Carina Ines Hausladen PRO
I am an Assistant Professor for Computational Social Science at the University of Konstanz, Germany.
Pour cette édition 2025,
261 idées sont soumises au vote
rudimentary sorting capabilities
rudimentary sorting capabilities
= built-in bias
Voters come for their friend's backyard bench idea, vote yes, and leave.
Voters come for their friend's backyard bench idea, vote yes, and leave.
is widespread in civic participation.
Could this be also usefull for PB?
1. Quantify the extent of harm done through the bad interface/sorting.
2. Properly simulate the effects of FairFeed.
3. Test FairFeed in a controlled online/lab experiment.
MünchenBudget 2025 and 2026
We used the Munich data (1k proposals, 7k voters etc.) & academic literature (which distributions for attention decay) to calibrate the model.
We have a first version....
... but the UI looks bad. You could improve it.
Additional interesting questions
- is 2:1 the perfect ration? What does it depend on?
- How to best calibrate the recommender itself?
Vast range of choices
Ideally,
many citizens browse many projects.
Unviable or poorly planned initiatives must be effectively filtered out.
Ideally,
many citizens browse many projects.
Unviable or poorly planned initiatives must be effectively filtered out.
Ideally,
many citizens browse many projects.
positive feedback only
rudimentary sorting capabilities
positive feedback only
rudimentary sorting capabilities
Can we build recommender systems for second stage PB?
😐 Not interested
YouTube’s, TikToK's: ``Not interested"
Facebook’s, Instagram: ``Show less",``Hide post",
Netflix’s Thumbs down
Tinder: swipe left
👎 Bad Content
Reddit's, Stack Overflow, Hacker News
🚩 Policy Violation
Facebook: “Hate Speech,” “False Information,”
Unviable or poorly planned initiatives must be effectively filtered out.
Contested Space
Vast range of choices
Ideally,
many citizens browse many projects.
By Carina Ines Hausladen
I am an Assistant Professor for Computational Social Science at the University of Konstanz, Germany.