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Dear FAccT community, We are writing to share an important update to the ACM FAccT submissions timeline beginning with the 2027 conference cycle.

Every year, thousands of developers of free and open-source software from all over the world gather at FOSDEM. For two weeks around this event – from the 26th…

Hello! We're excited that you're interested in being a reviewer (or Area Chair) for the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT)! Reviewers are the key drivers of the...

MAXMINDS 2.0

Responsible AI Day KDD 2025 – The ACM SIGKDD Conference on Knowledge Discovery and Data Mining Tuesday, August 5, 2025 Toronto, Canada The Responsible AI Special Day at KDD 2025 will explore the inte...

The Best Paper Award Committee was chaired this year by Alex Chouldechova and included six Area Chairs. The committee selected three papers for the Best Paper Award and recognized three additional pap...

CASA – home for cutting-edge IT security research. Innovative, holistic, interdisciplinary: Development of countermeasures against cyber attackers.

UPF is seeking an external consultant to provide support in carrying out and documenting the activities under the EU-funded project FINDHR (www.findhr.eu), GA nº 101070212, HORIZON-CL4-2021-HUMAN-01-2...

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The internet has become an extractive and fragile monoculture. But we can revitalize it using lessons learned by ecologists.

Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these accounts of harm is that generative AI models are trained on workers' creative output without their consent and without giving credit or compensation to the original creators. This paper reports findings from 20 interviews with creative workers in three domains: visual art and design, writing, and programming. We investigate the gaps between current AI governance strategies, what creative workers want out of generative AI governance, and the nuanced role of creative workers' consent, compensation and credit for training AI models on their work. Finally, we make recommendations for how generative AI can be governed and how operators of generative AI systems might more ethically train models on creative output in the future.