# Bridging Deliberative Democracy and Deployment of Societal-Scale Technology

arXiv: https://arxiv.org/abs/2303.10831 · HTML: https://mlsanity.com/paper/2303.10831/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Mar 2023.

## Built on by (most cited first, 1 of 1)

- [Culturally-Grounded Governance for Multilingual Language Models: Rights, Data Boundaries, and Accountable AI Design](https://mlsanity.com/paper/2602.00497/) (2026)

## Abstract (arXiv)

This position paper encourages the Human-Computer Interaction (HCI) community to focus on designing deliberative processes to inform and coordinate technology and policy design for large language models (LLMs) -- a `societal-scale technology'. First, I propose a definition for societal-scale technology and locate LLMs within this definition. Next, I argue that existing processes to ensure the safety of LLMs are insufficient and do not give the systems democratic legitimacy. Instead, we require processes of deliberation amongst users and other stakeholders on questions about the safety of outputs and deployment contexts. This shift in AI safety research and practice will require the design of corporate and public policies that determine how to enact deliberation and the design of interfaces and technical features to translate the outcomes of deliberation into technical development processes. To conclude, I propose roles for the HCI community to ensure deliberative processes inform technology and policy design for LLMs and other societal-scale technology.