Trumping the Danger of Outsourcing…


Copy Cat

Photo by Andreas.


The Trumps just can’t make up their minds about outsourcing! While the Donald says he wants to stop America from outsourcing, he just can’t seem to stop himself. Or his wife, Melania! Earlier yesterday, Melania told NBC’s Matt Lauer that wrote she whole speech herself (“with as little help, as possible”) Yet, some of the wording looks suspiciously like a speech by Michelle Obama. As we say in outsourcing, “Never outsource your core!” We also say, “outsource without the right partners, you might see your mistakes on the front page of the Wall Street Journal.” Hmmm… looks like Melania is learning this the hard way!

For a high-stakes speech, it makes perfect sense to give the task to a professional writer. I’m not sure who they picked, but the Trumps might have been better off using fiverr or gighours. Just to be sure that your writer doesn’t take any short-cuts, you might also want to use a good anti-plagiarism tool. Grammarly and other on-line services quickly find if sections of your document have been “re-cycled” from earlier speeches.

The speech issue was a blessing for the Trumps, because the press forgot about Melania’s dress, which was designed and manufactured offshore in Slovenia. You can see why Melania might want to promote a designer from her home country. But is a “Make America Great” rally the best place to showcase Eastern European fashion??

The day after the speech, the amount of help Melania had to do the writing (according to a campaign aide) had swelled to a full “team”. Are we making too much of this? Shouldn’t we give Melania the benefit of the doubt? It  could be a one in a million coincidence. Melania might have written from the heart, and just came up with the same words as Michelle Obama. Could it be that the Trumps and the Obamas are basically the same? Could Melania and Michelle really want the same thing for America, after all?

Not at a Republican Convention… stick with plagerism! Don’t expect an apology to the American people or an explanation from Melania. I wonder if Melania’s pre-nup limits how many times she can speak to the press? Do expect an explosive attack from the Donald soon. At least that’s my Niccolls worth for today!

Posted in Unique Ideas | Tagged , , | Leave a comment

Beyond UBER: Planes, Trains and Helicopters Go Autonomous

CrashOver the past few months, we’ve discussed UBER’s need to turn their growing fleet of cars into an army of robots. UBER is under huge pressure to become profitable, and their quickest path to the greatest profitability is through autonomous cars. But UBER is not alone. Every form of transportation is turning towards some form of autonomous driving. Increasingly, though, the motivation (at least publicly) is not just profit. Robot ships, planes, and trucks are SAFE ships, planes, and trucks.

Individually owned cars will definitely benefit from self-driving cars. However, drivers are not actively demanding autonomy. Most car buyers think of autonomy as a luxury feature, not a safety device.

Even so, there are some individual groups that should start thinking about safety. Do you have a teen who will soon get their driver’s license?  Are they asking for their own car? Do you own an expensive new car that is a little too good to hand over to a new, inexperienced driver? An account with UBER might be a better option than handing your kid the keys. What about your parents or grandparents? Have health issues diminished their ability to drive? An autonomous car could extend their ability to live independently for years to come.  

Coalitions for Autonomous Cars are being formed by car manufacturers, technology firms, and transportation firms. Their mission is to make Americans aware of the high cost of our car-centric culture. For example, every year in America there are 35,000 automotive deaths, and four million accidents, plus a half a trillion dollars for hospitalization, car insurance, and vehicle repairs. That’s a very high price, and a very powerful argument for getting as many autonomous cars on the road, as soon as possible!

The trucking and transportation industry is aware of even more reasons for autonomous cars. They realize that autonomous vehicles open up possibilities for much higher profits. The cost of the extra equipment to make a vehicle autonomous would be paid off in a few months, at most, for a heavily utilized truck. These savings don’t just come from eliminating truckers from the payroll. Robots, you see, drive differently from human beings.

Unless someone tampers with their programming, robots must always obey the law, and must follow the instructions they are given. Human truckers are only loosely bound to the law and instructions from the Boss. Truckers routinely drive over the speed limit, and intentionally break the law.

Because humans must eat and sleep, they must also make compromises with delivery schedules. An unscheduled nap on a long trip may require speeding to make up lost time. Not taking that nap may cause an accident, especially if the driver is unlucky enough to be speeding through a patch of bad weather. Good drivers are motivated by profit, and want to complete a job as quickly as possible and then pick up the next load. Unfortunately, start, stop driving isn’t very efficient. Fuel is the largest cost for trucking (about 39%), followed by the cost of the driver. A robot driver that never sleeps, drives at a steady rate maximum rate, and almost never gets into an accident would save a trucking firm a LOT of money. A human driver could try to drive like a robot, but human emotions… getting angry at other drivers, panicking when you’re late, and other all too human reactions… would make most humans poor copies of real robots.

Business owners clearly have their foot on the gas for autonomous vehicles, but Federal and local government officials are standing on the brake. Today, it’s perfectly legal for a U.S. citizen to turn on an (approved?) autonomous driving system. After all, drivers have been using cruise control, automated parking, collision warning and automated braking for years. There is no problem if a driver turns on these features, and takes their hands off the steering wheel.

However, there is a problem when the car has no driver. Lawyers, judges and insurance companies aren’t quite sure who is responsible for the car when it’s driving itself. Car manufacturers could just throw a robot driving system into an existing car design, or they could do something revolutionary. They could throw out the steering wheel, get rid of the driver’s seat, and have all the passengers face each other. A sedan could be turned into an office on wheels, or maybe a bedroom when the office is hours away. A new class of cars would be the biggest thing to happen to the auto industry since the SUV.

But there may be even more going on in the air, than on the ground. Think about every flight you’ve been booked on that was cancelled or delayed. If your plane waits on the tarmac too long, or when your flight crew racks up enough hours, the plane goes back to the terminal and the flight is cancelled. Of course, the deliberate crash of Germanwings flight 4U9525 makes us ask ourselves new questions about the reliability of human pilots.

While big jets have the same semi-autonomous features (such as autopilot) as premium cars, these jets have not yet sold seats for autonomous flights. It will be phased in, perhaps starting with short distance connecting flights, or perhaps air cargo will lead the way, but it will happen. Just this week autonomous planes took another major step closer, as a commercial helicopter took a 30-minute flight in Connecticut.

Trains are a very mature form of transportation, but even trains have slowly added autonomy features. Today, whenever we have a train wreck, whether is it a cargo or a passenger train, news stories instantly ask, “Why didn’t the train have a computer to limit its speed, slow it before a turn, or slam on the brakes before the wheels left the track?” The next question is often, “Where was the driver?” Or, “How COULD the driver text, while the train was in a high-speed turn?” The same bad judgement and inattention that car drivers exhibit are being seen in train accidents.

