As language models are fine-tuned to acquire more capabilities, we continue to seek new tasks to push the limits of Generative AI. In setting cryptic crossword clues, so far GPT-4 fails the test quite spectacularly.
What skills do social scientists need to adapt to generative AI, and how should educators approach teaching them? A narrow focus on training everyone in technical skills is misguided – what’s needed is authorial voice, leadership and management skills, and the critical force of the social sciences.
Can a language model outperform old Edward Lear in describing philosophers in Limerick form? “There once was a Scotsman named Hume…”
Will large language models acknowledge authorship of their own generated texts? Will a language model claim authorship or ownership of texts which it did not create? A mistaken comprehension of ChatGPT’s abilities throws up a distinctive problem of intellectual property rights.
What is the relationship between perplexity, creativity and novelty? Following on from ‘Perplexing Perplexity’, I set out to demonstrate that high perplexity texts are not always creative, and to showcase ChatGPT’s ability to work with and even generate novel words – culminating in the Tale of Zonkamoozle.