Jointly authored by Divya Siddarth, Matthew Prewitt,and Glen Weyl, this paper provides a framework for thinking beyond the traditional economic approach of public vs private goods. The paper argues for funding mechanisms that take into account “supermodular” goods, which encompass everything under the familiar umbrella of “public goods”, but also include private or excludable systems that become more effective when provided to more people.

Our roadmap outlines concrete steps that can be taken in 2024 to build a more democratic AI ecosystem that is adaptive, accountable, processes decentralized information, provides public goods, and safeguards human wellbeing. We describe what the ecosystem could build, research, advocate for, and fund in 2024 to democratize AI.

This report details a public input process on AI development conducted by with OpenAI as a “committed audience”. This work is part of the broader CIP Alignment Assemblies agenda, through which we are conducting a series of processes that connect public input to AI development and deployment decisions, with the goal of building an AI future that is directed towards people’s benefit, using their input.

It is fiendishly difficult to get lots of people to make decisions and work together both non-hierarchically and effectively. Because blockchain technology enables decentralized consensus at scale, the implications for human decision-making and coordination are immensely promising; if we can use it to scale decentralized governance, this could be a paradigm shift in how most of us live and work together.