Which raises a very interesting question, “Rather than a piecemeal approach to making trains more automatic, and safer… why not go all the way and install a robot driver?   

We’ve reached the tipping point, and autonomous vehicles are inevitable. Will they take over tomorrow, or at some time in the far future? I’d bet on a rapid implementation! Yes, there are piles of money to be made by replacing human drivers with robots, and the average American consumer will be the beneficiary as transportation costs drop by hundreds of billions of dollars. Even more importantly, tens of thousands of American lives will be saved every year (and many more crippling accidents avoided) as robots replace human drivers. Expect to hear lots more about the life savings benefits of autonomous vehicles… at least, that’s my Niccolls worth for today!

Don’t agree? Have other opinions? Share your opinions and ideas about autonomous cars and vehicles here! I’m listening, tell us what you think!   


Posted in Uncategorized | Leave a comment

Another Step Closer – UBER’s Pittsburg Pilot

UBER car

It is with a heavy heart that I tell you that all I have predicted is coming to pass. Hmmm… OK, I admit it. It is with joy and glee, and a bit of a dance that I tell you, “I told you so!”. UBER has started its early stage pilot of robotic cars in Pittsburg.  UBER bought out the robotics staff from Carnegie Mellon, and other robot labs, and has consolidated the team in Pittsburg. Not surprisingly, their early tests are going to be close to their robot headquarters. UBER’s somewhat clunky Ford Fusions, equipped with early versions of their custom radar systems and cameras, are now on the streets of Pittsburg. The earliest of the early test show that robots drivers are better than people when it comes to driving!

What exactly did I tell you would happen? First, UBER would develop its own robotic technology, probably partnering with a major car company, to launch a driverless car service. Second, once are on the streets, the real pilot will take place in the location where UBER pays drivers the most and where there are the greatest number of riders… New York City. Third, once robots are on the road they will quickly outperform their human counterparts. And fourth, once autonomous cars are seen as superior drivers, human drivers will first be seen as an expensive eccentricity and later as a genuine threat to society.  Why? Because The 35,000 or so annual deaths and several millions of accidents that are caused by human drivers will virtually disappear. That’s a massive impact on society. And on insurance companies.

Once robot drivers are common, the very act of turning off an autonomous driving system will be seen in the same light as ripping out your seatbelts or removing the airbags. Should you have an accident, the court is unlikely to be lenient. It won’t happen overnight. Drunk drivers may be “sentenced” to only using autonomous cars. Accidents made in anger or because the driver didn’t get enough sleep or because they were distracted by a text will have an increasingly difficult time defending themselves in court. Eventually , “recreational drivers” will find it terribly expensive to get the necessary insurance to continue driving their car.

Too soon to worry about losing your right to drive? Then consider, “The Self-driving Coalition for Safer Streets.” This is an association whose members include UBER, Lyft, Volvo, Google, and Ford. Their goal is to accelerate the introduction of autonomous vehicles and to make the public aware of the safety advantages of self-driving cars. Don’t worry, the government isn’t interested in taking away your right to drive. People are going to give up driving on their own. Of course, having your car insurance double every other year will certainly speed things up! And that’s my Niccolls worth for today. What do you think? Leave a comment and share your view!

Posted in cars, Employment, Robots, Uncategorized | Tagged , | Leave a comment

The New Job Market

Robot DataRobots and artificial intelligence are about to change… everything! Cars that drive themselves have arrived. Drones are scary killbots in the sky, but U.S. citizens rarely see them in person. A new generation of robots are arriving in the workplace, and will become teachers, clerks, analysts and even doctors. They may have a few glitches on day one, but within a year of arriving, robots will outperform their human counterparts.

Top US firms may wait and see, but corporations that are struggling for profit, startups seeking breakthrough costs, underfunded school districts, bankrupt municipalities, the military, poor areas without doctors, China’s emerging  touches and medical services for the elderly are likely to lead the way. They will demand quality services at a price that only a robot can provide. Transition to a robotic economy will take a decade, but we can expect the labor market to be “disrupted” for another 20 to 50 years, or more. How will you survive until the disruption is over?

The best predictions point to a loss of as much as half of all U.S. jobs, in as little as 10-20 years. This js a bigger labor disruption than anything before in U.S. history. Farming once employed 70% of U.S. workers, but now employs just 2%. That change took 150 years. Manufacturing was once 70% of the workforce but fell to 8% in just 50 years. In 1980 70% of Chinese workers were farmers. After 35 years, it’s just 29%. This “disruption”  represents the elimination of 300 million farmers jobs… just using “old” 20th-century mechanization. That’s equal to the entire workforce of the US AND Europe combined. How has China survived this shift in their labor market?

Essentially, China implemented the most impressive social engineering project that the world has ever known. China planned the transition for decades, invested trillions of dollars, built over 500 new cities, installed nearly 2,000 conventional and nuclear power plants, relocated (not always voluntary) hundreds of millions of workers from China’s  interior to coastal and river cities, and raised college enrollment from 1.5 million to 20 million.

Yet, even with this staggering amount of effort, the transition has not been without problems. Newly built cities have been left deserted due to changes in planning, there are huge inequities between city and rural pay, in 2015 there were nearly 3,000 strikes and riots, and new workers no longer want to work in factories creating labor shortages. Of course, the US and Europe labor markets were hit by their own disruption as offshoring eliminated millions of jobs. Robots will be even more disruptive. Especially when China itself (the world’s largest buyer of robots) installs millions of robots in its own factories.

In the West, we have been allowed to view some of the disruption in China, especially in factories where iPhones and similar electronics were assembled. China improved working conditions and raised pay. Strikes slowed down, but the increase in pay raised the cost of work in China, compared to competing Asian nations. In order to compete, China needs to improve worker productivity. Which led to China’s “robot initiative”.

To match the cost of countries with lower pay (Vietnam and Cambodia) or higher productivity (South Korea) China plans to install millions of robots. However, by installing these robots would not only costs, it would also more than double productive capacity. Therefore, China needs to either terminate more than half of their 100 million industrial workers, OR they need to encourage the West to outsource more jobs.

If China can cut labor costs in half (or lower), that will attract more work from the West. China also plans to move millions of displaced factory workers into knowledge work jobs into banking, insurance, media and service firms. With these new resources, China can execute on plans to take over these industries around the world. At the same time, the NEW generation of Artificial Intelligence systems will be rolled out to improve productivity in these sectors.

