Ranking, recommendation, and retrieval systems are widely used in online platforms and
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …

The education sector has benefited enormously through integrating digital technology driven
tools and platforms. In recent years, artificial intelligence based methods are being …

As machine learning (ML) increasingly affects people and society, awareness of its potential
unwanted consequences has also grown. To anticipate, prevent, and mitigate undesirable …

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

In this viewpoint article we discuss algorithmic decision-making systems (ADMS), which we
view as organizational sociotechnical systems with their use in practice having …

We consider the problem of generating rankings that are fair towards both users and item
producers in recommender systems. We address both usual recommendation (eg, of music …

The recent release of very large language models such as PaLM and GPT-4 has made an
unprecedented impact in the popular media and public consciousness, giving rise to a …

There is a growing consensus in HCI and AI research that the design of AI systems needs to
engage and empower stakeholders who will be affected by AI. However, the manner in …

There is increasing concern that how researchers currently define and measure fairness is
inadequate. Recent calls push to move beyond traditional concepts of fairness and consider …

There is growing interest in designing recommender systems that aim at being fair towards
item producers or their least satisfied users. Inspired by the domain of inequality …