CONCEPT
Pseudo-Attempts
The structural problem of AI-era creative production: outputs that occupy the form of creative attempts without involving the evaluative engagement that the equal-odds baseline requires to convert volume into quality.
The pseudo-attempt is the diagnostic category Simonton's framework generates for the AI moment. The equal-odds baseline predicts that excellent work scales with creative volume — but the scaling depends on each unit of volume constituting a genuine creative attempt, involving generation, evaluation, and iteration. When AI makes production trivially easy while leaving creation as hard as it ever was, the risk is that volume increases without the engagement that gives the baseline its predictive power. The lottery tickets are counterfeit. They look real. They occupy space. But they do not carry the probability of genuine tickets because the creative process that loads the probability was never engaged.
In The You On AI Field Guide
The distinction operates at the level of the individual creative act. A developer using AI to explore problems that interest her — generating multiple architectural approaches, evaluating outputs against her judgment, iterating until solutions satisfy her aesthetic sense — is producing genuine attempts. Her output involves full creative engagement, and the equal-odds