With new worker, and new technology China just may dominate global financial and service markets by the early 2020’s. Did you know that 4 of the top 5 banks in the world are Chinese? Or that China Life is the 3rd largest insurance company in the world? China is already well positioned to dominate the global markets. Recently China even created an alternative to the World Bank, the Asian Infrastructure Investment Bank. China will use this institution to lessen US and European political influence in developing countries, and support their own commercial expansion. This plan requires China to be on the leading edge of robotic automation. As China automate knowledge services, the U.S. and Europe will be pressured to do likewise.

Internationally and domestically, market pressures will accelerate the adoption of robotics and A.I. Similar pressures created the last wave of outsourcing. Decades of corporate outsourcing (2000 – today) created the infrastructure to quickly analyze a position, and then automate it or move it to a new (lower cost) worker. When it’s time to replace a job with a robot, all of the procedures and protocols are already in place. The top consulting firms (IBM, Accenture, Capgemini, TATA, etc.) already have contracts with the Fortune 500 firms. Networks and other technology that will control A.I.s and robots are already up and running. HR and legal long ago agreed on the processes and legalities to eliminate staff. The Robot Revolution will just take over the infrastructure, the “Outsourcing Engine”, speeding job losses until they outpace new job creation. Where does that leave you?

More Training: The more positive articles about the Robot Revolution say  that another degree might save you from losing your job. But this just doesn’t ring true. If your job as a financial analyst has been taken over by a robot, getting another degree to be promoted to a higher position in the same line won’t work because – 1) Can you afford to pay-off another school loan?, 2) It will take a couple of years to get a new job, but by then this job might be targeted for a robot takeover, 3) Having a lot of new PhD graduates doesn’t mean that there will be a lot of new PhD jobs.

More education is often a good thing, but not always. The numbers behind a new degree may work for a few jobs, but it requires case by case analysis. More education may not buy more security. Moving into a completely different field might be a more successful strategy for finding a job, but moving from a highly paid financial position to a mid-level healthcare job might provide the same level of compensation. Education may be the answer for some, but not the majority of displaced workers.

Be A Teacher: A growing number of articles tell us to, “Consider a job in training or education.” There are excellent opportunities in education, and we certainly need  more good teachers, but the Robot Revolution will create fewer new training positions than these writers expect. In the old model, trainers work with experts to document the how to perform work processes, and then use this documentation to train new workers. For robots, few trainers will be needed. Robots work directly with experts to learn work processes, and then robots will “teach” other robots. Robots are continuous learners, who correct and expand their database of knowledge. Robots then expand into adjacent jobs, with minimal help from trainers. Teach one robot to fill out mortgage applications, and all robots learn the process. Eventually, they learn how to fill out car loan applications, and replicate the information. Finally, they will learn how to approve the applications…. with better results than the humans they replaced.

Perhaps you want to be a trainer or teacher in some other field? Unfortunately, the Robot Revolution is targeting teaching. Robots can individually monitor students, tracking biometric information (eye focus, body language, blink rates) to know if they are paying attention to the materials, adjusting the pace of education for each student, customizing homework and projects to match individual abilities and issues. Humans cannot cost-effectively match the capabilities of a robot teacher. Don’t believe me? Then take it up with Elmo! That’s right, IBM’s WATSON learning system is teaming up with Sesame street to deliver education to young, poor students. In a few years… will the Cookie Monster teach financial modeling?

Climate Change: Two wrongs are not supposed to make a right… but, there is an exception. Climate change. Temperatures are rising around the world, water sources are dwindling, coastal cities may  drown, finned fish are disappearing, farm productivity is falling behind population growth, fossil fuels are anathema to millennials, and even optimistic environmentalists say we don’t have enough people to fix all of these problems. But when robots take hold and global unemployment rises by hundreds of millions, will this new army of workers be our solution?

Hurricane Sandy caused $70 billion in damage. Katrina cost $125 billion. Obviously, it’s worth paying a lot of money to avoid this magnitude of damage. New York City has a proposal to storm proof sections of the city, at a price of $20 billion. A plan for Jakarta is estimated at $40 billion. Then there is Venice, Mumbai, Naples, Bangkok,  Mexico City, and Miami. Think about all of the smaller towns along coastlines. Add to that damage to farms, dwindling water sources, highways and infrastructure, and so forth. One estimate puts the cost of economic damage for modest global warming (2.5% C) at 0.5% of global GDP, or around $500 billion annually.  Fixing the environment is a huge job. Not fixing the environment isn’t an option, unless we stop repairing cities after every storm or disaster.

Crowd Funding: In the past, if you had an idea for an important project (a business, a new product, a service) you would ask a bank or your friends and family for funding. Now, you can raise just about any amount of money, directly from the public. There are about 200 Crowd Funding sites, with more sites being built. Crowdfunding allows you to campaign for funding through social media tools. The biggest crowdfunded project to date is a game, Star Citizen, which has raised $110 million. In 2014 over $30 billion was raised through crowdfunding, and by as soon as 2018 it will surpass $90 billion. Today, Venture Capital (VC) is the money behind emerging technologies and emerging service companies, but crowdfunding is about to surpass VC funding.

Many of the college graduates who are about to be displaced by robots follow a very specific pattern. They graduate from an Ivy League business school, get a corporate job, gain experience, and then try to launch their own business. If they could, most would jump to creating their startup, either earlier in their career or while they are still in college. This is beginning to  happen with crowdfunding. Music, games, books, new technology, even projects that can save the world… are all getting funded through crowdfunding. The combination of a global environmental crisis, and the ability for new talent to circumvent traditional employment paths, is the best alternative to waiting for a robot to take your corporate job.

Conclusion: The coming Robot Revolution will revolutionize the workplace. The lucky owners of key corporations will see massive new profits as inexpensive robots replace high-cost human labor. This is a frightening scenario, but it is one that America has lived through before. Agricultural jobs went away.  Manufacturing jobs went away. Recently, millions of basic corporate jobs (clerks, phone operators, secretaries, typist pools) went away… and will never return.

In another year or two smart robots will move out of the factory and into the corporation, wiping out jobs from chauffer to financial analyst, and then learn how to do the same for lawyers, doctors, and teachers. The infrastructure for replacing large numbers of workers was put in place during recent rounds of outsourcing. The Robot Revolution will re-use the “outsourcing Engine”, vastly accelerating the replacement process, reducing jobs faster than they can be created.

With high paying jobs going away forever, we face the possibility of double-digit unemployment for decades to come. The solution to the labor market may collapse couldn’t be more ironic. The millions who lose their jobs in finance and in knowledge work may find new careers fighting environmental collapse or using crowdfunding to build new technologies and new products that the old sources of funding (banking, venture capitalists, etc.) would be too conservative to back. Will global warming and crowdfunding make up for the gap created by the Robot Revolution? It’s too soon to say if it can offset all of the job losses, but it will certainly soften the impact.

