The Two Sacred Principles That Make AI Addictive
Every behavioral addiction turns less on the size of a reward than on its price
Good morning. Let’s start this Tuesday together. Because, as always, “It is perfectly possible to be both rational and wrong.”
Every company runs on two unwritten principles that feel too obvious to state: that results should get better, and that effort should get smaller, and for most of corporate history these two sat in tension until a tool arrived that promised to satisfy both at once.
A planning team that once spent a whole Tuesday morning fighting through a strategy memo now produces four versions of it before the coffee is cold and picks the one that reads best, until a board member asks months later why the third assumption holds, and the room discovers it cannot rebuild an argument it never actually made.
How Does It Work?
Every behavioral addiction turns less on the size of a reward than on its price, because the brain weighs a reward against the effort it took to reach it, which is why dopamine, a prediction signal rather than a pleasure signal in Wolfram Schultz’s work, fires hardest when a good outcome arrives more easily than expected, so that cutting effort toward zero while the reward stays intact builds the profile of a slot machine.
Why This Is Important?
The two principles are not equally dangerous, because better results cost a company nothing while the compulsive avoidance of effort costs it the one thing it cannot buy back, namely cognitive capacity, which is not stored but built through the very friction the frictionless tool quietly removes, so that an organization optimizing away its own effort comes to resemble a person who pays a trainer to exercise for them and then wonders why they grow weaker.
And Now?
The answer is not less AI, which no organization will accept and none should, but an end to treating all effort as a cost, since some of it is waste worth removing and some of it is the actual work, which replaces the reflex of doing a task faster with the harder question of which effort is friction and which is the thinking that must survive even when a tool could remove it.
Bottom Line
Core knowledge: AI becomes addictive inside companies not because it improves results but because it lets people avoid the effort that builds the very capacity those results depend on.
Watch for the task that turned pleasant rather than productive, since ease is often the first sign of capacity leaving the room
Separate the effort that is waste from the effort that is the actual thinking before you automate either of them
Give people feedback on the quality of their process rather than the speed of their output
Ask whether your team can still rebuild the reasoning behind a decision or only recall its conclusion
Chief Behavioral Officer wanted.
Where are management decisions made every day that are still based on people acting logically? Where can you be a Chief Behavioral Officer yourself this week?
See you next Tuesday.
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