Ever since OpenAI released ChatGPT, the internet has been awash in synthetic text, with suggested applications including robo-lawyers, robo-therapists, and robo-journalists. All of these applications present unacceptable risks because ChatGPT and all other language models are nothing more than ungrounded text synthesis machines. I will overview how language models work and why they can seem to be using language meaningfully—despite only modeling the distribution of word forms. This leads into a discussion of the risks we identified in the Stochastic Parrots paper (Bender, Gebru et al 2021) and how they are playing out in the era of ChatGPT. Finally, I will explore what must hold for an appropriate use case for text synthesis.

"AI" doesn't refer to a coherent set of technologies. Instead, it is and always has been a marketing term, designed to sell technology that concentrates power, replicates and amplifies historical biases, and displaces accountability. In this talk, I demystify the range of technologies sold as "AI", explain the mechanisms of AI hype, and offer strategies for making informed decisions amidst the noise.

Humans make sense of language in context, bringing to bear their own understanding of the world including their model of their interlocutor's understanding of the world. In this talk, I will explore various potential risks that arise when we as humans bring this sense-making capacity to interactions with artificial interlocutors. That is, I will ask what happens in conversations where one party has no (or extremely limited) access to meaning and all of the interpretative work rests with the other, and briefly explore what this entails for the design of language technology.