There is a fascinating trend in the Eurovision: once-winning formulas (English lyrics, pop sound, danceability) eventually become the baseline!
https://t.co/oef4Njsc7v
What can Eurovision teach us about learning systems?
New research shows how both organizers and participants adapt over time. It’s “multi-level learning” in action, where feedback shapes behavior across an entire system.
https://t.co/RBoG1hrVYz
Algorithms can bridge large-scale voting with face-to-face deliberation via real world. Key tools: Preference-based Clustering for Deliberation, human-in-the-loop & “Read The Room” visualisations for transparent group decision-making.
https://t.co/ex9pCMTyuf
We can use digital twin simulations to test design choices in deliberative democracy by running “what-if” scenarios in virtual communities to explore better democratic institutions.
https://t.co/xDzm6GxZBY
Co-creating the future: how digital technologies, AI, and open-source innovation are transforming cities into participatory ecosystems for governance and sustainability.
A vision for more democratic, resilient urban futures.
https://t.co/QZ3SSe8odM
How do citizens judge legitimacy in municipal budgeting? This study finds that participatory methods (like the Method of Equal Shares) boost perceived fairness. But process alone can't fix outcome dissatisfaction.
https://t.co/36ZRpTSvNA
The facilitator's paradox in co-creation: boosting group cohesion can unintentionally reduce the diversity that drives innovation. Agent-based modeling uncovers how to strike the right balance.
https://t.co/6scIkpjAVH
Can collective intelligence + participatory budgeting empower everyone? This agent-based modeling shows that naive approaches can harm minorities unless we share knowledge. Open innovation boosts fairness and quality for all.
https://t.co/nQiH6OiGsN
Science and technology are evolving at incredible speed for which we need new ethical architectures, not just patchwork fixes. This paper calls for reshaping institutions to keep up with deep tech transformations
https://t.co/4EzaR8jzzv
Converging technologies (AI, gene editing, neurotech, nano) are collapsing domain boundaries and outpacing siloed regulation. We need converging international governance to keep pace.
https://t.co/pwjy2x16J8
“Human digital twins” might be the key to enabling Society 5.0, but not without serious risks. The new study explores how digital replicas of humans could reshape AI��human interaction, identity, privacy, autonomy, and social power.
https://t.co/DIvYbiFmVb
Trustworthiness of Voting Advice Applications in Europe” finds that these VAAs often fall short on transparency, stakeholder diversity, clear documentation, and disclosing assumptions, even though they can shape electoral behavior.
https://t.co/H3XEqHyABI
Urban Digital Twins and metaverses towards city multiplicities” argues that immersive UDTs may do more than just optimize: they risk deepening social divides by offering multiple, co‑existing urban “realities” tailored to different stakeholders.
https://t.co/ptiCB60oqy
“LLM Voting: Human Choices and AI Collective Decision Making” finds that GPT‑4 / LLaMA‑2’s votes shift with voting methods, ordering, and persona settings and that they may show less diversity & biases vs. humans.
https://t.co/NoUY6MmLcC
"Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting” shows that more expressive vote input and fair aggregation rules boost citizens’ perceptions of legitimacy.
https://t.co/1HKRwS4teI
“On the Legitimacy of Voting Methods” probes how different voting rules shape citizens’ belief in government legitimacy. A timely reminder: the how we vote matters as much as the what.
https://t.co/w8QvrmTOeL
VoteLab is an open‑source, modular, adaptive platform for online collective decision experiments. You can build campaigns, deploy multiple voting methods, and collect insights in real time!
https://t.co/hvNhmTUrBM
We need to re‑think digital twins of cities. Not as industrial machines, but as complex, living, evolving systems. Complexity science gives us the tools to capture how cities interact, adapt, and change over time.
https://t.co/gucedHiON9
What if traffic lights could be voted on?
This study combines voting with deep reinforcement learning to let agents choose traffic signal policies based on their goals.
Turns out, “democratizing traffic” can outperform centralized control.
https://t.co/ImdxUp3lJS