ΑΙhub.org
 

Watch the talks from the ACM Conference on Fairness, Accountability, and Transparency


by
18 August 2022



share this:
FAcct tiger logo

The ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) took place in Seoul, South Korea from 21-24 June 2022. The event brought together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.

All of the keynote talks, panel discussions, tutorials, and research talks are available to watch on YouTube. There are playlists for each:

There were four distinguished paper awards presented at the conference. You can see the associated talks below:


The values encoded in machine learning research
Abeba Birhane, Pratyusha Kalluri, Dallas Card, William Agnew, Ravit Dotan and Michelle Bao


Fairness-aware model-agnostic positive and unlabeled learning
Ziwei Wu and Jingrui He


Algorithmic tools in public employment services: towards a jobseeker-centric perspective
Kristen Scott, Sonja Mei Wang, Milagros Miceli, Pieter Delobelle, Karolina Sztandar-Sztanderska and Bettina Berendt


Towards intersectional feminist and participatory ML: a case study in supporting feminicide counterdata collection
H. Suresh, R. Movva, A. Lee Dogan, R. Bhargava, I. Cruxen, A. Martinez Cuba, G. Taurino, W. So, C. D’Ignazio





Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



Interview with Yuki Mitsufuji: Improving AI image generation

  23 Jan 2025
Find out about two pieces of research tackling different aspects of image generation.

The Good Robot podcast: Using feminist chatbots to fight trolls with Sarah Ciston

  22 Jan 2025
Eleanor and Kerry chat to Sarah Ciston about the difficult labor of content moderation, chatbots to combat trolls, and more.

An open-source training framework to advance multimodal AI

  22 Jan 2025
EPFL researchers have developed 4M, a next-generation, framework for training versatile and scalable multimodal foundation models.

Optimizing LLM test-time compute involves solving a meta-RL problem

  20 Jan 2025
By altering the LLM training objective, we can reuse existing data along with more test-time compute to train models to do better.

Generating a biomedical knowledge graph question answering dataset

  17 Jan 2025
Introducing PrimeKGQA - a scalable approach to dataset generation, harnessing the power of large language models.

The Machine Ethics podcast: 2024 in review with Karin Rudolph and Ben Byford

Karin Rudolph and Ben Byford talk about 2024 touching on the EU AI Act, agent-based AI and advertising, AI search and access to information, conflicting goals of many AI agents, and much more.

Playbook released with guidance on creating images of AI

  15 Jan 2025
Archival Images of AI project enables the creation of meaningful and compelling images of AI.




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association