When experts first started raising the alarm a couple decades ago about AI misalignment — the risk of powerful, transformative artificial intelligence systems that might not behave as humans hope — a lot of their concerns sounded hypothetical. In the early 2000s, AI research had still produced quite limited returns, and even the best available AI systems failed at a variety of simple tasks.
But since then, AIs have gotten quite good and much cheaper to build. One area where the leaps and bounds have been especially pronounced has been in language and text-generation AIs, which can be trained on enormous collections of text content to produce more text in a similar style. Many startups and research teams are training these AIs for all kinds of tasks, from writing code to producing advertising copy.