The labor market today is  significantly different than it was just a decade ago. Now, we MUST use social media as a part of our job search process. Music stars, software developers, actors, writers and many others live on social media and can’t work without it. The most intelligent and talented young workers will bypass traditional corporate employment and become part of the creative economy… creating new products and services, funding them directly through crowdfunding. Signs of the environmental crisis are mounting, and project to fix the world will be crowdfunded. The Robot Revolution and Global Warming, two of the greatest disruptions to human civilization EVER, may be the only cure for each other. That’s my Niccolls worth for today, and I’m sticking with it!

Do you agree, or do you think there are better options for the coming disruptions to employment? Comment on this blog and let everyone know what you think!

Posted in Uncategorized | Leave a comment

Flatline… Subscriptions Will Be The Death Of Tech Jobs

FlatlineWhen does a buzzword become a technology? It’s hard exactly, but “Subscription” is a great example. It started as a simple idea. Software sales groups spend a lot of time and money chasing after customers. They want customers to buy the latest version of software, but the cost and effort to buy and install software are often too much for too little benefit. Even worse, the customers who invest the least, end up with the most obsolete hardware and software and require the most support. Maybe they need to squeeze another year out of obsolete equipment. Either way, these customers consume the most resources and pay developers the fewest fees. A subscription/cloud solution could solve this problem! Software would be up to date, and the sales revenue from updates would be more predictable! That’s not a bad goal, but it could create changes that will disrupt the Tech sector. Let’s dive in and go through the details!

The concept of a subscription is that consumers pay a fee every year (or monthly) for every user of a software product (or suite). Customers with an ebb and flow of projects only need to pay for the licenses needed to work today. In the old days, a big project at the beginning of the year might require 100 licenses; when the project ended, and only 10 licenses are needed for the rest of the year, you can’t get your money back. You might be able to rent licenses from a subcontractor, but that is usually expensive and messy. A subscription is just turned off when you’re done. That’s a big advantage, that can lead to big cost savings.

Of course, once you use a subscription, if you ever fail to pay the fee, the product stops working. Just like failing to pay the phone bill means that it is disconnected. That’s quite different than the old model where if you fail to pay for a new version of software or fail to pay for a support contract, you run an outdated version of the software or you cannot call for support.

Subscription models also automatically renew. As a customer, you may not see this as a wonderful feature, but your software provider loves this feature. It makes their revenue predictable. Before subscriptions, customers chose if they wanted to upgrade. Customers tended to skip some upgrades and install others. A new release might have great features, or it might just contain incremental fixes. Even when you want to upgrade, an enterprise rollout of a new version of software involves much more that licensing fees. You may need to upgrade your O/S, hardware and networks, other software, test drivers, change printers and other equipment. That involves a lot of IT hours and a lot of potential conflicts with other corporate projects. When customers fail to embrace a new version of your software,  the loss of revenue can hurt your bottom line.

The bigger the corporation, the greater the impact of a weak release. Lost revenue is just the beginning. Public firms MUST announce their predictions for an upcoming release, long before it is ready. To must report when the release will happen, how many customers will adopt it, expected revenues and anticipated problems. When expectations are not met, Wall Street analysts are not forgiving. Ger ready to be hammered a second time! The weak release cost your revenue, and now the analysts downgrade the value of your stock or recommend that your shareholders sell. Even if it is a very small miss, or even if you met your prediction, analysts may be unhappy that you did not exceed it. An unsuccessful release can force out a CEO or crush a publically traded firm. Regular releases that need to be purchased create an “event”, that analysts want to comment on. Subscription models spread out revenues and make them more predictable. That’s very alluring to the C-Suite, which explains the growing popularity of the model.

Another incentive is… cost! Older computers (and printers, servers, etc.) cost much more to support. As drivers slowly go out of date, old software is no longer supported or doesn’t run reliably. Automatic upgrades, a standard in subscription software, constantly test your configuration, and “ping” you as individual pieces of older equipment become obsolete. Rather than big messy upgrades, subscriptions create small incremental hardware upgrades. “Cloud” component are standard with many subscriptions, moving large parts of the storage and processing offsite, allowing the use of simpler/cheaper workstations. That further reduces the need for expensive upgrade projects. So far, so good? Here’s the downside.

The first item is the cost. What is the right price for a subscription? Under the old model an expensive software product, such as Autodesk’s Autocad, costs thousands of dollars for a minimal installation. A full suite of tools easily costs $10,000 or more per user, not including PCs, printers, and networks. How do you count licenses? Are they concurrent (i.e. maximum number of users at any one time), or is each license owned by a specific user (total number of users employed this month)? That’s a BIG difference if the product is used infrequently. If you can change your license count, these “flexible licenses” are usually expensive and more difficult to

If your license count changes frequently, “flexible licenses” are often expensive, difficult to count, and harder to use (can you only change count once per month?). Will your annual license be based on a “natural” purchase cycle of once every 5 years ($10,000 / 5 = $2,000 annually), every $3 years ($10,000 / 3 = $3,333), or something else? Whatever calculations are used, some new subscription users, especially those who upgrade infrequently, are going to pay more under the new model.

While a particular business might be greatly impacted by new pricing model, the operational model creates the real impact. Because subscriptions and Cloud services often go hand in hand, they will trigger massive consolidation. Imagine you run a business that relies on computer software. You switch to a subscription plan that moves your software and data files to the Cloud. You now have little (or no) need for servers, and for desktop storage. Your firm’s IT infrastructure shrinks, dramatically reducing the need for servers, customized PC’s, software installation and support for remote computers. Your IT department moves to the Cloud, but the jobs don’t.

For you, supporting technology is a cost center. For your vendor, providing software is how they generate profit. Automatic updates dramatically reduce the support cost for vendors. Taking the hardware platforms of a thousand corporations and consolidating it into just one big environment is massively more efficient. BUT… vendors are not building servers and hiring new techs. Instead, they too are moving their services to Cloud providers, such as Amazon Web Services (AWS).

Software developers no longer want to create their own storage centers, because they cannot create storage servers centers as cost effectively as AWS and its rivals. In 2014, AWS had over 1,000,000 customers, and their annual revenue grew by 40%. Microsoft, Iron Mountain, Rackspace and many other providers are seeing similar growth. New technology startups often begin building their model with cloud storage and processing baked into their model.

