Events

AI Commons began not as an organization but as a conversation about whether AI would amplify inequalities or become shared infrastructure.

For nearly a decade, AI Commons participated in and helped shape the AI for Good Summit series one of the earliest sustained convenings dedicated to what AI should be for.

An early framework articulating the distinction between AI as a competitive capability and AI as shared infrastructure.

A Data Commons concept proposed as a key enabler for SDG-oriented AI projects, spearheaded by XPRIZE and Ocean Protocol, with Berkman Klein contributing the framework.

Among the first attempts to design a licensing architecture for AI systems built on shared knowledge, using smart contracts to make contribution and consent traceable. A precursor to AMPL.

AI Commons presented 'From Data Commons to AI Commons' exploring the shift from shared data repositories to a full AI commons including compute, algorithms, and talent.

Co-organized with MILA at ICLR 2019, exploring AI for social good at the intersection of academic ML research and applied ethics.

Date: May 2019 Type: Event Context: AI for Good Global Summit · Geneva

AI Commons hosted a workshop on the Global Data Commons and leveraging AI for the Sustainable Development Goals.

A multi-stakeholder initiative to establish shared principles around data governance in the age of AI.

Co-authored by Amir Banifatemi, Nicolas Miailhe, R. Buse Çetin, and Konstantinos Karchalios.

Sustained engagement with GPAI on building institutional conditions for responsible AI.

Generative AI has the potential to transform industries and society, but responsible design and collaboration among stakeholders are crucial. The Responsible Generative AI Leadership Summit gathers top leaders from…

AI Commons contributed to the Hiroshima AI Process, focusing on obligations arising from training systems on humanity's shared intellectual inheritance.

Date: 2023 Type: Publication Context: World Economic Forum

The reframing: AI is an ecosystem without a coordination layer.

Two days with MIT Media Lab, Creative Commons, EleutherAI, IBM, Wikimedia Foundation, Common Crawl, and OSI. First time the full commons stack was articulated as a single interoperable layer.

Co-hosted with the Interdependence Declaration. Surfaced the framing of AI as civilizational infrastructure requiring shared standards, accountability, and incentives.

Co-created with Khoj Studios. Part exhibition, part working commons, part salon. A prototype for how the commons shows up in the world.

AI Commons curated a full-day funders track. Core insight: the problem is not a lack of capital but a lack of coordination.

Hosted by Mei Lin Fung (Vice Chair, UN AI for Good Impact Steering Committee).

Full enforcement of the EU AI Act. Provenance requirements, transparency obligations, and high-risk system standards move from regulation to compliance.

Driven by the rapid progress in Artificial Intelligence (AI) research, intelligent machines are gaining the ability to learn, improve and make calculated decisions in ways that will enable them to perform tasks…

This workshop a part of the Project Resilience was planned in conjonction with the AI for Good summit to foster discussions around the development of a collaborative portal and platform to address global…

Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy