This chapter describes the concept of combining generative and traditional Artificial Intelligence (AI), citizen-science physiological, neuroergonomic wearables and environmental sensors into activities for learners to understand their own well-being and emotional states better with a view to developing empathy and environmental stewardship. Alongside bespoke and affordable wearables, interpretable AI and data science were used for learners to explore how the environment affects them physiologically and mentally in authentic environments. As anthropogenic environmental pollution is becoming a prevalent problem, our research also aims to leverage on generative AI to introduce hypothetical scenarios of the environment as emotionally strong stimuli of relevance to the learners. This would provoke an emotional response for them to learn about their own physiological and neurological responses (using neuro-physiological data). With respect to changes in microclimate, fluctuations in ambient temperature tend to increase cognitive stress and make emotional arousal and emotional valence more negative (less positive). Furthermore, it was found that air quality also has a great impact on participants’ cognitive stress. The results also suggest that the act of viewing images that convey environmental degradation mostly leads to higher emotional arousal and emotional valence. By involving themselves in the act of using Generative AI—specifically Generative fill—in altering images to convey environmental degradation, participants experienced more intense and negative emotions. Ultimately, we hope to establish a bidirectional understanding of how the environment affects humans physiologically and mentally; after which, to gain insights as to how AI can be used to effectively foster empathy, pro-environmental attitudes and stewardship.