Emerging Role of AI in Simplifying and Democratizing Smart Contract Programming
Summary:
Emin Gün Sirer, founder of Ava Labs, speculates at the Cornell Blockchain Conference that AI could simplify smart contract coding, potentially allowing lawyers to become the primary authors of smart contracts, and enabling people to write them in their everyday language. He also forecasts a future where additional conditions for funds transfer can be set. However, Sirer admits that practical and legal issues need resolution before this can be universally adopted. Views from experts such as Sam Friedman of Chainlink Labs suggest that smart contracts that can handle plain language are almost within reach. Despite the current advancements, they agree crucial improvements still need to happen for AI-written smart contracts to become fully functional and universal.
Emin Gün Sirer, the founder of Ava Labs, asserted that the complexity of smart contract programming is what prevents it from becoming more widespread. He made this assertion at the recent Cornell Blockchain Conference in New York City. Sirer proposed that artificial intelligence (AI) could simplify the process by performing the coding for smart contracts. This could lead to lawyers, rather than coders, becoming the primary authors of smart contracts. In addition, Sirer believes it could enable people to write smart contracts in their everyday language, similar to how they would write a check.
Sirer envisages a future where additional conditions for funds transfer could be set, such as projecting that a certain sum would be given to a person only if they are able to raise a larger amount by a particular date, with the promise of a refund if the condition is not met. This evolution is expected to take place in five to ten years and could drastically increase the number of blockchain users.
Ava Labs has revolutionized the smart contracts domain by developing a unique virtual machine that enables programming in any natural language, as opposed to Solidity, which is the current programming language for smart contracts.
However, practical challenges and legal issues need to be addressed before such "coin-operated agents," as Sirer refers to them, can be universally adopted. The need for precise interpretation of terms and addressing the limitations of AI, such as "hallucinations," still exist.
Fortunately, some interim solutions like requiring consensus from multiple agents, have been proposed to address these issues. Other experts, such as Sam Friedman from Chainlink Labs, point out that smart contracts that employ ordinary language are almost within reach. He cited the example of Council, an AI framework developed by ChainML, which translates plain English instructions into executable code.
Despite these significant advancements, Friedman recognizes that there is still a significant amount of development ahead to fully realize Sirer's vision. For instance, he envisages multiple AI agents working collaboratively throughout the lifecycle of a smart contract, each performing a different role such as defining requirements, writing the contract, testing for quality and security, deploying the contracts, and ongoing maintenance.
Emin Gün Sirer acknowledges that numerous uncertainties remain and emphasized the need for input from individuals with backgrounds in technology, ethics, and humanities. He also believes that lawyers' expertise in contracts could make them the most skilled smart contract programmers in the future. In contrast, non-specialists would most likely be skilled enough to specify basic transactions, resulting in democratic, open platforms accessible to anyone.
In conclusion, Sirer believes that the transformative potential of this novel approach to smart contracts is too significant to overlook.
Published At
5/8/2024 4:15:00 PM
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