Unerasable Characters by Winnie Soon (2019)

Winnie Soon is a practice-based researcher, artist and coder. She is interested in the cultural and political implications of software infrastructure. Her recent lines of enquiry follow themes of visibility and erasure.

In her project Unerasable Characters, Soon uses machine learning to generate pieces of text from a database of censored comments on the Chinese social platform Weibo. The output is a representation of a collective censored voice.

Machine learning (ML) is used here as a conceptual tool; the process of querying this database is more important than the output. ML is usually used as a way to reach a desired goal or make predictions. Here, the ML process is used as an attempt to query this censorship practice.

The resulting lines of text that are generated are nonsensical. Although this does not provide useful data in the conventional sense, it does reveal something about the mechanics of this particular type of censorship. There are no official guidelines of what is likely to be censored — it often comes as a surprise when a user finds their post has disappeared or that they’re no longer able to receive messages.

And so a game of semantic cat-and-mouse is constantly being played between the platform censors and the users trying to get their subversive messages out there. The messages become increasingly subversive and so the collective ML output becomes increasingly nonsensical. This is further complicated by the use of emojis, slang and other languages.

The ML process of enquiry in this instant is useful as an artistic tool to illustrate the absurd game that is being played on this social platform between the subversive political activists / trolls on one side, constantly thinking up new ways of getting censored messages across undetected, and the state censors on the other side, blocking messages and shutting down accounts, creating an ever-growing list of forbidden words and symbols.