  Recent publications explore AI biases in detecting objects and people in the
environment. However, there is no research tackling how AI examines nature.
This case study presents a pioneering exploration into the AI attitudes
(ecocentric, anthropocentric and antipathetic) toward nature. Experiments with
a Large Language Model (LLM) and an image captioning algorithm demonstrate the
presence of anthropocentric biases in AI. Moreover, to delve deeper into these
biases and Human-Nature-AI interaction, we conducted a real-life experiment in
which participants underwent an immersive de-anthropocentric experience in a
forest and subsequently engaged with ChatGPT to co-create narratives. By
creating fictional AI chatbot characters with ecocentric attributes, emotions
and views, we successfully amplified ecocentric exchanges. We encountered some
difficulties, mainly that participants deviated from narrative co-creation to
short dialogues and questions and answers, possibly due to the novelty of
interacting with LLMs. To solve this problem, we recommend providing
preliminary guidelines on interacting with LLMs and allowing participants to
get familiar with the technology. We plan to repeat this experiment in various
countries and forests to expand our corpus of ecocentric materials.
