Editorial: What Have Large-Language Models and Generative Al Got to Do With Artificial Life?
Abstract
Accessible generative artificial intelligence (AI) tools like large-language models (LLMs) (e.g., ChatGPT,1 Minerva2) are raising a flurry of questions about the potential and implications of generative algorithms and the ethical use of AI-generated text in a variety of contexts, including open science (Bugbee & Ramachandran, 2023), student assessment (Heidt, 2023), and medicine (Harrer, 2023). Similarly, among the graphic and visual arts communities, the use of generative image synthesis algorithms (e.g., DALL-E,3 Midjourney,4 Stable Diffusion5) that take text prompts as input and produce works in the style of a particular human artist, or no artist who ever lived, are causing consternation and posing challenging questions (Murphy, 2022; Plunkett, 2022). The use of generative AI to create deep fakes has also been in the spotlight (Ruiter, 2021), as has its role in answering scientific research questions directly (Castelvecchi, 2023).To our minds, the questions these technologies are raising do not seem to be of a fundamentally different character to questions asked about AI for many years. They largely concern (a) what is possible, (b) what is right, and (c) the implications of the technology’s use. For instance,Can AI generate documentary “evidence” that is indistinguishable from reality? Can AI generate artifacts that are competitive with (or superior to) those made by a human?How is the concept of “truth” confused or undermined by the output of these technologies? Is it…
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