Meanwhile, back at your office, your reduced IT staff is struggling to provide 24 x 7 support. Time to move the rest of your servers to the Cloud? Most corporations will save quite a bit of money, get higher security and more reliable backups. New software rollouts will be faster and take less planning. When everything was on-site, you would wait weeks or months for an opening in IT’s maintenance schedule. Cloud providers have reduced this to the flip of a virtual switch. Let’s break this down:

  • Server Scale: A cloud-based service allows you to grow or shrink your operations, without any previous notice. That means fewer barriers to running the latest versions of software and drivers. The more up to date your environment, the lower the number of problem calls per user, and the lower the cost of operations.
  • Budgets: Installing new software in the corporation means buying new software licenses, new equipment, and budgeting time for the techs to do the work and fix the inevitable follow-on problems. For a big upgrade, you may need a big budget increase over last year. These periodic surges in the budget are difficult for IT managers to explain to financial managers. That leads to delayed upgrades, which leads to higher complaints. Subscription based services may not lower the budget, but they make budgeting more predictable.
  • Support Cost: Data centers at AWS and its competitors are far larger than most corporations. They buy more servers and storage and get lower prices. Cloud providers can sell each GB of storage or CPU Cycle for less than you can pay. And you get built-in services such as…
  • Anti-Virus: Virus attacks, malware, spyware and targeted attacks on corporate data centers have shown how vulnerable most centers are. The cost of security rises every year, and so too do the number of large-scale “hacks”. Cloud storage bakes in anti-virus/malware software plus other security services into the data center design, making another layer of corporate techs unnecessary.  Few corporations can compete with AWS’ in-house virus lab. Corporate reputations have been permanently damaged by cyber-attacks. IT heads are increasingly turning to dedicated storage providers for an answer.
  • Automation: In order to be the most efficient providers of storage and CPU’s, services like AWS make use of far more automation than corporate IT groups. Gone are the endless meetings with IT to authorize and schedule work. Gone too are the IT techs and managers. Instead of submitting requests, you move a slider on a control panel and… you have more space. Installations and uninstallations are automated. AWS, for example, also provides automated software testing facilities, eliminating the need for (human) techs to perform this function. This may not spell the end of software testing as a career, but it dramatically reduces employment.
  • Efficiency: CThe scale of Cloud-based services allows them to manage and update your environment more quickly and at a lower cost. Even if Cloud services were no more efficient than corporate IT department, merely consolidating a thousand IT groups would yield massive redundancies. Let’s assume a 50% improvement, which we’ll call “A”. However, AWS storage is much more efficient than a typical corporation. By buying an order of magnitude more equipment than the typical customer, hardware prices are much lower. Add automation that is years ahead of their customers, and you have at least another 50% in efficiencies that we will call “B”. Finally, future growth from customers joining the Cloud will drive the next generation of efficiency, for another 50% that we call “C”. “A” x “B” x “C” is 12.5%. Optimistically, less than 20% of IT support will survive the next 5 to 10 years.

The Bureau of Labor Statistics (BLS) lists 4 million support techs and software developers in the U.S., plus half a million IT managers. Add to that another 2 million sales and sales support positions in the technology industry. What happens to the sales staff under a subscription model?

Sales staff either finds new customers or helps customers move from their first interest in a product to negotiating a price, training staff and installing the product. Sales groups are usually divided into “hunters” to find new customers, and “farmers” to grow existing accounts. Farmers focus on renewing licenses on-time and growing the number of licenses for an existing account. Subscriptions automatically renew, eliminating that part of farming. Adding, deleting and reassigning licenses is better handled by Artificial Intelligence (A.I.) than human sales staff. An A.I. just needs to monitor accounts and message customers when they need adjustments in their license count. Users can make other changes themselves.

That just leaves the “Hunters”. Small software firms still sell their products directly, while larger firms outsourced most of their hunters in the 1990’s. They use “channel distributors” or “Value Added Resellers” (VAR). Developers create products, pay for ads, provide technical support and training (to VARs and customers), pay for conferences and events, and send sales leads to distributors.

Distributors are independent firms that sell products from one or more software developers, plus add-on products, training, installation services, and support. Simple products (ex.: MS Office), are sold on-line or in big box stores. Expensive products that require professional installation and training (ex.: a full suite of CAD products from AutoDesk, for $10,000 or more per license) usually involve a VAR. Developers surrender a large part of their revenue stream to distributors because distributors usually cost less (30% less) than internal sales groups. With subscription based sales, sales groups and VARs will need to cut over 50% of staff.

With a Cloud/subscription model, the few remaining sales staff will each be paid less. Today, in a market like New York City, top sales people get compensation of $250,000… $500,000… even $1,000,000 or more. A very, very few of these will remain but most are destined to become support, and might be moved into customer service. The subscription product is so much simpler, commissions will be few and far between. I have seen communications from developers to distributors explaining how the new subscription world will work. They all talk about change, some mention staff reductions, none discusses the need for more sales staff.

The subscription model is picking up steam and will probably be the standard in less than 5 years. Six million tech and sales jobs are at risk, and most will be lost in 5 years with the rest gone in no more than 10 years. Customers never asked for this model, the benefits to the customer (simplicity, consistency, better support, maybe cost savings) make it very compelling. Developers drove the model, and their benefits (lower support costs, higher revenue, elimination of distributors, reduction of sales staff, stable revenue) make the model inescapable.

A few firms or customers will refuse to go along, but they can only delay, not derail subscriptions. If you’re in technical support or sales, the future is a bit grim. On the other hand, by reading this you have become one of the privileged few who knows exactly what’s coming. And still has time to prepare for it. At least, that’s my Niccolls worth for today! Follow the next blog where we discuss alternatives to the coming Robotic revolution… such as the creative economy!

What do you think? Do you agree that the subscription model is about to disrupt sales and support positions? What are the alternatives? Write in and tell us what you think!

Posted in Best Practices, Common Sense Contracting, Delivering Services, Unique Ideas | Tagged , , , , | Leave a comment

The Robot Revolution On Speed: Too Late To Turn Back!


Tongues have been wagging about the rise of the robots. Robots taking over manufacturing, robots acting as home companions and robots taking our jobs. A lot of digital ink has been spilled on the subject.  You know what? Just about every one of these fear mongering articles… is right! Many of the most common types of robots won’t look anything like people. Don’t expect tall silvery humanoids with antennae sticking out of their heads. Many robots will be hard to recognize or they might just be one more app running on a computer, or even a cell phone.

What makes robots and artificial intelligences game changers is not how they look, but what they do. And what they do… or are about to do… is your job!  When robots aren’t actually performing your job, they will spend their leisure hours learning how to do your job better. Or, maybe they will learn how to do your boss’s job. Before the end of 2016 you’re going to see some of the first skirmishes in the robot revolution. By 2017 you’ll see human employees lose a few critical battles. Read along and learn what you need to know about the coming Robot Revolution!

