Mark Surman’s Post

Good stuff Mark! Balancing open-source AI with its potential misuse is like giving everyone a lightsaber and hoping they all become Jedi instead of Sith. While openness can drive innovation, it also poses risks like disinformation. History shows openness fuels progress, but with AI, the stakes are higher and the path more treacherous. Creating frameworks and guidelines is just the beginning; enforcing them is the real challenge. Balancing openness and safety is a tightrope walk above a pit of shark with laser beams attached to their heads.

This is an important start to a conversation at the intersection of AI and open source.

Definitely reading this report!

NEW 📢 framework on openness and AI Columbia IGP and Mozilla have been working with #AI leaders for 6 months. Today, the group is publishing a paper that proposes a framework to consider openness in foundation models. Camille François | Ayah Bdeir 

What defines AI systems and corresponding Neural Network Weights (NNWs) as "open-source"? In the maelstrom of regulation emerging around AI systems, significant carve-outs exist for "open-source" or "open-weights" models. But what counts as open-source AI? Some food for thought: https://lnkd.in/ebxY5YyH - TechCrunch article https://lnkd.in/eMiPvhtg - Draft standard definition

The Columbia Convening on Openness and AI Policy Readout highlights the benefits of openness, including: - Enhancing reproducible research and promoting innovation - Creating an open ecosystem of developers and makers - Promoting inclusion through open development culture and models - Facilitating accountability and supporting bias research - Fostering security through widespread scrutiny - Reducing costs and avoiding vendor lock-In - Equipping supervisory authorities with necessary tools - Making training and inference more resource-efficient, reducing environmental harm - Ensuring competition and dynamism - Providing recourse in decision-making #AI4Good Well done!

Open Source AI: OSI Wrestles With a Definition... At PyCon US, Open Source Initiative enlisted help in hammering out a FAQ for its open source AI definition. Some very sticky sticking points remain.

The Open Source Initiative (OSI) is working to establish a definition for "open source AI" through a global effort, addressing challenges in applying traditional open source concepts to AI systems, with a focus on transparency, replicability, and ethical considerations, while acknowledging the complexities of AI components like training data and model weights. https://lnkd.in/e6yCT98T

When it comes to AI, the biggest opponents of its adoption often say that there are too many unknowns. So, let's address one. “Openwashing” – What is it? “Openwashing” is the idea that companies are using the “open source” term disingenuously to make themselves look good. As Sarah Kessler goes on to explain, the debate around this topic first came about thanks to the lack of definition around what open source AI means or is. As such, “organizations that apply the label to their models may be taking very different approaches to openness.” Open Governance is essential to being part of an open source community. #AI #FutureOfWork

VentureBeat has captured our efforts and progress in the Generative AI Commons initiative. This piece provides valuable insights into our commitment to advancing open source AI. Explore our story and impact in the full article: https://hubs.la/Q02dx6Zk0