Despite the growing consensus that stakeholders affected by AI systems should participate
in their design, enormous variation and implicit disagreements exist among current …

In recent years, the effective governance of artificial intelligence (AI) systems has become a
strategic necessity for many nations. Among those nations, Canada is particularly …

Text-to-image generation has become very popular in various domains requiring creativity.
This article investigates the potential of text-to-image generators in supporting creativity …

Diversity in datasets is a key component to building responsible AI/ML. Despite this
recognition, we know little about the diversity among the annotators involved in data …

The race to train language models on vast, diverse, and inconsistently documented datasets
has raised pressing concerns about the legal and ethical risks for practitioners. To remedy …

Humans produce and consume language in a particular cultural context, which includes
knowledge about specific norms and practices. A listener's awareness of the cultural context …

Calls for representation in artificial intelligence (AI) and machine learning (ML) are
widespread, with" representation" or" representativeness" generally understood to be both …

Many recent technological advances (eg ChatGPT and search engines) are possible only
because of massive amounts of user-generated data produced through user interactions …

As artificial intelligence (AI) continues to captivate the collective imagination through the
latest generation of generative AI models such as DALL-E and ChatGPT, the dehumanizing …

Impact sourcing is the practice of employing socio-economically disadvantaged individuals
at business process outsourcing centres to reduce poverty and create secure jobs. One of …