The McDonaldization of Science (malcolmmielle.phd)

In a provocative critique, a new article argues that large language models (LLMs) are not enshittifying science but leading it toward its McDonaldization. The author suggests that the efficiency driven by LLMs encourages researchers to prioritize metrics like the h-index and citation counts over substantive contributions to knowledge. This trend promotes a superficial approach to science, where the focus shifts to producing easily digestible results at the expense of innovative, meaningful research. The McDonaldization metaphor emphasizes a system where rational decisions can yield irrational, detrimental outcomes, similar to fast-food businesses optimizing for profit while compromising on quality. The article calls on the AI and science communities to reassess their evaluation metrics and methods, advocating for a more collaborative and creative approach that values deeper impact over mere publication quantity. It challenges established researchers to foster a cultural shift towards "community garden" models of science, which prioritize quality, collaboration, and genuine contributions to the field, in contrast to the rapid-fire, quality-compromising outputs encouraged by current systems. Such a shift is seen as essential for the long-term health of scientific inquiry, especially in an era where LLMs make producing research easier yet risk flooding the field with lower-quality work.