Machines replacing people? This isn’t exactly new.  Machines, starting with simple machines like the wheel, have made people more productive. For most of human history, humanity was so poor that we would immediately consume any additional productivity. Especially when that productivity was in the form of food or fuel. This additional productivity led to more wealth and more security. This Virtuous Cycle has been working since the earliest days of civilization.

Virtuous Cycle: The age of Sail started thousands of years ago and ended just a few centuries ago. Sail driven ships moved more goods, for a lower cost.  It also showed us that there were far more goods in the world than our own village, and some foreign goods (high-quality wool, silk cloth, spices, delicate jewelry, superior metals) were vastly superior. We had choices in what we could buy. This drove wealth, then luxury, and finally leisure time. Better machines improved productivity, which improves our standard of living. There were gaps and exceptions, but the story of mankind has been one of growing wealth.

Political collapse, war and natural disaster could disrupt this Virtuous Cycle, but eventually it would move forward and increase our wealth. In the 21st century we live with constant technological change and constant material improvement. There may be a good argument that wages have stalled for the last 20 years, but even with no more dollars in our pockets, our lifespan increases every year, diseases are cured, nutrition around the world gets better, and even our entertainment choices improve. But, what if something broke this cycle? Something like… robots?

Consider how this “Virtuous Cycle” works. It takes a very long time to implement new technology, and even longer to fully optimize and integrate into society. Social and technological limitations (cost of travel, cost of fuel, short live spans) made it difficult for the technology to spread very far from where it was discovered. It took centuries for the locals to figure out all of the details of a new technology, and even after a thousand years, it might not spread very far. Over this long period of time, wars and disasters could disrupt or even wipe out the technology. But all of these problems provided people and society

But all of these problems provided a benefit. People and society had time to absorb the technology. 3,000 years ago iron was the “secret weapon” the Hittite people used to conquer the middle east. In less than a thousand years, the iron age had spread across most of the world and even small villages had blacksmiths.

American Example: If an iron age example a bit too “dawn of time” for you, let’s move it up to… the early United States. America started out as a largely agricultural country, but also had fishing, mining,  a textile industry, fur trapping, shipbuilding and other industries. By 1850, agriculture was America’s the primary source of employment. The industrial revolution arrived and replaced animal and human labor with machines. EXCEPT the American South. The South’s choice of slavery over technology sparked a war between the North and South. Over 150 years, farm workers declined from 70% of the workforce to just 2%.

Need another example? Here’s one! The factories that built the machines that replaced the farmers, needed workers. Early factories were often difficult places to work, but they were better than farms. They paid more, they brought people together, increased education, and (eventually) improved life expectancy. Were the farmers happy about the transition? Absolutely not. There were all political and physical fights over land and jobs, culminating in the Civil War. Nonetheless, the industrial age turned farmers into factory workers, and by 1960 most Americans worked in factories. Yet just 50 years later, manufacturing is just 8% of the job market, and shrinking.

There is, however, an important difference between the revolution in farming and the revolution in farming and the revolution in manufacturing. Time! You may not be surprised that the Iron Age took 1,000 years to take hold. America’s farming revolution took just 150 years. Manufacturing took just 50. Every new technology revolution builds on the last revolution and takes less time to be adopted across a larger area. Still not enough? Let’s look at one more example.

Chinese Comparison: In 1980, 70% of China’s workforce was agricultural… just like the U.S. in 1850. China needed to move agricultural workers into manufacturing jobs. This became the #1 priority of their long-term economic plan. By 2012, agricultural workers were just 35% of the workforce. In percentages, that’s at least twice as fast as the US conversion. Pretty good. But in total population, this is absolutely stunning!

America eliminated most of the agricultural positions when our nation was young, with a small population. Agricultural employment peaked in the US in the 1920’s, at just under 11 farmers; now there are just 2-3 million farmers. This transformation occurred over 7-8 generations, so it impacted the lives of more than 11 million farmers. However, China peaked at 700-800 million farmers towards the end of the 20th century. China eliminated 350-400 million jobs in just 35 years, or 10 million annually. Rather than eliminating jobs twice as fast as America, it might be more accurate to say that China eliminated jobs 100 to 200 times faster. How long would it take China to eliminate the 40 to 60 million corporate “knowledge worker” jobs in America?

New Cycle: The Data Economy arrived in the last quarter of the 21st Century. Instead of wealth arising from the land or a factory, it came from information. Farms were largely self-supporting through human history. In the 20th century, farms grew large enough to need  significant capital to buy fertilizers, pesticides, seeds and equipment. Manufacturing firms were still larger, and needed banks for funding, banking services, and services to exchange payments with workers, vendors and customers. Financial firms (and financial departments in corporations) needed Knowledge Workers.

Knowledge workers turn collections of information into knowledge (insights). These insights guide investments: which markets are growing, where are profits the highest, etc. Knowledge workers initially used data, a calculator and paper & pen. Soon, computers replaced calculators, and data feeds replaced paper. Demand continued to rise, and publishing firms sold on-line data: McGraw Hill Financial, Standard and Poors, Moody’s, Gartner and others. On-line services began replacing jobs. Computer and consulting firms (IBM, Oracle, Accenture,  McKinsey, Bain, and scores of others) sold services to automate (or outsource) functions, reducing onshore knowledge worker jobs.

Outsourcing created the Virtuous Cycle 2.0, and a quandary. Jobs with better salaries were being created but in lower pay geographies. A $60,000 position in the US, had a total cost of $100,000-$120,000 (adding bonus, benefits, space, IT support, etc.). In India, that position is paid just $20,000 (the employee is paid just $6,000). Even if it takes 2-3 workers to replace one onshore, it still saves money. That $6,000 offshore salary isn’t much in the US, but it an be a great salary offshore. Virtuous Cycle 2.0 still works, if you look at global results and ignore domestic losses. Did VC 2.0 continue to create wealth? This is still being hotly debated.

The Vicious Cycle: The Data revolution differed from the two prior revolutions in many ways, but the key difference was… speed! It’s very simple. Employment is determined by new jobs created and old jobs lost. Whether the economy is hot or cold, jobs are always created and lost.

In the Data economy, computer intensive work was targeted for offshoring.  In 1970, computer jobs were a rarity. By 2000, you couldn’t get hired in a corporation without computer skills. One by one, isolated parts of the corporation that were not “outsourcing ready”, disappeared. Decades of effort, effort that was not always specifically aimed at outsourcing, slowly prepared millions of jobs for outsourcing and automation. “Flexible” robots and A.I.s will now trigger the elimination of these jobs.

