There’s a kinda meme image circulating where a person says they had imagined a future where AI made her work easier so that she had more time for creative leisure. Instead, AI is being used to generate creative work.
The unspoken conclusion is that the woman continues to be stuck working hard.
Additionally there is an increasing skepticism about any sort of creative work being the result of the artist. I was watching artists presenting proposals for public art installations in the last two weeks and each made very specific disclaimers about what in their presentations was AI generated. (Largely, it was the streetscapes in which the proposed art work was positioned.)
Economist Tyler Cowen recently posted a job listing which was paying people with sports expertise pretty well to evaluate AI tools analysis of basketball games. As a number of commenters noted, people would essentially be training their replacements.
Since I have already seen an AI translate foreign language into English from video and match the energy of the speaker, I imagine it won’t be long before AI is doing analysis and color sports commentary in real time, drawing from existing reporting about injuries and career history.
I guess there is potential for these tools to be applied to reviews of performances and lead to a return of arts coverage. Though I imagine that would be a lot tougher to identify the nuances in technique and tempo in dance and music those fans want vs. analysis of a basketball game. One obvious concern in addition to this tool replacing human writers is AI reviewing work created by AI.
Here is the job description Cowen posted.
Role Overview
We’re looking for Basketball experts — avid fans, sports journalists, commentators, and former or semi-professional players — to evaluate basketball games. You’ll watch basketball games and answer questions in real time assessing the quality, depth, and accuracy of AI insights, helping us refine our AI’s basketball reasoning, storytelling, and strategic understanding.
Key Responsibilities
Game Evaluation: Watch basketball games and review AI-generated play-by-play commentary and post-game analysis.
Performance Scoring: Rate the accuracy, insight, and entertainment value of AI sports coverage.
Context & Understanding: Assess the AI’s grasp of player performance, game flow, and strategic decisions.
Error Detection: Identify factual mistakes, poor interpretations, or stylistic inconsistencies.
Feedback Reporting: Provide clear written feedback highlighting strengths, weaknesses, and improvement opportunities.
Collaboration: Work with analysts and developers to enhance the AI’s basketball-specific reasoning and realism.

