when cars and trucks utilizing such features as adaptive cruise control and “truck platooning” as described above allow vehicles to use less roadway? And if less infrastructure is required, what will happen to those construction jobs?
Sure, we may still need humans as caregivers for the aged, to shovel asphalt onto roads and to pick fruits and vegetables, for a while at least, but how many people desire those jobs? And McDonald’s. See http://www.restaurant.org/News-Research/News/The-future-is-now-3-robots-at-the-NRA-Show
So, in my mind, this is the big unanswered question for both our politicians and our policy makers, “How do we manage a future where, on the planet, in Tomorrowland, there will be more people than there will be work for those people to do?” and “What will those people’s lives be like?”