The Domino Theory: Have you ever watched a domino display fall down? A good display can take days to set up, and seconds to fall. It just takes one little push on that first domino, and the rest all fall. We’ve been setting up “dominos” for the robot revolution for 30 years. Take a good look at this delicate stack of dominos:

  • Infrastructure: Think of mobile robots (self-driving cars, flying drones) as blue collar workers, and A.I.s running on computers as white collar workers. Corporations own BILLIONS of PC’s. Each computer could run an A.I. that writes stories (reporter, financial analyst, lawyer), analyzes data (accountant, financial analyst, lawyer) or performs other tasks. Tasks too complex for any single PC would be shared across a network, in your office or around the world. Any work performed on a PC is ready for an A.I. to take it on.
  • Capabilities: A.I. systems are disembodied intelligences that read electronic data and documents. However, not all information is in computer format. To capture information from the “real world”, you need cheap and reliable robot “senses”. A generation ago, these didn’t exist. Now they are everywhere, including your cell phone. Robots can read and speak (Siri and Cortina), hear (voice recognition) and see (phone cameras, object recognition software). Touch screens let you physically interact with technology. Smell and taste? Not yet, but specialty sensors can identify: smoke, explosives, drugs, etc. Arms and legs are difficult to mimic, but automated kiosks (such as ATM’s) can take your cash and checks and hand you money without lifting a robotic finger.
  • Capacity: Corporate computers are already used by employees, but only for 40 hours a week. “Robot workers” could exploit the remaining 128 hours. As computers wear out or become obsolete, less expensive yet more powerful replacements will lower the cost of robot workers every year. Consider, Deep Blue. In 1985, IBM wanted to build a computer capable of defeating a chess grand master. IBM built the world most powerful supercomputer (Deep Blue), and won! Today, a chess app running on a cell phone can defeat grandmasters. Once a robot takes over a job, they ALWAYS perform it better than a human. A job lost to a robot, is lost forever.
  • Self Learning: Robots differ from earlier technology. First, they are flexible, allowing them to work in less structured environments. Older tech would stall when faced with unexpected issues; robots can apply general rules to find a specific solution. That allows robots to work in more environments. Second, robots learn on their own. Humans still write the general software, but robots then work with experts to learn how to do work. The expert gives the robot an assignment. The robot then analyzes documents (spreadsheets, images, forms,etc), to produce its assignment. Just like a student, the robot’s work is graded and the robot eventually “graduates” and can then independently perform work. This process is applied to task after task, eliminating jobs. After “worker” tasks are all replaced, robots can apply the same process to management positions.
  • Knowledge Transfer: When outsourcing hit the US, the speed of moving jobs offshore was limited by the speed of training. Training an offshore financial analyst took years. Then, after a few years, the local pool of candidates was smaller or completely used up. More workers could be found by hiring less skilled candidates, and providing more training. This took longer, and cost more, but outsourcing could continue. Once a robot is fully trained, you just download the software to another robot. Or a million. The cost of outsourcing rises every year as the best candidates are consumed. The cost of robots falls, as technology becomes cheaper every year. And each new robot is always more capable than the one before it.
  • Scale: In the last revolution, jobs were lost to automation or were moved offshore. In the robot revolution, you will still compete with outsourcers to keep your job. But you will also compete with the robots your company buys, on-line robots from data providers, consulting firms bundling robots and A.I.s with their services, and a new generation of robot vendors. Offshore firms will also build or buy their own robots, and offer hybrid human/robot services. The forces competing for your job will be far more numerous and more capable than ever before.

Robots Everywhere: We’re faced with a pretty simple question, “How many jobs will robots take over and how fast?” The answer is equally simple, “More jobs than ever before, and faster than anything you’ve ever seen!” There are more sources for robots, more corporations and universities working on robots and… thanks to the infrastructure already in place… vastly more jobs for robots to immediately take over.

Robots will create some new jobs, but less than people expect as robots eventually take over their own training, management and possibly sales. In the Virtuous Cycle 3.0, new wealth is still being developed, but fewer are domestic jobs with the same pay. Corporations will have higher profits, retirees will benefit from affordable personal services, and those with wealth will see a new age of luxury.

However, the 30% to 50% of the workforce that will be eliminated, especially the younger workers,  will have a more difficult life. Especially in the next 10 years, when we lose 10 – 20 million jobs, or more. In as little as 20 or 30 years, this disruption may end and employment may rise again.

It will be years before we have any idea of what VC 4.0 will look like. Most likely, it will rely heavily on the Creative Economy (more in a soon to be released blog). For now, if you have an entry or mid-level corporate job, spend your time writing or reading reports, work on a computer, drive a car, train, ship or plane, assume that a robot can do your job. If not today, then in a very few years.  And that’s my Niccolls worth for today.

Do you agree or disagree? Comment on this blog and tell us what you think!

Posted in Decision Making, Delivering Services, Employment, Improvement, Robots | Tagged , , , | Leave a comment

Uber Orders 100,000 Robot Cars!


AP Photo/Jonny Mattsson

Did they or didn’t they? Everyone wants to know if the rumor is true. Did UBER order 100,000 Mercedes Benz type S cars? If they did, UBER could provide a “driverless” taxi  service AND  set a new low price for car and transportation services. Some report that UBER is on the verge of buying the cars while others report that the deal is already consummated. The truth is… it doesn’t really matter!

Whether UBER placed an order or not, the rumors are an indicator that UBER is far enough along in negotiations with Mercedes-Benz (and other manufacturers?) to start leaving an evidence trail that they need to buy cars soon. I said it before and I’m saying it again… the robot revolution is on its way, and UBER is the tip of the spear. The future is as early as tomorrow morning, and tomorrow morning is when YOU WILL GO TO WORK WITH AN UBER DRIVERLESS TAXI. Today, we look at the UBER phenomena and the inevitability of driverless cars.

First, and perhaps most importantly, I told you so. Now that that’s out of the way, here’s what you can expect. The first step, the pilot of driverless cars in a taxi service, will start in New York City. Second, by the end of that year, 15,000 to 20,000 taxi driver jobs will be eliminated in New York City. Third, within 5 years, 1 million driver jobs in the Metro New York area (not just taxis) are eliminated, and a total of 5 million driver and transportation positions are eliminated or targeted for elimination across the US. Fourth, after 5 years of “disruption”, we pick up speed as consumers embrace driverless cars. The auto insurance industry crumbles, healthcare and legal industries lose billions of dollars of revenue from car accidents, garages and gas stations close due to a lack of fender benders, and the car industry has strong growth for a few years before changing direction and losing 90% of its workers. This is what the robot revolution will bring about in transportation.

