Can AI help us disagree better?

Kari Jaaskelainen

12 Jan 2026 — 1 min read

Can AI help us disagree better?

Democracy thrives when diverse voices are heard, but at scale, participation, political equality, and meaningful discussion often pull against each other.

New research asks whether AI mediators powered by large language models can ease this trilemma. Building on a recent tool that helped people with different views find common ground, the authors outline what AI could do — and what could go wrong.

Scale participation: guide more people through constructive, structured dialogue.
Support equality: fairly allocate speaking time and summarize every voice.
Enrich deliberation: surface trusted information and highlight areas of agreement and disagreement.

But challenges remain: bias and unequal performance, hallucinated facts, opaque reasoning, over-smoothing legitimate conflict, and risks of manipulation. The authors call for rigorous testing, transparency, human oversight, and community governance before deploying AI in civic processes.

Bottom line: AI could augment — not replace — human deliberation. Read more: https://arxiv.org/abs/2601.05904v1

Paper: https://arxiv.org/abs/2601.05904v1

Register: https://www.AiFeta.com

AI Democracy Deliberation CivicTech PublicPolicy GovTech LLM Mediation

Meet GRACE: a moral governor for safer, more transparent AI

AI agents are getting powerful—so how do we make sure they do the right thing, not just the effective thing? Meet GRACE, a reason-based moral governor that keeps AI behavior aligned with human norms by separating moral reasoning from goal-driven decision-making. * Moral Module: uses deontic logic and explicit reasons

Why some fine-tuned LLMs miss phishing—and how to fix it

Not all fine-tuned LLMs spot phishing equally. A new study tests Llama 3.1 8B, Gemma 2 9B, and Mistral on high-stakes phishing detection—and uses SHAP and mechanistic interpretability to reveal why models do (or don’t) generalize. * Architecture × data diversity matters: Gemma 2 9B hits state-of-the-art performance (F1

AI that explains itself—by following the science

AI that explains itself—by following the science Black-box AI can be powerful, but it often can’t tell us why it made a decision. Concept Bottleneck Models (CBMs) try to fix that by predicting human-understandable concepts first, then the final answer. The catch: standard CBMs ignore domain-specific cause-and-effect and

Meet GenomAgent: A Team of AI Specialists for Smarter Genomics Q&A

TL;DR: Finding reliable answers in genomics is hard. GenomAgent turns one big AI into a coordinating team of specialists—and beats the current leader by 12% on a key benchmark. Genomic facts live across many databases. Standard chatbots struggle because they can’t flexibly query those sources. GeneGPT added