AI systems don't have to be controlled by fascist bootlickers. They don't have to be controlled by for-profit tech companies!
Check out our report on the possibility and necessity of an #AICommons: oneproject.org/ai-commons/
AI Commons - One Project
#aicommons
1st post - be as gentle as you feel the need to be :-) https://open.substack.com/pub/blackerthanmirrors/p/exploring-the-ai-commons-questions?r=5v4urt&utm_medium=ios
It was a real pleasure imagining #AICommons as alternatives to extractive AI together with @rumya, Michelle Thorne and Solana Larsen at this year's @republica 🤓
A session co-instigated by Renata Avila from
@okfn and my colleague Deshni Govender from GIZ's FAIR Forward.
🤔 How can we build sustainable, participatory #AICommons?
📺 Review the recording of the session at @republica where @rumya, @danbru8, Michelle Thorne and Solana Larsen discussed why data work matters in shaping alternatives to extractive AI.
✋ #AICommons, one of 15 proposals for #SommetActionAI deliverables, aims to boost citizen participation in AI governance for more inclusive and equitable AI development.
Stay updated by following our #DigitalCommons for Public AI work: https://openfuture.eu/our-work/ai-and-the-commons/
🧵 Open Future participated in a consultation by The Future Society that gathered 200 leading voices on AI governance, and we are happy to see our ideas for #AICommons recognized as key proposals for the Summit.
Check the key findings on #AIGovernance: https://thefuturesociety.org/aiactionsummitconsultationreport/
🗞️"Transparency around the content used to train AI and information about how it was processed can support the legitimate interests of preventing discrimination and respecting cultural diversity." Learn more in this article by Maximilian Gahntz & Zuzanna Warso, published in Tech Policy Press.
https://www.techpolicy.press/how-the-eu-ai-act-can-increase-transparency-around-ai-training-data/
@mozilla and Open Future co-hosted an event that brought together policymakers, industry representatives and civil society.
The goal was to exchange views on what transparency for content used to train AI models should look like.
📄 Read more: https://openfuture.eu/event/from-code-to-conduct-insights-from-a-mozilla-morning/
"The Open Source #AI Definition is an important step in defining the standard of openness in AI development. Still, it should be seen as just one position in a broader debate that needs to bridge positions of AI developers with those of other stakeholders."
– read our new analysis of the Open Source Initiative (OSI)'s definition of open source AI, by @tarkowski and @paulk
"Archival Images of AI", great new project from Sound & Vision.
It starts with a simple premise: you can usage heritage collections to make images of AI that are better than the ever-present illustrations of humanoid robots.
And turns out to be an opportunity to ask serious questions about heritage, the commons, and AI.
https://aixdesign.co/posts/archival-images-of-ai
#aicommons #ai #DigitalHeritage
Dan Cohen and Dave Hansen wrote recently a really good piece on books, libraries and AI training (the piece refers to the paper on Books Data Commons that I co-authored).
They start with a well-known argument about levelling the field: without offering public access to training resources, AI monopolies will benefit from information asymmetries. Google already has access to 40 million scanned books.
They add to this a key point about libraries' public interest stance - and suggest that libraries could actively govern / gatekeep access to books.
This reminds me of the recent paper by Melanie Dulong de Rosnay and Yaniv Benhamou, which for me is groundbreaking - it proposes that license-based approaches to sharing are combined with trusted institutions that offer more fine-grained access governance.
So it's good to see that this line of thinking is getting traction.
https://www.authorsalliance.org/2024/05/13/books-are-big-ais-achilles-heel/
Interesting data from a new edition of the Foundation Model Transaprency Index - collected six months after the initial index was released.
Overall, there's big improvement, with average score jumping from 37 to 58 point (out of a 100). That's a lot!
The interesting fact is that researchers contacted developers and solicited data - interactions count.
More importantly, there is little improvement, and little overall transparency in a category that researchers describe as "upstream": on data, labour and compute that goes into training. And "data access" gets the lowest score of all the parameters.
More at Tech Policy Press: https://www.techpolicy.press/the-foundation-model-transparency-index-what-changed-in-6-months/
The Think7 Italy Summit is happening this week, with the theme “The G7 and the World: Rebuilding Bridges”.
We have been invited to write a brief on “Democratic governance of AI systems and datasets”, which will be presented tomorrow by @tarkowski .
The brief has been a joint effort of three organizations: Open Future Foundation, Centro Politiche Europee and MicroSave Consulting (MSC), with contributions from Renata Avila, Lea Gimpel, and @savi.
https://think7.org/event/t7-italy-summit-the-g7-and-the-world-rebuilding-bridges/
Open Future's newest white paper, authored by @zwarso and myself, addresses the governance of data sets used for #AI training.
Over the past two years, it has become evident that shared datasets are necessary to create a level playing field and support AI solutions in the public interest. Without these shared datasets, companies with vast proprietary data reserves will always have the winning hand.
However, data sharing in the era of AI poses new challenges. Thus, we need to build upon established methods like #opendata refining them and integrating innovative ideas for data governance.
Our white paper proposes that data sets should be governed as commons, shared and responsibly managed collectively. We outline six principles for commons-based governance, complemented by real-life examples of these principles in action.
https://openfuture.eu/publication/commons-based-data-set-governance-for-ai/
I participated yesterday in an expert workshop on Public-Private Partnerships in Global Data Governance, organized by the United Nations University Centre for Policy Research (UNU-CPR) and the International Chamber of Commerce (ICC).
I was also invited to prepare a policy brief that presented how the Public Data Commons model, which we have been advocating for, could be applied at global level for dealing with emergencies, and the broader poly-crisis.
It is exciting to see UNU explore data sharing policies within the context of the policy debate on the UN Global Digital Compact.
Worth noting is also the recent report of the High-Level Advisory Board on Effective Multilateralism, "A Breakthrough for People and Planet". One of the transofrmative shifts, "the just digital transition", includes a recommendation for a global data impact hub.
In my brief, I show how this impact hub could be designed as a Public Data Commons. I also highly recommend other briefs presented at the event, by Alex Novikau, Isabel Rocha de Siqueira, Michael Stampfer and Stefaan Verhulst.
#aicommons #datacommons #datagovernance #ai
You can find the report and all the briefs on the UNU webpage: https://unu.edu/cpr/project/breakthrough-people-and-planet
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