Finding QAnon: A Technology Parable

Bro Adams
2 min readFeb 21, 2022


LAST WEEK, The New York Times published an article about the apparently successful conclusion to the search for the mysterious author of the poisonous QAnon conspiracy theories that have plagued political discourse in the United States and elsewhere since 2017. According to The Times, the anonymous Q was in fact two early proselytizers–Paul Furber and Ron Watkins–whose public enthusiasms were linked stylistically to postings by Q.

The sleuths in the case were two pairs of forensic linguists–Claude-Alain Roten and Lionel Pousaz of Switzerland, and Florian Cafiero and Jean-Baptiste Camps from France–who used Artificial Intelligence tools to compare Q’s writing with the writing of a long list of possible suspects. Their computational analyses discovered substantial continuities between the ramblings of Q and subsequent messages composed by Furber and Watkins.

It’s an encouraging story in some ways, beginning with its validation of the importance of linguistics as a field of study. It’s not often that this (or any) core subject in the humanities gets such unequivocally positive press. The story also offers yet another instance of how powerful and useful Artificial Intelligence has become in solving all kinds of problems, including, now, the unmasking of the agents of malevolent disinformation in the political sphere.

In other ways, however, the story is distressing. For it reminds us again of how dominant the instruments and effects of digital technology have become in our political lives. The bizarre ramblings of Furber and Watkins were able to gather an audience because the web’s tentacles now reach into every part of the political sphere, strangling more traditional and well-ventilated sources of information and communication. And if this particular application of AI appears to have serviced the common good, there are many more uses that do not, including the algorithms that enable the mass electronic distribution of political falsehoods. In some quarters, AI is regarded as a model for thinking itself; the mind as information machine. Our digital instruments are like the brooms and buckets in Fantasia’s retelling of “The Sorcerer’s Apprentice,” familiar household objects that take on magical, malevolent powers when summoned unwittingly from the closet.

In one sense, it’s always been this way. We invent new technologies to solve problems; new technologies create new problems; the new problems require still more technologies, and so on, to the end of time. But the world of information technology seems different somehow. Every new solution seems to create more expansive and complex problems, whose solutions seem to require more expansive and complex commitments to the digital realm. The innovation loop, or spiral, seems increasingly self-referential, sealed off, closed. All sorcery, no apprentice.