Nick Szabo, a computer scientist and cryptographer, first introduced the term “smart contracts” almost twenty years ago. His example of an early smart contract is a vending machine. In the purest definition, vending machines are a smart contract as it removes static documents that require human management. The machine drives the transaction between the two parties and actively monitors and triggers the event once the condition is met. The buyer fulfills their conditions when they insert the money into the machine. The machine automatically honors its side of the unwritten agreement when it delivers the snack.
Since its first introduction, smart contracts have evolved to perform complex tasks using blockchain technology; however, as we previously discussed, smart contracts do have limitations. There’s a lack of legal structure, it’s difficult to code smart contracts without the technical know-how, and there’s a lack of integrations. Additionally, they cannot use past data to create future contracts that are more effective, secure, and easier to use.
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Many of these limitations can be overcome when enabling smart contracts with artificial intelligence. “Since smart contracts are really just a form of automation, AI can play an important role here. To start, we’re going to see a lot of AI applied to auditing these contracts—confirming code and the terms of contracts. Eventually, though, AI will be writing smart contracts, which should help alleviate the problem of human error in creating these programs,” says Ben Lamm, co-founder of AI solutions agency Hypergiant.
Unlike ordinary smart contracts, AI can be used to predict outcomes of agreements. For example, AI can analyze past contracts to determine the best types of language and clauses to use in future contracts in order to secure a successful agreement. It can also identify variables that parties previously did not consider and incorporate into other contracts moving forward.
Because of its ability to analyze past contacts and predict outcomes, AI essentially acts as an agent to negotiate and execute the contract based on the agreed upon terms of both parties. Experts recommend including a severability clause and a binding dispute resolution provision in the contract between the two parties. Courts have routinely upheld these clauses, and the Federal Arbitration Act and the New York convention is well known to permit international enforcement.
To translate input into complex smart contract code structures and execute the terms of the agreement, AI uses belief-desire-intention models (BDIs). Additionally, when the AI agent creates a natural language version of the contract, parties can typically present this document in court.
Security and Reliability
“Security is one of the main advantages of smart contracts, for companies and individuals. Rather than putting one’s trust in a centralized authority or to fulfill the terms of a contract, smart contracts act as a neutral ‘third party’ that activates once both parties have met agreed-upon conditions,” says Lamm.
Before creating a new contract, AI can determine any loopholes in the code of previous contracts and standardize the process of writing codes for the future—preventing any unmet conditions or missed tasks. Lamm notes, “What’s more, because these contracts are immutable, they protect against bad actors and attempts to destroy contracts, forge contracts, or retroactively alter their terms.”
During the execution of codes, dynamic security checks are carried out in the virtual machine for smart contracts. After the contract is executed, AI can perform an audit to ensure no errors occurred and the results are within a reliable range.
Ease of Use
Lamm says, “The user experience is potentially the valuable element of smart contracts for businesses, providing that we can reach a critical mass of trust and adoption, which I believe we will. The ideal user experience comes down to an interface that clearly lays out terms and conditions for users with minimal legalese.”
If using AI-enabled smart contracts, the parties do not need to negotiate the terms. The AI agent will negotiate on their behalf using a game-type algorithm with parameters for gap fillers, such as price or quality ranges that can be adjusted dynamically.
The AI agent may use search, or even supervised or unsupervised learning techniques to mine data for the best price to quality ratios over a specific time frame, and may trigger the purchase at an optimal time in the future that maximizes the price to quality ratio. “Because so much of contracts is bogged down in the details of repercussions should contract obligations not be met, we can ideally cut through a lot of that bureaucracy. If conditions are not fulfilled, then payment or whatever response was needed will simply not go into effect,” states Lamm.
Together, AI and blockchain facilitate more complex agreements, expedite the negotiation and execution process, and increase the efficiency of the contract. The practice has a ways to go before its widely accepted and used, but most experts agree smart contracts are the future of B2B commerce.
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Note: This article should not be considered as legal advice.