The Paradox of Automation
Machines are getting smarter. More and more tasks are becoming fully automated. As this happens, there is a tendency to believe that many of the difficulties involved with human control will go away. Across the world, automobile accidents kill and injure tens of millions of people every year. When we finally have widespread adoption of self-driving cars, the accident and casualty rate will probably be dramatically reduced, just as automation in factories and aviation have increased efficiency while lowering both error and the rate of injury.
When automation works, it is wonderful, but when it fails, the resulting impact is usually unexpected and, as a result, dangerous. Today, automation and networked electrical generation systems have dramatically reduced the amount of time that electrical power is not available to homes and businesses. But when the electrical power grid goes down, it can affect huge sections of a country and take many days to recover. With self-driving cars, I predict that we will have fewer accidents and injuries, but when there is an accident, it will be huge.
Efficient automation makes humans more important, not less.
The Paradox of Automation says that the more efficient the automated system, the more crucial the human contribution of the operators. Humans are less involved, but their involvement becomes more critical.
If an automated system has an error, it will multiply that error until it’s fixed or shut down. This is where human operators come in.
Helping not replacing
Automatic systems can take over tasks that used to be done by people, and saves them from the dull, dreary routine tasks, allowing more useful, productive use of time, reducing fatigue and error. But when the task gets too complex, automation tends to give up. This, of course, is precisely when it is needed the most. The paradox is that automation can take over the dull, dreary tasks but fail with the complex ones.
”Full automation is a myth.” - Svetlana Sicular, research vice president at Gartner.
Augmented intelligence is growing as an approach to artificial intelligence, in a way that helps humans complete tasks faster, rather than being replaced by machines entirely. In an IBM report called “AI in 2020: From Experimentation to Adoption,” 45% of respondents from large companies said they have adopted AI, while 29% of small and medium-sized businesses said they did the same. All of these companies are still in the early days of AI adoption, and are looking for ways to infuse it to bolster their workforce.
Ginni Rometty, the former CEO of IBM, said in a talk at the World Economic Forum that augmented intelligence is the preferable lens through which to look at AI in the future.
There are tasks that require expertise and decision-making that can only be accomplished by the essential creativity that only humans could bring to the table. AI is really an assistant to help you get done with the mindless tasks more quickly so you can focus on the more challenging creative aspects. Automation is being used across organizations that typically require very repeatable tasks such as customer churn and telecommunications, recommendations in retail and supply chain.
If a computer does the work, the need for people often increases
What’s happening with automation is not so simple or obvious. It turns out that workers will have greater employment opportunities if their occupation undergoes some degree of computer automation. As long as they can learn to use the new tools, automation will be their friend.
Take the legal industry as an example. Computers are taking over some of the work of lawyers and paralegals, and they’re doing a better job of it. For over a decade, computers have been used to sort through corporate documents to find those that are relevant to lawsuits. This process—called “discovery” in the profession—can run up millions of dollars in legal bills, but electronic methods can erase the vast majority of those costs. Moreover, the computers are often more accurate than humans: In one study, software correctly found 95 percent of the relevant documents, while humans identified only 51 percent.
But, perhaps surprisingly, electronic discovery software has not thrown paralegals and lawyers into unemployment lines. In fact, employment for paralegals and lawyers has grown robustly. While electronic discovery software has become a billion-dollar business since the late 1990s, jobs for paralegals and legal-support workers actually grew faster than the labor force as a whole, adding over 50,000 jobs since 2000, according to data from the U.S. Census Bureau. The number of lawyers increased by a quarter of a million.
How can this be?
It might seem a sure thing that automating a task would reduce employment in an occupation. But that logic ignores some basic economics: Automation reduces the cost of a product or service, and lower prices tend to attract more customers. Software made it cheaper and faster to trawl through legal documents, so law firms searched more documents and judges allowed more and more-expansive discovery requests.
When demand increases enough in response to lower prices, employment goes up with automation, not down. And this is what has been happening with computer automation overall during the last three decades. It’s also what happened during the Industrial Revolution when automation in textiles, steel-making, and a whole range of other industries led to a major increase in manufacturing jobs.
Photo by Maxim Hopman on Unsplash