Brit Award-winning singer Jorja Smith's record label has said it wants a share of the royalties for a song it claims was created using an artificial intelligence clone of the singer's voice. I Run by British dance act Haven went viral on TiKTok in October thanks, in part, to smooth soul vocals by an uncredited female singer. Although I Run has now been re-released with new vocals, Smith's label FAMM said it believes the track was made with AI trained on her work, and is seeking compensation. It's bigger than one artist or one song, FAMM wrote in a statement on Instagram . The label said it believes both versions of the track infringe on Jorja's rights and unfairly take advantage of the work of all the songwriters with whom she collaborates.

A geography professor shared his method to detect AI-generated plagiarism with Fox News. He developed it after noticing that ChatGPT produced fake citations. Companies that develop software to detect if artificial intelligence or humans authored an essay or other written assignment are having a windfall moment amid ChatGPT's wild success. ChatGPT launched last November and quickly grew to 100 million monthly active users by January, setting a record as the fastest-growing user base ever. The platform has been especially favored by younger generations, including students in middle school through college.

The Writers Guild of America has proposed allowing artificial intelligence to write scripts, as long as it does not affect writers' credits or residuals. The guild had previously indicated that it would propose regulating the use of AI in the writing process, which has recently surfaced as a concern for writers who fear losing out on jobs. But contrary to some expectations, the guild is not proposing an outright ban on the use of AI technology. Instead, the proposal would allow a writer to use ChatGPT to help write a script without having to share writing credit or divide residuals. Or, a studio executive could hand the writer an AI-generated script to rewrite or polish and the writer would still be considered the first writer on the project.

Thinking of technology as a design material is appealing. It encourages designers to explore the material's properties to understand its capabilities and limitations, a prerequisite to generative design thinking. However, as a material, AI resists this approach because its properties emerge as part of the design process itself. Therefore, designers and AI engineers must collaborate in new ways to create both the material and its application experience. We investigate the co-creation process through a design study with 10 pairs of designers and engineers. We find that design 'probes' with user data are a useful tool in defining AI materials. Through data probes, designers construct designerly representations of the envisioned AI experience (AIX) to identify desirable AI characteristics. Data probes facilitate divergent thinking, material testing, and design validation. Based on our findings, we propose a process model for co-creating AIX and offer design considerations for incorporating data probes in design tools.