Vana

• Vana is a Layer 1 that lets people pool personal data into user-owned DataDAOs and license it collectively.

• Contributors retain ownership and share in revenue when their data trains AI models.

• VANA is the network token.

• Supply allocated across community, ecosystem and investors.

• Used for network fees, staking and DataDAO participation.

Pros:

• Collective bargaining over data is a genuinely different approach from individual consent.

• Directly relevant as AI training data becomes contested and litigated.

• Working DataDAOs with real contributor bases rather than only a framework.

Cons:

• AI labs can generally obtain data without paying, which limits pricing power.

• Data licensing legality varies by jurisdiction and by how the data was originally collected.

• Verifying that contributed data is genuine and not duplicated is an unsolved problem.

• Exposure to user-owned data infrastructure as AI training data becomes contested.

• Collective structure gives contributors leverage individuals lack.

• Weigh whether buyers will pay for data they can otherwise take.

• Data pooled into collectively owned entities that license as a bloc, giving contributors negotiating power no individual has.

• Individuals have data worth something in aggregate and nothing individually, so they cannot negotiate.

• Pooling it into a collective creates a counterparty large enough for a buyer to deal with.

• Founded by Anna Kazlauskas and Art Abal, originating from research at MIT.

• Backed by Paradigm, Polychain and Coinbase Ventures.

• No public ICO. Distributed through airdrop and ecosystem allocations in December 2024.

• AI labs can source comparable data without paying.

• Data provenance and legality vary by original collection method.

• Sybil resistance in data contribution is unsolved.

• Regulatory treatment of personal data licensing differs sharply by jurisdiction.