AI Needs Data Transparency: Web3 Startup Space and Time Offers Solution

The Need for Verifiable Data in the Age of AI Manipulation

As artificial intelligence becomes more prevalent and internet content becomes easier to manipulate, there is an increasing need to ensure that data and brands are verifiable, according to Scott Dykstra, CTO and co-founder of Space and Time, who spoke on The Zero Byte’s Chain Reaction podcast.

The FTX Collapse: A Lesson in Brand Trust Manipulation

Dykstra highlighted the recent collapse of the crypto exchange FTX as an example of how an organization with brand trust can manipulate its records internally and mislead investors. He compared this to querying a database for financial records but manipulating the data within their own system.

The Incentive for Data Manipulation Across Industries

The issue of data manipulation extends beyond the crypto industry and into other sectors as well. Dykstra noted that there is often an incentive for financial institutions and other organizations to manipulate their records, prices, books, and finances, making the problem more widespread and concerning.

Zero-Knowledge Proofs: A Solution for Data Verification

Dykstra believes that the best solution to this problem is through the use of zero-knowledge proofs (ZK proofs), which are cryptographic actions that prove something about a piece of information without revealing the original data itself. ZK proofs work by having a prover and a verifier confirm that a statement is true without conveying any additional information beyond its correctness.

Space and Time: A Verifiable Computing Layer for Web3

Space and Time aims to provide a verifiable computing layer for web3 by indexing data both off-chain and on-chain. The startup has already indexed data from major blockchains such as Ethereum, Bitcoin, Polygon, Sui, Avalanche, Sei, and Aptos, with plans to support more chains in the future to power the advancement of AI and blockchain technology.

The Concern of Unverifiable AI Data

Dykstra expressed concern about the current lack of verifiability in AI data, particularly in the context of large language models (LLMs). While teams are working on developing ZK proofs for machine learning and LLMs, the process can take years, leaving room for model operators to tamper with the system in problematic ways.

The Need for a Decentralized, Globally Accessible Database

To address these issues, Dykstra emphasized the need for a decentralized, globally accessible database that can be created through blockchains. Such a database must be readily available, uncensorable, and owned and operated by the community rather than a single monopoly.

It has to be decentralized, it’s going to have to be on-chain, there’s no way around it.

This story was inspired by an episode of The Zero Byte’s podcast Chain Reaction. Subscribe to Chain Reaction on Apple Podcasts, Spotify, or your favorite pod platform to hear more stories and tips from the entrepreneurs building today’s most innovative companies.

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