Evaluating social and ethical risks from generative AI

Dear Tech enthusiasts! Let’s divulge some fascinating insightful content and introduce a fresh set of comprehensive evaluations for AI systems. As experts in generating, manipulating, and learning from data, we have identified three different layers that assess the risk-appropriate functioning of AI system. In this context, we propose an extensive framework of evaluation to analyze various aspects like capability, human interaction, and systemic impacts, to better inform the downstream safety of generative AI systems. In our new paper, we explore the gap between existing approaches for assessing AI system safety and provide a comprehensive evaluation for two additional layers of evaluation in specific applications like social media, recommendation engines, and natural language processing. We have also made available repurposed evaluation methods for assessing general-purpose models and their functions for ethical consideration. Our findings highlight the importance of leveraging large models themselves as well as engaging institutions to mitigate risks associated with advanced AI development. Finally, we propose building a responsible approach to data enrichment by recognizing the fundamental role of language in communicating thoughts and concepts. Overall, this paper seeks to empower policymakers, industry stakeholders, and technologists to better understand and mitigate the risks associated with AI systems, which are crucial for advancing technology while also promoting responsible governance.