A practical implication of the Astolfo Effect: bias in AI generated images

Abstract

The year of 2022 saw a huge advance in AI technology, especially Large Language Models, or LLMs. This culminated in the release of Chat GPT, an AI Chatbot assistant that, as of the time of this writing, is wowing the public with its uncanny performance.<p>

<p>However, chatbots are not the only application of LLMs. One such application is the artificial generation of images. Although such idea is not a novel one (it dates back to the 1970s; Elgammal, 2022), the advancements on large language models allowed a new breakthrough in what these methods are able to achieve.<p>

<p>A non-obvious application of such models is as a “probe” for bias in its learning set. Since these models are trained on public datasets collected from the Internet, they tend to reflect the inherent biases present in human generated content. As such, we see the advent of AI generated image as an opportunity to further test the ‘Astolfo Effect’ hypothesis, as first outlined by Tomotani & Salvador (2021).