AI and blockchain: A match made in heaven or hell

The following is a guest post by Kadan Stadelmann, CTO of Komodo Blockchain.

From AI Models on Bitcoin to AI training data on a layer 2 blockchain, coins linked to AI crypto projects are all the rage in the altcoin universe.

It’s a reflection of broader market conditions. Hot stock Nvidia (NVDA.O) has stolen headlines since last year and put AI on the investing map. 

That stock became the seventh public U.S. company valued at over $1 trillion. By March 2024, it became the world’s third most valuable company after Microsoft and Apple as the market cap eclipsed $2 trillion. Investors yearn for exposure to machine learning technology at a clip that rivals the world’s largest companies.

AI tokens at the time of writing have a market value of $26.4 billion. Last April, that number was a mere $2.7 billion. 

The CoinDesk Indices Computing Index includes AI-linked tokens and has increased more than 165% in the past 12 months. And trading volumes hit an all-time high of $3.8 billion in late February.

Although many investors are chasing price gains, AI-linked crypto tokens provide an opportunity in crypto that is at the same time uncorrelated to crypto. These tokens’ values are arguably more tied to the fate of the AI sector than to crypto.

Investment manager VanEck predicts that AI crypto revenue could reach a whopping $10.2 billion by 2030 on the low end with use cases similar to non-AI crypto projects—reward tokens, physical computation infrastructure, data verification, provenance, and more.

To be sure, the AI blockchain revolution remains in its infancy. How the merger of these two exciting industries plays out is unknown. Bitcoin Maximalists, for instance, believe the entire crypto index could go to zero. 

There is a long list of possible uses for AI tokens. Payments, trading models, machine-generated non-fungible tokens and blockchain-based marketplaces for AI applications to name a few.

Theoretically, blockchain improves the security of protocols with a decentralized and immutable settlement layer.

AI detects risks in real-time and provides an extra layer of security monitoring network activities, analyzing historical and provenance data and asset conditions, discovering anomalies, using predictive analytics to make smart contract conditions more efficient, and analyzing provenance data, asset conditions, and market trends.

Imagine a system where these two novel technologies pull and verify data while managing network loads.

Blockchain could be a public record of AI training. 

AI algorithms improve threat detection and response; blockchain’s immutability of security-related data provides a robust defense against cyber threats paired with a decentralized approach to data management. 

Once the AI-verified information is recorded to the blockchain, it cannot be altered or deleted. 

Nonetheless, the merger of AI and blockchain poses threats.

The United Nations General Assembly adopted March 21, a global artificial intelligence (AI) resolution promoting “safe, secure, and trustworthy” AI development. 

The European Parliament passed March 13 an AI Act to set governance standards for the Union.

Additionally, the European Commission launched a probe into the use of AI.

The Biden administration’s October 2023 executive order notes AI development’s safety and security problems. 

Meanwhile, India introduced AI requirements in March before the national elections.

AI and blockchain, both alone and combined, pose privacy and security risks. Vast amounts of sensitive data could one day depend on the security of AI-blockchain apps, and how these might be secured remains unclear.

AI requires vast amounts of data to learn, predict, and act. The data could become increasingly personal over time, posing a greater risk to privacy. Blockchain can counteract these risks by anonymizing data transactions to protect identity with methods including zero-knowledge proofs and also creating an immutable and often public record. 

Data recorded to a public blockchain can be deleted by nobody, presenting a conflict with privacy norms and laws such as the right to be forgotten. 

The theoretical potential for AI to act on data secured by blockchain without human oversight raises significant questions about consent and privacy. 

In the quest to harness blockchain and AI without dystopia, the world must be guided by ethical principles and safety standards so that these technologies end up serving humanity’s best interests and solving our most pressing needs. 

A collaborative approach among developers, ethicists, and policymakers is needed to delineate clear boundaries for AI behavior and data integrity on blockchain networks. Developers must design innovative solutions to protect privacy and security in the new digital frontier.

The principles of transparency, accountability, and inclusivity ensure that AI and blockchain systems are designed with an understanding of their societal impacts. 

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