GIP-63: Should GnosisDAO award a Grant to Algovera to develop a DAO framework for Decentralized AI Teams?

Simple Summary Algovera is requesting a grant of $50,000 to develop a DAO framework (on top of Gnosis smart contracts) for decentralized AI teams. This will involve building a Proof of Concept for publishing and co-owning AI assets in a trustless manner, receiving profits generated by assets to the treasury, and sharing profits generated with team members.

Algovera Algovera is a community of independent AI teams developing user-centric Web3 AI applications. We’re building an AI creator platform where teams and their community can keep ownership of and monetize their creations. We provide support to teams including funding, community events/workshops and our decentralized AI framework (DAID) provides guidance in how to build a decentralized AI DAO that is based on a vision of cooperation, sustainability and ethics. Algovera Grants 2 has funded 28 independent AI teams (called Squads) to date. We also train squads to use our decentralized AI infrastructure, which consists of decentralized storage, compute and marketplace (developed through grants from Ocean Protocol, 12+ OceanDAO grants to date and 1 Ocean Shipyard grant, and 1 Filecoin grant).

Abstract DAO tooling can help to onboard AI developers to Web3, and improve coordination and governance within distributed AI teams. We have been setting up Squads that we fund within DAOs (currently DAOhaus) and have run into a number of problems. It is not possible for AI squads to publish and co-own IP related to data, algorithms and apps in a trustless manner, and there are no suitable tools for sharing profits generated by assets. Furthermore, existing tools are targeted at generic Web3 users, rather than data and AI teams. A UX study that we conducted showed that ownership, monetization of datasets and AI models are the most important at this time for our squads and communities.

The aims of this project proposal are to (i) build a Proof of Concept for using Gnosis to enable the publishing and co-owning of data and AI assets, as well as sharing of profits generated by assets and (ii) onboarding Algovera Squads to Gnosis and ML teams.

Motivation AI development is currently controlled and owned by large tech companies within the singular vision of human-competition, autonomy and centralization, without consideration for society at large. We experienced this ourselves and would like to change this. We believe that AI is a common good and communities should have ownership. Although there are tools to develop AI models such as Kaggle or Huggingface, it is difficult for AI teams to keep ownership and create sustainable revenue for AI DAO communities.

AI teams have hardly any experience with Web3, Gnosis and DAO frameworks. Through our research and qualitative interviews, we found there is some awareness in the value of decentralized AI specific tools and architecture but most tools do not exist yet. Some of the biggest pain points for AI developers are lack of ownership around what they create in universities and tech companies, and lack of infrastructure for coordinating and monetizing their creations online.

Specification Work Package 1: Proof of Concept to publish data sets and AI models for monetization of marketplaces During this work package, we will implement a Proof of Concept for trustlessly publishing and co-owning IP NFTs for datasets and algorithms through a Gnosis Safe app for AI DAOs, receiving earnings generated by assets into the treasury, and distributing earnings back to the contributors/members of the team. Publishing of the asset will be performed by the multisig, with the transaction being executed after the policy defined by the multisig has been satisfied. The asset will be published with the multisig wallet address as the author and any fees associated with the consumption of the asset will be transferred to the multisig treasury. The final step to the solution is implementing profit-sharing tools to distribute earnings back to the contributors/members of the team.

Overview of goals:

Build a Gnosis Safe app for AI DAOs Publish datasets and algorithms to Algovera/Ocean Marketplace through app Receive earnings from marketplace into the Gnosis treasury Distribute amongst DAO members Documentation and video guide to onboard users Work Package 2: Onboarding of Algovera Squads to Gnosis and decentralized AI strategy awareness and education In this work package, we will run regular Decentralized AI DAO (DAID) workshops to not only develop Web3 awareness e.g. onboard our squads to Gnosis safe and monetization tools but also to expose them to pluralistic strategies of how to develop decentralized AI organizations. We believe that bringing together GnosisDAO and AlgoveraDAO squads would be mutually beneficial to the community.

Current centralized AI systems do not actively consider community ownership or how to integrate gender, racial or sustainability factors in developing AI models. Furthermore, researchers have highlighted the harm of AI models that are benchmarked in human-competition, autonomy and centralization [How AI Fails Us: Divya Siddarth, Glen Weyl et al. 2021]. They propose a pluralistic vision of developing AI models that complement, cooperate and support society rather than compete with humans.

This is why we have developed a Decentralized AI DAO framework 2 (DAID) which accelerates our squads with technical tools and strategies that are rooted in interdisciplinary team work, human-centered design, ethics, sustainability and community commercial models.

Our goal is to host 2x interdisciplinary workshops with members of the GnosisDAO, Ocean Protocol, IPFS and Algovera communities for six months, create 6 videos and 5 tutorials to onboard our Squads to Gnosis, and to foster interdisciplinary teams to push towards the development of AI datasets and models for Web3 projects and DAOs.

DAID consists of 4 key areas:

Primary - Design Thinking: who is the user and who is impacted by my AI model?

Community Value Generators: How to achieve sustainable ethical, environmental and commercial value creation.

Decentralized AI activities: from data sourcing, storage, training, deploy to publishing AI models to market places.

DAO activities: covers how to set up a DAO, governance, proposals, treasury management and member protection and monetization of data sets and AI models

Implementation The implementations must be completed before any GIP is given status “Final”, but it need not be completed before the GIP is accepted.