Those of us somewhat interested in chess, or perhaps curious thanks to blockbuster shows like The Queen’s Gambit, have been following the chaos in the world of grandmaster-level chess, particularly the feud between world champions Magnus Carlsen and Hans Niemann. Chess is one of the few competitions where even at the highest levels there are relatively few serious efforts to prevent cheating, even with incidents like Arcangelo Ricciardi receiving morse code signals in his armpit in 2015. That may soon change.
An article in The Washington Post earlier this week discussed the Carlsen-Niemann situation, but from an interesting perspective of the impact of technology on problem-solving. As an aside, it also described the surprisingly high level of physical exertion resulting from the concentration required by chess. During a tournament in 2018, sensors connected to grandmaster Mikhail Antipov revealed he burned 560 calories in two hours, sitting completely still.
The description of using AI for potential cheating is interesting , but the impact of using technology to supplement or even replace thinking is important.
“The Carlsen-Niemann confrontation raises the important matter of “techno-solutionism.” Too much machine intelligence in problem-solving, as it happens, can be more confusing — and weakening — than helpful. The long-term cost of techno-solutionism can be a fatal slackness, both mental and physical. You don’t want to lose your conditioning for decisive human judgment.”
In the article this “techno-solutionism” takes two forms. By using AI and computers, there is less of the learning rigor that traditional chess players go through by playing thousands of games. This also decreases the strength and endurance for what is, although it appears to have little movement, a very physical event. Magnus Carlsen has a very intensely physical daily workout regimen to prepare himself for tournaments with almost no physical movement.
In the lean world we often talk about the problems with technology. Technology itself is not necessarily negative, but it needs to be used appropriately and at the right time.
When recording data, we like teams to first use whiteboards and other manual methods before switching to electronic systems. As Issac Asimov said, “Writing, to me, is simply thinking through my fingers.” Taking the time to write and record data by hand leads to increased pattern recognition, reflection, and understanding. Several studies have shown that college students that take notes by hand demonstrate longer term knowledge and understanding compared to those that took notes on a computer.
Too much reliance on technology can also, especially over time, reduce understanding of underlying processes and associated skills. We see this with computer-controlled manufacturing processes and accounting systems, among many others. We may lose the ability to recognize, and then correct, deficient processes. One example of this was the Asiana 777 crash at San Francisco in 2013. Most pilots still land manually to reinforce their flying skills, but in this case the company policy was to allow more reliance on the autopilot. An investigation showed that the pilots were so used to using the autopilot that they lost the ability to recognize, and then correct, an incorrect landing trajectory.
Technology can also mask or even create waste. Fancy conveyor systems may speed up or automate processes, but the underlying waste may still exist. Data collection systems can generate reports and analyses that are irrelevant and create unnecessary projects and action. How often have we wanted to tell a boss “that’s simply not important!”? We see charts with so many metrics that none are truly understood let alone acted upon.
Technology can create improved understanding and efficiency. But first we need to truly learn what is going on so we can improve the process, then we also need to ensure we maintain and improve that understanding. Technology is a tool, not a solution in itself.