The field of generative AI is rapidly evolving, with a growing focus on mitigating risks and ensuring responsible development. Researchers are exploring the potential threats posed by open-weight AI models, including accelerated malware development and enhanced social engineering. To address these concerns, there is a need for pragmatic policy interpretations, defensive AI innovation, and international collaboration on standards and cyber threat intelligence sharing. Additionally, the issue of digital waste, or stored data that consumes resources without serving a specific purpose, is becoming a critical sustainability challenge. Studies are investigating the impact of generative AI on administrative burdens, trust dynamics, and the effectiveness of labeling AI-generated images in reducing misinformation. Noteworthy papers include:

• Mitigating Cyber Risk in the Age of Open-Weight LLMs, which proposes evaluating and controlling specific high-risk capabilities rather than entire models.
• Responsible Data Stewardship, which introduces digital waste as an ethical imperative within AI development and proposes strategies to mitigate its environmental consequences.