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To achieve algorithmic fairness we need to bridge AI technology with society and legal systems
Researchers are calling for a more ambitious study of algorithmic fairness that bridges AI technology with social and legal components.
Jan 22
•
Przemyslaw Grabowicz
2
Opportunities and Challenges for the Hotly Debated Digital Services Act
Our upcoming Opinion article in Communications of the ACM discusses the hotly debated Digital Services Act (DSA) — online platform transparency and…
Dec 22, 2025
•
Przemyslaw Grabowicz
and
Francesco Pierri
1
Political Biases on X before the 2025 German Federal Election
We find that the default feed of X shows more content from far-right AfD than from other political parties. Is the feed algorithm of X promoting…
Feb 18, 2025
•
Przemyslaw Grabowicz
3
1
Using biased social polls from X to forecast the US election outcome? We see promise for this novel approach!
Thousands of social polls on X suggest that Trump is leading the election race by a landslide. While many recognize the bias in these polls, there’s an…
Nov 5, 2024
•
Przemyslaw Grabowicz
Fair Machine Learning Post Affirmative Action
There exists a path to fair algorithmic decision-making that differs from affirmative action measures, which have been invalidated by the U.S. Supreme…
Mar 18, 2024
•
Przemyslaw Grabowicz
and
Nicholas Perello
Towards an AI accountability policy
It’s a new day for AI. AI systems can assist us in writing a new web script, decide whether we should worry about that weird spot in an X-ray, and find…
Mar 7, 2024
•
Przemyslaw Grabowicz
and
Nicholas Perello
2
How to train models that do not propagate discrimination?
We develop a rationale for determining which machine learning methods are compliant with legal provisions in terms of discrimination prevention.
Mar 6, 2024
•
Przemyslaw Grabowicz
and
Nicholas Perello
Uncommon Good
(Un)common Good is a blog about responsible techno-social systems such as AI and social media. Common good designs are rare in practice. We want them to become more common.
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