When it comes to automation, people tend to assume the robots will perform the same tasks as the humans they replace, just with fewer mistakes and fewer days off. While that is true, automation almost always means changing how the work gets done, in order to break it into discrete operations. Instead of a man at a workstation, doing a series of tasks, each task is done as a single event by a single robot. This simplifies the task of automation and reduces the cost of the automation by eliminating variables.

This atomization of the work not only makes the work process more efficient, it changes how the humans have to analyze it. Instead of focusing on the people, they must focus on the process. That’s always part of process improvement, but because the process changes and the variables change, new phenomenon turn up in the process. In statistics, they say quantity has a quality all its own. In automated systems, speed has a quality all its own. Those super fast, super accurate robots change the nature of the process.

Think of the game of table tennis. It is a pretty simple game, in terms of strategy. The players try to trick one another with various tactics like setting up a shot or putting spin on the ball so it is hard to return. Player A will use top spin to force Player B to change how he strikes the ball. At some point Player A will change, thus fooling Player B, who then hits the ball beyond the far edge of the table. Alternatively, one player will make the other player move side to side, increasing the chances of a physical error.

If you are coaching table tennis, it is all about training the human to play against the other human. Now, replace the players with robots. The first thing that changes is the players will not make physical errors. So, the side to side business no longer makes sense. The same is true of using ball spin to induce a physical error. The robots will strike the ball correctly each time. In other words, when you remove human error and human emotion from the game, the strategy of the game has to change as well.

It also means the game changes. For example, the team that makes the first robot player will build it to capitalize on human error. Soon, other teams will replace their humans with robots. At that point, everyone stops trying to exploit human error. Instead, they are trying to make faster robots. If their robots can exceed the physical limits of the other robots, then they win. Soon, there is an arms race between the robot builders to make the fastest robot, in terms of physical response, along with the faster processors.

If you stop and think about what this would look like, it sounds kind of cool at first. The first robots would be slow and stupid, but eventually they would pretty amazing. They would go from amusing to terrifying as the speed of the game would become incomprehensible to humans. The speed, agility and processing power of the machines would have the ball flying through the air near its maximum velocity of 900 miles per hour. The paddles would be made of special material, in order to prevent them from flying apart.

Automating the game of table tennis would first result in removing the strategy of the game that exploits human failure. This would be true of any system that is being automated. System analysis would also change as the speed of the machines would create new points of failure and new challenges, in terms of finding efficiency and a competitive edge. In other words, as the problem solving shifts from the human variable to the engineering issues, system analysis has to change accordingly.

Now, instead of robots playing table tennis, let’s think of something else. Currently, close to 90% of trades in the equities markets are done by robots, which are just computer programs attached to the financial system. These programs have access to financial data throughout the system, which is inputted into their systems and the output is the buy and sell decisions. Teams of smart people called “quants” spend endless hours fine-tuning their programs to make them faster and more efficient at trading equities.

If you read the book The Money Game, which was written in the 1960’s, it presciently predicted the rise of the machines in the financial markets. What was clear to smart people at the dawn of the robot age, but not clear to most people, is the old systems regulating and controlling markets would not hold up to automation. It took the Black Monday crash of 1987 for everyone to realize that the controls had to change in order to accommodate the new robot players in the financial system.

In the 2000’s, the rise of high speed trading algorithms and large scale trading models eventually broke the system again. The emergence of the so-called “flash-crash” was entirely due to speed. While the first phase of automation removed the normal human checks on trading, resulting in runaway selling, the next phase of automation allowed for bad human decisions, like errors in trading algorithms, to be implemented so quickly, the systems could not respond. The result was erroneous sell-offs.

That brings us to the current market volatility. The decline itself is getting all of the attention, mostly for marketing and political reasons. The dullards in the media know how to sell gloom and they like blaming bad news on Trump. Historically, this bear market is not important. Whether it is called a correction or a bear market, the numbers are not all that significant. We’ve seen much worse. No one is jumping from their office windows and the public is not banging the sell button on the investment account.

What’s unique about this market is the weirdness. There is sustained volatility, but also a sustained decline, that does not appear to correlate to factors in the economy or in the financial system. The tiniest bit of news can cause wild swings. Apple announced what everyone should have known by now, that their toys are not selling as well as in the past, and the market takes a big tumble. Apple shares dropped 10% in minutes. Of course, this ripples to the rest of the market in seconds as well.

What could be happening is the next phase of automation. The speed and complexity of the algorithms are no longer comprehensible by the humans involved in the system. Like our table tennis playing robots, a level of speed and complexity passes the event horizon of humans to comprehend. Watching the robots play table tennis would be like watching a whirl of stars, beautiful, but impossible for the mind to fathom. Similarly, the new market dynamics may be reaching the limits of human regulators to fathom.

This is not to imply that the robot traders have become aware and are now taking control of the system from humans. That would be interesting, but the robots are still relatively dumb. Instead, they have reached levels of efficiency and speed that exceeds our ability to model properly. The result is the wild volatility and the seemingly irrational behavior of the markets. Put another way, this is the age of basic ideas implemented so fast and with such efficiency, they become irrational to their human creators.