If you haven’t read my earlier articles, here’s some key background. UBER has never made a profit. In 2015, UBER lost $250 million. A primary cost, fuel, recently dropped dramatically. That makes driver’s compensation even more prominent. Add to that a run of stories about UBER drivers killing and raping passengers. If UBER goes driverless in just Manhattan, a mere 23 sq. miles, UBER goes from a $250 million loss to a profit of at least a billion dollars. That’s even if LEAST a billion in profit in year one, even if they fully loaded the cost of new robot cars into the first year. The numbers are really stunning, and it is these numbers that would drive UBER and its competitors. Here’s one more number. If UBER can ride this wave and stay in business, their fleet of 100,000 cars will grow to 10,000,000 in 10 years.

That’s a lot of big numbers and big projections. You must be thinking, “Surely it’s not possible for me to predict how this part of the robot revolution is going to play out over the next decade.” Or is it? Here’s your playbook for the coming revolution!

Ground Zero: Autonomous cars today drive as well or better than human drivers. However, while it is legal for a driver to turn on an autonomous driving  feature, it is not clear if an autonomous car is allowed on the road without a driver. The more counties and states you drive through, the more laws and regulations you may break. However, New York City is UBER’s biggest market, with both the highest revenue and the greatest driver costs.

In just a few years, UBER created a fleet of 15,000 cars in NYC, more than all of the Yellow Taxis (which had a near monopoly since the 1930’s). Manhattan, just 23 square miles of land, is responsible for 90% of UBER’s NYC revenue. UBER could not hope for a better location for a driverless taxi pilot than Manhattan.  UBER’s aggressive “just try to stop me” operating model in NYC is how they out-grew the Yellow Taxi industry, and it is how they will beat the City government once again if the City blocks autonomous cars.

Lost Jobs: It took UBER just a few years to build its fleet of 15,000 taxis in NYC, and they could replace it in just one year. The fact that they haven’t purchased the garages and gas stations they would need for their cars is a sign that they are not year ready for the rumored 100,00 cars, but they could quickly build the infrastructure they need for a pilot. By offering a Mercedes Benz type S (or any similar car), New Yorkers have a choice between riding in an UBER luxury car or a low to mid-end Yellow Taxi. If the UBER ride is cheaper, Yellow Taxis could be gone in just 2-3 years.

Lawsuits, regulations, and government foot-dragging give Yellow Taxi’s another year or two, but that’s it. After all, can City government be against autonomous cars that virtually never have an accident or kill a citizen? Taxis that electronically cooperate could also reduce traffic jams. An autonomous car is really the auto industry’s greatest safety feature, and will save more lives than seat belts, airbags, and anti-lock brakes put together. As driverless taxis take over NYC, commercial trucks, buses, trains, and airplanes will also adopt full autonomy.

The US: Driverless cars will succeed in New York, and they will spread throughout the US. Some states or counties may form pockets of resistance, and former drivers will protest and vandalize robot cars (that’s the pattern for employment disruption). But it won’t change the outcome. Consumers will adopt “autonomy” in the next 3-5 years. They will let their car drive them to work. This will drive changes in car design: removal of the steering wheel, drivers seat, perhaps having all seats face each other, add a work table, WiFI, and maybe a bed for the owner with a long commute to work?

Now, we enter UBER’s next stage, making American’s give up car ownership. Why have a second (or third?) car that spends most of the time in your garage? Instead of giving your teen a car, give them an UBER account. Shouldn’t you get your parents to stop driving at night with their limited vision? Will super-moms welcome some help picking up and dropping off the kids at school and other activities? Dump the extra cars, the cost of gas, lease and insurance costs, and get everyone pre-paid UBER accounts! UBER’s fleet rises to 10 million cars or more. Then UBER can turn its full attention to taking over truck transport, bus services, messenger delivery, etc.

Disruption: Just as moving from vinyl to CD’s made us all buy many of the same albums in a new format, as the “office on wheels” becomes the car of the 21st century, old cars with a driver’s seat will be ditched and new cars purchased. A couple of years later, when the average American family has 1 car or less, the auto industry crashes and half of all transportation (5 million) and auto manufacturing jobs (also about 5 million) go away.

By year 10 this rises to about 18 million lost jobs. All of those driverless cars start to eliminate car accidents and deaths. The auto insurance industry collapses. A million lawsuits a year don’t happen, and 4 million accident victims don’t need medical care. Without a steady stream of fender benders, thousands of garages close. Without many repairs and with highly reliable cars, a third to a half of car dealerships are wiped out. Patrol cars around the US become autonomous, reducing the nation’s fleet of police and patrol vehicles. Round that up to about 20 million lost jobs, in about 10 years.

End Game: If you continue to drive your own car, the cost of insurance soars. If you have an “accident”, it will have only occurred because you made a conscious decision to disable a safety feature of your car (autonomous driving). You have just surrendered your defense against damages, especially if anyone has been injured or dies. If it is even possible to get insurance to drive your own car, the price will be so high that only a handful of Americans will able to afford it!

In 10 years we’ll all gather around the fire and say, “That’s how it happened.” You think this isn’t possible, or that something will come along to change it? Look at the history of America. The 1800s was the century of the horse and the wooden ship. The 1900s was the age of steam, with an iron horse (trains) and iron ships. The 20th century was the age of oil, which gave us the car and airplane.

Today we are in the age of data and computers. Cars, trains, ships and planes will continue on, we will simply add artificial intelligence to drive them. Cars are already highly automated, and automatic braking is just the newest “must have” feature. More than anything else, “autonomy” just ties together all of the features that are already on your car.

Driverless cars are going to be a chaotic disruptor simply because of the speed and thoroughness of the transition. In previous disruptions, new jobs (often better jobs) replaced jobs that were lost. This transition will destroy jobs faster than they can be created. We’re going to lose 10-20 million jobs in the next 10+ years, but replacement jobs may not arrive until after he “disruption” ends… 15 to 30 years later.

One or more generations of relatively unskilled labor will have very few choices, but higher paid workers and the wealthy retired will see many benefits. This will be like going through the changes of the last 20-30 years, but at twice the speed and wearing a blindfold. A big wave of changes will hit our labor market in just a little while, If you want to stay ahead of that wave, keep reading this blog! At least, that’s my Niccolls worth for today!

Posted in cars, Decision Making, Robots, Uncategorized, Unique Ideas | Tagged , , , , | Leave a comment