aiguide

Machines are now able to generate text that is hard to distinguish from that generated by humans. This gives rise to many potential problems; for example, enabling efficient automation of misinformation, spam, impersonation, student cheating on writing and coding homework, and so on. How can society deal with the upcoming deluge of machine-generated text? This is an urgent problem, but fortunately there is a lot of promising research in the works aimed at enabling people to detect when a text has been generated by a machine.

My first post on this blog was a perspective on a very interesting paper by Webb et al., “Emergent Analogical Reasoning in Large Language Models”. Taylor Webb, the first author of that paper, responded by email to my perspective, and he gave me permission to post his response on this blog. Here is Taylor’s thoughtful response, which is well worth reading. I will make a few comments at the end.