Alignment Assembly on AI and the Commons
Between 13 of February and 15 of March, Open Future hosted an asynchronous, virtual alignment assembly for the open movement to explore principles and considerations for regulating generative AI.
You can read the report capturing learnings and outcomes from the assembly using the link below.
Alignment Assembly
One of the most pressing questions facing open movement activists, creators, and organizations is how artificial intelligence (AI) will shape and affect the Digital Commons. So much of generative AI is built on the digital infrastructure of the commons and uses the vast quantity of images, text, video, and rich data resources of the internet. Organizations train their models with trillions of tokens from publicly available datasets like CommonCrawl, GitHub open source projects, Wikipedia, and ArXiV.
Access to the Commons has enabled incredible innovations while creating the conditions for the concentration of power in entities that are able to amass the immense energy and data needed to train a generative AI. Community consultations at conferences like Mozfest, RightsCon, Creative Commons Summit, and Wikimania have also revealed concerns about transparency, bias, fairness, and attribution in AI.
We hope to reach participants spread across different fields of open and coming from different regions of the world. We are organizing the assembly in partnership with Creative Commons and Fundación Karisma.
We want to bring to the conversation the perspectives of:
- Activists and experts, including digital rights advocates, legal experts
- Stewards: people from organizations that steward collections that are part of the Digital Commons such as Wikimedia, Open Access repositories, and heritage collections
- Creators: people who create works that form part of the Digital Commons, broadly: not only visual artists and musicians but also researchers who do open science or open source AI programmers
We are using the process of an alignment assembly, an experiment in collective deliberation and decision-making. This model is pioneered by the Collective Intelligence Project (CIP), led by Divya Siddarth and Saffron Huang. The model has been used by OpenAI, Anthropic, and the government of Taiwan.
You can sign up to take part in the process by registering your interest here (we will only use the contact information to invite you to the assembly and to provide updates and delete it once the assembly process is complete).
What does participation look like
Participation in the assembly involves answering questions in an interactive survey, and adding your own questions for other participants.
- Each registered participant receives a link to the pol.is platform, the emails with links will be sent to registered participants on ongoing basis.
- Once you have received the link, you can visit the pol.is platform and start voting on the initial set of questions. The system will show you a live overview of how participants are voting
- You are also able to submit statements for other people to vote on. These will help to further explore the topic.
You can join just once and provide answers to the questions, or come back and answer or add additional questions. You can sign up to receive notifications when new questions are added.
Desired outcomes
The Alignment Assembly on AI and the Commons builds on work from Creative Commons’s summit AI and the Commons in October, where Open Future and Creative Commons hosted a workshop on generative AI and its impact on the commons. The group agreed and released seven principles for regulating generative AI, and those principles can be found here.
We treat the principles as a starting point. We are using the assembly methodology and the pol.is a tool to understand where there is consensus and which principles generate controversy. In particular, how much alignment there is between the perspectives of activists, creators, and stewards of the commons.
At the end of the process, we will produce a report with the outcomes of the assembly and a proposal for a refined set of principles. As the policy debate about the commons and AI develops, we hope the assembly will provide insights into better regulation of generative AI.
