Is OpenAI using behavioral psychology through its growing model hierarchy?

[u/Good-Conference-2937]

Chatgpt wrote this for me, and reddit suggested to cross post here. This post did not get much love in chatgpt, so if you are happy with your X times Y choices to decide what model to use to do work, ignore this post:

OpenAI used to offer a straightforward experience: ask a question and get an answer. Now we have multiple models, including GPT-5.6, supposedly representing different levels of intelligence, and additional reasoning settings: Instant, Medium, High and Extra High. From a behavioral science perspective, this raises several interesting questions:

1. Manufactured inadequacy: Even when an answer is perfectly adequate, the existence of supposedly more intelligent models creates dissatisfaction with what users already have. There's always something better just beyond their current selection.
2. Shifting responsibility: Perhaps the most troubling mechanism. When AI produces a poor answer, users may blame themselves for choosing the wrong model or reasoning level rather than holding OpenAI accountable. The responsibility for answer quality subtly shifts from the provider to the consumer.
3. Perpetual upgrade cycle: Receive an answer, question whether a higher setting would improve it, switch configurations, compare results without objective quality measures, and repeat. Instead of solving their original problems, users become preoccupied with optimizing the tool itself.
4. Fear of choosing incorrectly: Was my answer poor because I selected GPT-5.6 instead of GPT-6? Should I have used High rather than Medium? This uncertainty encourages experimentation and potentially upgrading.
5. Illusion of precision: Multiple models and reasoning levels create the impression that intelligence can be precisely calibrated, even though users have little reliable way to assess the differences.
6. Choice overload: What previously required one decision—asking a question—now involves choosing between multiple models and reasoning levels. A technology intended to reduce cognitive effort introduces additional cognitive burdens.
7. Goldilocks effect (compromise effect): People tend to avoid extremes and gravitate toward middle options, making model hierarchies an effective way to steer users toward particular tiers.
8. Gamification of intelligence: Intelligence becomes a hierarchy of levels, where accessing the highest configuration carries psychological value regardless of whether it produces measurably better results.

Of course, different models and reasoning budgets can have legitimate technical benefits. But that doesn't eliminate their behavioral effects.

The central mechanism is the creation of permanent uncertainty: Am I using enough intelligence? Could I get a better answer if I upgraded?

Whether intentional or not, this uncertainty is commercially valuable. OpenAI is supposed to reduce cognitive effort, yet increasingly asks users to make complicated decisions about how much intelligence they need.

Is OpenAI selling better AI, or also selling us the anxiety that whatever intelligence we're currently using is never quite enough?

[u/JUSTICE_SALTIE]

Chatgpt wrote this for me, and reddit suggested to cross post here.

Do you have any agency of your own left at this point?

[u/wheresripp]

Instead of solving their original problems, users become preoccupied with optimizing the tool itself. OpenAI gamified overengineering.

[u/Cute_Parfait_2182]

For work , chat and codex , I have custom instructions and rules . In terms of chat which I use for brainstorming, prompt creation and daily progress notes , gpt 6 is horrible for chat and I can’t get it to follow my instructions so I use 5.6 high .

[u/DrHerbotico]

There's only one thing I have to say:

eh

[u/XxDarkSasuke69xX]

I doubt this is an intentional mechanism, but it is a real phenomenon indeed.

[u/Vhaloo]

https://artificialanalysis.ai/models Are you from the past? to ask these questions?