Within the generative AI boom, data is the brand new oil. So why shouldn’t you have the ability to sell your individual?
From big tech firms to startups, AI makers are licensing e-books, images, videos, audio and more from data brokers, all within the pursuit of coaching up more capable (and more legally defensible) AI-powered products. Shutterstock has deals with Meta, Google, Amazon and Apple to produce tens of millions of images for model training, while OpenAI has signed agreements with several news organizations to coach its models on news archives.
In lots of cases, the person creators and owners of that data haven’t seen a dime of the money changing hands. A startup called Vana wants to alter that.
Anna Kazlauskas and Art Abal, who met in a category on the MIT Media Lab focused on constructing tech for emerging markets, co-founded Vana in 2021. Prior to Vana, Kazlauskas studied computer science and economics at MIT, eventually leaving to launch a fintech automation startup, Iambiq, out of Y Combinator. Abal, a company lawyer by training and education, was an associate at The Cadmus Group, a Boston-based consulting firm, before heading up impact sourcing at data annotation company Appen.
With Vana, Kazlauskas and Abal got down to construct a platform that lets users “pool” their data — including chats, speech recordings and photos — into data sets that may then be used for generative AI model training. In addition they wish to create more personalized experiences — as an illustration, each day motivational voicemail based in your wellness goals, or an art-generating app that understands your style preferences — by fine-tuning public models on that data.
“Vana’s infrastructure in effect creates a user-owned data treasury,” Kazlauskas told TechCrunch. “It does this by allowing users to aggregate their personal data in a non-custodial way … Vana allows users to own AI models and use their data across AI applications.”
Here’s how Vana pitches its platform and API to developers:
The Vana API connects a user’s cross-platform personal data … to can help you personalize your application. Your app gains easy access to a user’s personalized AI model or underlying data, simplifying onboarding and eliminating compute cost concerns … We expect users should have the ability to bring their personal data from walled gardens, like Instagram, Facebook and Google, to your application, so you’ll be able to create amazing personalized experience from the very first time a user interacts along with your consumer AI application.
Creating an account with Vana is fairly easy. After confirming your email, you’ll be able to attach data to a digital avatar (like selfies, an outline of yourself and voice recordings) and explore apps built using Vana’s platform and data sets. The app selection ranges from ChatGPT-style chatbots and interactive storybooks to a Hinge profile generator.
Image Credits: Vana
Now why, you would possibly ask — on this age of increased data privacy awareness and ransomware attacks — would someone ever volunteer their personal info to an anonymous startup, much less a venture-backed one? (Vana has raised $20 million so far from Paradigm, Polychain Capital and other backers.) Can any profit-driven company really be trusted to not abuse or mishandle any monetizable data it gets its hands on?
Image Credits: Vana
In response to that query, Kazlauskas stressed that the entire point of Vana is for users to “reclaim control over their data,” noting that Vana users have the choice to self-host their data moderately than store it on Vana’s servers and control how their data’s shared with apps and developers. She also argued that, because Vana makes money by charging users a monthly subscription (starting at $3.99) and levying a “data transaction” fee on devs (e.g. for transferring data sets for AI model training), the corporate is disincentivized to use users and the troves of private data they convey with them.
“We would like to create models owned and governed users who all contribute their data,” Kazlauskas said, “and permit users to bring their data and models with them to any application.”
Now, while Vana isn’t selling users’ data to corporations for generative AI model training (or so it claims), it desires to allow users to do that themselves in the event that they select — starting with their Reddit posts.
This month, Vana launched what it’s calling the Reddit Data DAO (Digital Autonomous Organization), a program that pools multiple users’ Reddit data (including their karma and post history) and lets them to make your mind up together how that combined data is used. After joining with a Reddit account, submitting a request to Reddit for his or her data and uploading that data to the DAO, users gain the suitable to vote alongside other members of the DAO on decisions like licensing the combined data to generative AI corporations for a shared profit.
It’s a solution of sorts to Reddit’s recent moves to commercialize data on its platform.
Reddit previously didn’t gate access to posts and communities for generative AI training purposes. But it surely reversed course late last yr, ahead of its IPO. For the reason that policy change, Reddit has raked in over $203 million in licensing fees from corporations including Google.
“The broad idea [with the DAO is] to free user data from the key platforms that seek to hoard and monetize it,” Kazlauskas said. “It is a first and is a component of our push to assist people pool their data into user-owned data sets for training AI models.”
Unsurprisingly, Reddit — which isn’t working with Vana in any official capability — isn’t pleased concerning the DAO.
Reddit banned Vana’s subreddit dedicated to discussion concerning the DAO. And a Reddit spokesperson accused Vana of “exploiting” its data export system, which is designed to comply with data privacy regulations just like the GDPR and California Consumer Privacy Act.
“Our data arrangements allow us to place guardrails on such entities, even on public information,” the spokesperson told TechCrunch. “Reddit doesn’t share non-public, personal data with industrial enterprises, and when Redditors request an export of their data from us, they receive non-public personal data back from us in accordance with applicable laws. Direct partnerships between Reddit and vetted organizations, with clear terms and accountability, matters, and these partnerships and agreements prevent misuse and abuse of individuals’s data.”
But does Reddit have any real reason to be concerned?
Kazlauskas envisions the DAO growing to the purpose where it impacts the quantity Reddit can charge customers for its data. That’s a protracted ways off, assuming it ever happens; the DAO has just over 141,000 members, a tiny fraction of Reddit’s 73-million-strong user base. And a few of those members might be bots or duplicate accounts.
Then there’s the matter of find out how to fairly distribute payments that the DAO might receive from data buyers.
Currently, the DAO awards “tokens” — cryptocurrency — to users corresponding to their Reddit karma. But karma may not be the very best measure of quality contributions to the information set — particularly in smaller Reddit communities with fewer opportunities to earn it.
Kazlauskas floats the concept that members of the DAO could decide to share their cross-platform and demographic data, making the DAO potentially more priceless and incentivizing sign-ups. But that might also require users to put much more trust in Vana to treat their sensitive data responsibly.
Personally, I don’t see Vana’s DAO reaching critical mass. The roadblocks standing in the way in which are far too many. I do think, nevertheless, that it won’t be the last grassroots try and assert control over the information increasingly getting used to coach generative AI models.
Startups like Spawning are working on ways to permit creators to impose rules guiding how their data is used for training while vendors like Getty Images, Shutterstock and Adobe proceed to experiment with compensation schemes. But nobody’s cracked the code yet. Can it even be cracked? Given the cutthroat nature of the generative AI industry, it’s definitely a tall order. But perhaps someone will discover a way — or policymakers will force one.
