The field of artificial intelligence is moving towards a greater emphasis on sustainability and ethics. Researchers are investigating the environmental and social impacts of AI, including the unequal distribution of costs and benefits, and the role of big tech in shaping the development of AI. There is a growing recognition of the need for more responsible and sustainable approaches to AI research, including the development of more efficient and environmentally-friendly hardware, and the creation of more equitable and inclusive value chains. Noteworthy papers in this area include: The paper 'The dual footprint of artificial intelligence: environmental and social impacts across the globe' which introduces the concept of the 'dual footprint' to capture the commonalities and interdependencies between the environmental and social impacts of AI. The paper 'From FLOPs to Footprints: The Resource Cost of Artificial Intelligence' which quantifies the material footprint of AI training and highlights the need for more sustainable approaches to AI research. The paper 'Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value' which proposes a new approach to aligning AI systems with human values, and highlights the need for more nuanced and contextual understandings of value and ethics in AI research.