Generative AI Smart Contract Analysis
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Solution Overview
Problem
Existing smart contract systems on blockchain platforms are challenging for consumers and industry participants to understand due to their code-based nature, leading to confusion and missing contractual terms. Additionally, off-chain contractual dependencies are often not transparent, even to programmers.
Innovation Solution
The use of generative artificial intelligence (AI) to automate the analysis of smart contracts by converting their code into natural language content. This includes training a language model to generate summaries, itemizations of conditions, missing contract terms, warnings about off-chain conditions, and suggested contract language based on the smart contract code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If smart contracts are implemented as code on blockchain, then transaction transparency and security are improved, but consumer understanding and contractual clarity deteriorate
Solution Approach 1:
The patent introduces an intermediary system that translates smart contract code into natural language explanations. This mediator layer allows consumers to understand contract terms without compromising the underlying code-based security and transparency of blockchain transactions.
Solution Approach 2:
The patent segments the understanding of smart contracts into multiple layers: the underlying code layer for security and execution, and a natural language explanation layer for consumer comprehension. This segmentation allows each layer to serve its specific function without compromising the other.
2Productivity
If smart contract code is used, then automated execution is improved, but detection of off-chain dependencies deteriorates
Solution Approach 1:
The patent performs preliminary analysis of smart contract code to identify off-chain dependencies before execution. By detecting these dependencies in advance, the system can provide warnings and explanations to consumers about external factors that may affect contract execution, while maintaining automated execution capabilities.
Solution Approach 2:
The patent implements feedback mechanisms that analyze smart contract code and provide information about off-chain dependencies. This feedback loop allows the system to maintain automated execution while improving transparency about external dependencies through natural language explanations and warnings.
3Loss of information
If manual analysis of smart contracts is performed, then contractual term identification is improved, but computational resource consumption deteriorates
Solution Approach 1:
The patent implements self-service mechanisms where the smart contract analysis system automatically identifies and explains contractual terms without requiring extensive manual intervention. The system serves itself by using AI models to translate and explain code, reducing the need for human computational effort while maintaining comprehensive term identification.
Solution Approach 2:
The patent replaces manual mechanical analysis of smart contracts with automated AI-based language models. This substitution reduces computational resource consumption by using efficient natural language generation techniques rather than resource-intensive manual code analysis methods.
Data Source
AI summary
Methods and systems are provided for using generative AI for automated analysis of smart contracts on blockchain. In embodiments described herein, smart contract code for a smart contract is accessed in blockchain via a retriever component. The smart contract code includes a condition of the smart contract in a programming language format. A language model generates natural language content based on the smart contract code. The natural language content is then displayed.