New paper with Peter Singer on speciesist bias in AI

Somehow, this paper must be something special. It got desk-rejected without review not by one, not by two, but by three different journals! This never happened to me before and I can only speculate about the underlying reasons. However, I am grateful to the editors of AI and Ethics who had the guts to let our research be peer-reviewed and published. But what is it all about? Massive efforts are made to reduce machine biases in order to render AI applications fair. However, the AI fairness field succumbs to a blind spot, namely its insensitivity to discrimination against animals. In order to address this, I wrote a paper together with Peter Singer and colleagues about “speciesist bias” in AI. We investigated several different datasets and AI systems, in particular computer vision models trained on ImageNet, word embeddings, and large language models like GPT-3, revealing significant speciesist biases in them. Our conclusion: AI technologies currently play a significant role in perpetuating and normalizing violence against animals, especially farmed animals. This can only be changed when AI fairness frameworks widen their scope and include mitigation measures for speciesist biases.

PS: I had the opportunity to publish an op-ed article in the German tech magazine Golem as well as a research summary at The AI Ethics Brief regarding the paper.

Blind spots in AI ethics

I wrote a critical piece about my own field of research. It discusses the conservative nature of AI ethics’ main principles as well as the disregarding of negative externalities of AI technologies. The paper was recently published in AI and Ethics and can be accessed here.