The author suggests that this trend is not limited to academia but is also prevalent in AI industry labs and even in the hiring process for machine learning engineering jobs. The author warns that this could lead to a situation where the quantity of work produced becomes more important than the quality or originality of the work. The author concludes by expressing concern about the potential negative impacts of this trend on the future of work and workers in the AI field.
Key takeaways:
- The article discusses the increasing pressure in the AI research field to constantly produce and publish work, leading to what the author calls "RL career games".
- The author argues that this pressure to constantly produce can lead to a loss of genuine interest and passion in the field, as researchers are more focused on meeting metrics and gaining recognition.
- The author also highlights the issue of "leaderboard inversion", where individual rankings on projects are turned into a ranking of the individuals themselves, leading to further pressure and competition.
- The author concludes by warning of the "Great AI Weirding", where AI is used to quantify and rank everything, leading to a loss of individuality and consent in decision-making processes.