{"id":40770,"date":"2018-03-20T04:45:54","date_gmt":"2018-03-20T09:45:54","guid":{"rendered":"https:\/\/michaelhyatt.com\/?p=40770"},"modified":"2018-03-20T04:45:54","modified_gmt":"2018-03-20T09:45:54","slug":"difficulties-of-automation","status":"publish","type":"post","link":"https:\/\/fullfocus.co\/difficulties-of-automation\/","title":{"rendered":"Automation for the People"},"content":{"rendered":"

If you want to understand how hard it can be to automate, consider the many attempts to replace cashiers with self-checkout systems.<\/p>\n

To wit, CVS pharmacies were once lousy with self-checkout systems, which I personally tried to use, many times, to get out the door faster. Almost every time, some loud error sent me to the back of the queue instead. After a while, I gave up on these time-wasting devices. So did many other customers. In 2015, the company threw in the towel and removed them<\/a> from most stores.<\/p>\n

The problem with self-checkout systems isn\u2019t simply that customers don\u2019t like them and would prefer to deal with flesh-and-blood people. Rather, the rub is that automation can be really hard to get right.<\/p>\n

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The personal touch<\/h3>\n

Tallying up products and their prices and charging for those products are surprisingly complex tasks. Machines can assist people greatly, but when things go wrong, people tend to find workarounds. (\u201cManager to aisle three!\u201d) Machines simply spit out error messages for days and make people want to find another use for those cheap umbrellas.<\/p>\n

Or consider the humble book slipcase. It\u2019s not a complicated thing: simply cardboard arranged like a close-fitting box around most of the book. It\u2019s a protective sleeve that can make books more durable and presentable. You might think it would be a no-brainer to package a huge number of books this way.<\/p>\n

Yet slipcases continue to be rare\u2014typically reserved only for special editions. Why? Slipcases are expensive because they usually have to be assembled by hand, whereas most of the processes that go into book production\u2014from printing to binding to trimming\u2014have been automated.<\/p>\n

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The reason why has to do with one major limitation of machine production. Machines are great for heavy lifting such as folding steel plates or gluing whole phonebooks together. They are not so great at manipulating fragile things. They\u2019re lousy at stuffing decent burritos, for instance, or dealing with flimsy cardboard that has to be folded, glued or taped into place, fitted around a new book, and packed away.<\/p>\n

Driving a truck<\/h3>\n

If automation is so hard, why is there a whole genre<\/a> of popular articles out there predicting that the machines are about ready to take over many of our jobs and render millions of workers redundant? Many futurists predict practically peopleless factories in the next decade or so, the takeover of fast food and other service jobs by robots, and fleets of unmanned taxis and self-driving long-haul trucks. How likely is that to come to pass?<\/p>\n

Dan Hanson is an expert in automation with 20+ years of experience in the field. On the economics site Marginal Revolution last month, he poured cold water<\/a> all over the idea that a fleet of long-haul automated trucks is just around the bend.<\/p>\n

Hanson began his case for sanity in the automation debate by asking a great question: \u201cI wonder how many of the people making predictions about the future of truck drivers have ever ridden with one to see what they do?\u201d Then he explained the significance of that question. \u201cLots of jobs,\u201d he wrote, \u201clook simple or rote from a think tank or government office, but turn out to be quite complex when you dive into the details.\u201d<\/p>\n

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Truckers, for example, \u201cdon\u2019t just drive trucks.\u201d They also secure loads, verify manifests, act as \u201cagents\u201d for their employer or contractor by dealing with the authorities, serve as \u201cearly warning systems\u201d for mechanical problems, put up literal warnings in the form of road flares and reflective signs for other vehicles when the truck breaks down, and double as \u201csecurity for the load\u201d by sleeping in the cab on long hauls.<\/p>\n

Most truckers, Hanson explained, \u201chave real local knowledge that is not easily transferable. They know the quirks in the routes, they have relationships with customers, they learn how best to navigate certain areas\u201d — and avoid the kinds of snags that machines would have no good way of avoiding.<\/p>\n

Somewhere, over the rainbow<\/h3>\n

From all his years working in automation, Hanson wrote, \u201cWhen you see how hard it is to simply digitize a paper process inside a single plant (often a multi-year project), you start to roll your eyes at ivory tower claims of entire industries being totally transformed by automation in a few years.\u201d<\/p>\n

And yet, Hanson and many others still work at automating processes for one very important reason: There\u2019s productivity gold at the end of that rainbow.<\/p>\n

In fact, when you think about it, there\u2019s gold (e.g., productivity gains) at several points along that rainbow. Take automated checkout, for example. Even if we assume that they never get it quite right and that people shopping in brick-and-mortar stores never cotton to self-checkout machines, that doesn\u2019t mean the attempt has been a flop. Far from it.<\/p>\n

Remember, one of the reasons human checkers can compete so successfully with machine checkers is that much of the process has already been automated. Barcodes, scanners, and point-of-sale programs have made it so items don\u2019t have to be individually tagged with prices. This has allowed an explosion in the number of SKUs many stores can carry and cut down much of the friction in adding up the items.<\/p>\n

Before the latest wave of automation, the checker was more of a clerk, adding items as fast as she could punch the buttons. (And before the advent of cash registers, doing all of this on paper.)<\/p>\n

Now, she\u2019s more of a mini-manager, trading local color, making sure that what she\u2019s seeing on her screen makes sense as it scans, fielding questions from customers about prices, accommodating requests for packaging, and finding solutions when the computer isn\u2019t producing the right outcome.<\/p>\n\t\t