We invite contributors across five broad themes, welcoming perspectives from AI, HCI, and public policy.

Each theme is introduced by an illustrative question, but the questions and topics listed below are intended to serve as starting points rather than limits. We also encourage submissions that go beyond these themes by extending, reframing, or connecting them.

1. Safety and Alignment for Agentic & Physical AI

How do we ensure that increasingly autonomous and embodied AI systems remain safe, aligned, and under meaningful human control, especially when they are adapted or deployed outside the contexts in which they were built?

Possible topics: agentic and embodied AI, retrieval-augmented generation (RAG), multimodal alignment, human-in-the-loop, safety evaluation, LLM vulnerabilities, scalable oversight, uncertainty estimation and calibration, vision-language-action (VLA) models

2. Open Models, Data Sovereignty, and Responsible Deployment

How can open models and local data governance move beyond the defensive goal of "reducing dependence" to become positive conditions for cultural and narrative agency? How can communities build on global models while retaining control over how their data, corpora, and knowledge are collected, interpreted, and used?

Possible topics: Indigenous and community data sovereignty, open-weight and foundation models, local adaptation, data provenance

3. Human Agency & Trustworthy Human-AI Interaction

How can people effectively understand, oversee, and intervene in AI systems without losing their own agency?

Possible topics: human-AI and human-robot interaction, explainable AI(XAI), delegation, mixed-initiative interaction, appropriate reliance, usable transparency and privacy, user control, contestability, human intervention, and failure recovery

4. Inclusive AI for Underserved Communities

How can people from different technical, cultural, and professional backgrounds help build AI that better serves diverse languages, communities, and public needs?

Possible topics: multilingual and low-resource NLP, culturally grounded AI, community-driven data and models, accessibility, civic technologies, news and information integrity, media literacy, and resource-efficient deployment

5. Democratic Resilience and Multi-Stakeholder AI Governance

How can governments, researchers, industry, and the public meaningfully participate in governing AI and holding it accountable? And when "the local community" is itself plural — even internally contested — who has the legitimacy to speak on its behalf?

Possible topics: agile regulatory design, AI ethics, AI law and privacy, public accountability, transparency and explainability, auditable algorithms, due process and contestability, institutional coordination, public-sector deployment, co-governance, and deliberative democracy