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.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Introducing ARFBench: A time series question-answering benchmark based on real incidents

  18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.

Does ‘federated unlearning’ in AI improve data privacy, or create a new cybersecurity risk?

  15 May 2026
As the capacity of AI systems increases apace, so do concerns about the privacy of user data.

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.

Half of AI health answers are wrong even though they sound convincing – new study

  12 May 2026
Imagine you have just been diagnosed with early-stage cancer and, before your next appointment, you type a question into an AI chatbot.

Gradient-based planning for world models at longer horizons

  11 May 2026
What were the problems that motivated this project and what was the approach to address them?

It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea

  08 May 2026
Increased offloading to new tools has raised the fear that people will become overly reliant on AI.

Making AI systems more transparent and trustworthy: an interview with Ximing Wen

  07 May 2026
Find out more about Ximing's work, experience as a research intern, and what inspired her to study AI.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence