AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …

This paper presents a critical review of key ethical issues raised by the emergence of mental
health chatbots. Chatbots use varying degrees of artificial intelligence and are increasingly …

The hidden costs of artificial intelligence, from natural resources and labor to privacy and
freedom What happens when artificial intelligence saturates political life and depletes the …

Algorithmic audits (or 'AI audits') are an increasingly popular mechanism for algorithmic
accountability; however, they remain poorly defined. Without a clear understanding of audit …

Understanding the landscape of potential harms from algorithmic systems enables
practitioners to better anticipate consequences of the systems they build. It also supports the …

Trauma is the physical, emotional, or psychological harm caused by deeply distressing
experiences. Research with communities that may experience high rates of trauma has …

Much attention has focused on algorithmic audits and impact assessments to hold
developers and users of algorithmic systems accountable. But existing algorithmic …

Recent advances in machine learning leverage massive datasets of unlabeled images from
the web to learn general-purpose image representations for tasks from image classification …

Generative models are now capable of producing highly realistic images that look nearly
indistinguishable from the data on which they are trained. This raises the question: if we …

External audits of AI systems are increasingly recognized as a key mechanism for AI
governance. The effectiveness of an audit, however, depends on the degree of access …