Many commentators seem to have forgotten Goodhart’s Law: When a measure becomes a target, it ceases to be a good measure. Jeff Hammerbacher, an early Facebook employee, once lamented that The best minds of my generation are thinking about how to make people click ads. That sucks. Now, hundreds of thousands of smart, energetic people are working on large language models (LLMs) which, so far, have chalked up few successes and lots of collateral damage. The latter includes spreading scams and political disinformation, undermining education, contributing to the replication crisis that discredits scientists and scientific research, and addicting vulnerable people to risky AI buddies. Surely, the people working on LLMs could be doing other things that would benefit society; perhaps designing better transportation systems and less expensive housing. The opportunity costs are enormous. At least that is what I thought until my confidence in their intelligence was shaken by two recent events. The Rise of Tokenmaxxing LLMs break text into small chunks called “tokens,” which are words, parts of words, punctuation marks, or blank spaces. …