The impact of Artificial Intelligence on Ecojustice and Ethics
Abstract
Artificial Intelligence (AI) has attained human-level performance in tasks like text summarization, machine translation, and code generation while handling multimodal data. Despite these advances, AI poses challenges such as generating false or biased outputs, causing discrimination, and exhibiting opaque decision-making processes that hinder bias mitigation. Additionally, training large language models (LLMs) for AI consumes substantial energy and can enable autonomous warfare, posing a threat to eco-justice, and raising sustainability concerns. Their ability to create realistic content poses the risk of misuse and perpetuating misinformation. This article addresses these ethical issues and presents solutions through regulation and technology, with examples of global legislation tackling algorithmic discrimination and consumer rights. It emphasizes the need for a workforce skilled in navigating an AI-driven world. Future research directions touch upon mechanistic interpretability to understand AI outputs, new approaches to natural language processing and multimodal data understanding, and developing more interpretable neural network architectures with fewer parameters. This article summarizes the tutorial on the topic that includes some of the author’s work in related areas.
