AI Makes Avoiding Decisions Cheaper

You ask AI to compare two options. It lists the advantages and disadvantages of each, but that does not feel like enough, so you ask for another perspective. It adds long-term risks. You then ask it to consider the worst case, the team’s capabilities, and what might change in the future. Several rounds later, the analysis is more complete, but the decision has not moved forward.

It looks as though you are still working to find an answer. In practice, each round may only postpone the same thing: accepting one option, giving up the other, and accepting the possibility that your choice will be wrong.

AI has reduced not only the cost of getting answers, but also the cost of avoiding decisions.

“Yes, but…” Used to Come to an End

In the 1964 book Games People Play, psychiatrist Eric Berne described an interaction he called “Why Don’t You—Yes But.”

One person presents a problem, and others offer suggestions one after another. Each suggestion receives a similar reply: “Yes, but that will not work because…” On the surface, the conversation is searching for a solution. In the end, every solution is rejected and the problem remains unchanged.

In the past, this kind of conversation had a natural endpoint.

The people offering advice would get tired. They might realize that whatever they proposed, the other person could always find another “but.” They would stop answering, or simply ask, “So what are you going to do?”

That impatience mattered. It showed the person asking for help that the problem might no longer be a lack of options, but an unwillingness to choose. Continuing to ask for advice strained a relationship and exposed the fact that they were not ready to act. Avoiding the decision was therefore not free.

AI Removed That Friction

AI does not get tired, and it will not stop answering after the tenth “Yes, but…”

It can generate ten more options, try five more perspectives, and simulate another debate between advocates and critics. The person asking does not have to exhaust anyone’s patience or admit that no answer can make the choice—and bear its cost—for them. As long as they keep entering prompts, they can preserve the feeling that they are still engaged in serious analysis.

AI did not create our tendency to avoid decisions. It changed the constraints on that avoidance. In the past, a consultation that went nowhere would eventually be stopped by another person’s patience. Now it can continue indefinitely, and every round can produce more text as evidence that “further analysis” is still needed.

Avoiding a decision has gone from a behavior that encounters social friction to a service that can be renewed almost indefinitely.

Before the Next Prompt

Not every follow-up question is an attempt to avoid a decision. New facts can change the choice, overlooked risks deserve attention, and important judgments need to be checked more than once. The problem is that AI can always keep answering, so it will not tell you when the analysis is over.

Only the person asking can restore that endpoint.

Before sending the next prompt, ask: What did the previous answer change?

If it did not add a new fact that affects the choice, rule out an option, or produce a next action, what is missing may no longer be another answer. It may be a decision that only you can make.

“Why Don’t You—Yes But” is used here only to describe the interaction pattern of repeatedly asking for options and then making every option unworkable. This does not treat Games People Play as a personality theory fully validated by modern experiments. Some of the book’s explanations and examples also reflect the limitations of the 1960s.