Abstract Evaluation practices in natural language generation (NLG) have many known flaws,
but improved evaluation approaches are rarely widely adopted. This issue has become …

This paper investigates the direct risks and harms associated with modern text-to-image
generative models, such as DALL-E and Midjourney, through a comprehensive literature …

Natural language generation has witnessed significant advancements due to the training of
large language models on vast internet-scale datasets. Despite these advancements, there …

Human annotated data plays a crucial role in machine learning (ML) research and
development. However, the ethical considerations around the processes and decisions that …

The importance and pervasiveness of emotions in our lives makes affective computing a
tremendously important and vibrant line of work. Systems for automatic emotion recognition …

We present the first English corpus study on abusive language towards three conversational
AI systems gathered" in the wild": an open-domain social bot, a rule-based chatbot, and a …

Human annotations play a crucial role in machine learning (ML) research and development.
However, the ethical considerations around the processes and decisions that go into …

We present POTATO, the Portable text annotation tool, a free, fully open-sourced annotation
system that 1) supports labeling many types of text and multimodal data; 2) offers easy-to …

ImageNet-1k is a dataset often used for benchmarking machine learning (ML) models and
evaluating tasks such as image recognition and object detection. Wild animals make up …

A key part of the NLP ethics movement is responsible use of data, but exactly what that
means or how it can be best achieved remain unclear. This position paper discusses the …