If Smart Contracts Are Already ‘Smart’, Why the Need for AI?

AI is often described as today’s ‘internet moment’ from the nineties. People can outsource mundane tasks in their daily lives to algorithms, while businesses can save money and time. AI has also spread into emerging technologies such as blockchain and Web3.

Smart contracts are a critical part of blockchain technology. They are self-executing contracts with agreement terms written directly into code. In practice, they are digital agreements that enforce themselves when pre-determined conditions are met, without middleman intervention or tampering. 

This automated system operates on a blockchain. That makes its activity transparent and tamper-proof.

But if smart contracts already provide automation and transparency, why does blockchain need AI as its partner in crime? 

The Limitations of ‘Smart’ Contracts

Rigidity is one limitation. Smart contracts operate exactly as coded, so even a small error or vulnerability can cause significant problems.

Traditional black-and-white contracts can sometimes be clarified through negotiation or legal interpretation. Smart contracts follow their code to the letter, which can produce unintended consequences. 

Consider a DeFi lending platform that uses smart contracts to automate loans between users. If a borrower defaults after a sudden job loss, the smart contract cannot independently restructure the loan or offer a grace period.

Smart contracts use cryptographic principles to improve security, but they are not immune to hacking. Because blockchains are decentralised, changing a smart contract after deployment can be extremely difficult when new vulnerabilities are found.

In August 2021, token swapping platform Poly Network suffered an audacious heist. Hackers stole more than $600 million worth of cryptocurrency before returning it 48 hours later. 

Addressing Limitations: How AI Overcomes Smart Contract Limitations

Smart contracts are powerful, but they have limitations such as rigidity and immutability after deployment. AI addresses these issues with machine learning algorithms that add flexibility and adaptability. It can improve decision-making and reduce manual intervention. 

AI can also improve transparency, security, and reliability by monitoring transactions in real-time and making oracle data more accurate. 

Similarly, aelf, a layer 1 AI blockchain, addressed some of these challenges by adding AI technologies to its architecture. The architecture includes a mainchain, customisable sidechains, and a ZK-Rollup Layer 2 solution for scalability. 

Through partnerships with AI innovators such as AgentLayer and ChainGPT, aelf has enabled smart contracts to move beyond their rigid design. The technology supports development of the next generation of dApps and helps sustain performance across the blockchain network. It can also make intelligent decisions in response to changing conditions.

aelf’s pipeline includes an AI oracle designed to strengthen the connection between the aelf chain and AI-powered dApps. 

Other Cool Benefits of Integrating AI with Smart Contracts

Streamlined Compliance and Regulatory Requirements 

AI integration can simplify compliance and regulatory requirements. 

• Machine learning models can be trained to interpret and apply different compliance rules automatically
• This reduces manual effort and the risk of human error
• It helps smart contracts remain compliant with changing legal standards, especially in the highly regulated financial sector

Upgraded Usability for Developers and Users

AI Natural Language Processing (NLP) can improve usability and support Web3 development. The average person on the street may not have specialised knowledge of coding languages. 

• NLP allows AI systems to understand and interpret human language more effectively, simplifying the creation and management of smart contracts
• This understanding lets developers and users interact with smart contracts more naturally, lowering the barrier to entry and making the technology accessible to a broader audience
• NLP-driven AI can translate complex legal and technical jargon into plain language, improving clarity and reducing misunderstandings

Data Privacy, Made Even More Private 

Discussions about blockchain and smart contracts often focus on transparency. AI can also strengthen data privacy, which is a growing global concern in an interconnected world. 

• AI algorithms can anonymise sensitive information before smart contracts process it. Users benefit from blockchain’s immutable ledger while personal or sensitive data stays confidential.
• AI can assess and encrypt data at different stages of a transaction, adding security in areas such as healthcare or finance
• Transactions stay secure while personal information remains private

Case in Point: AI Smart Contracts in Ride-hailing

Have you used ride-hailing services and wondered why fares seem artificially inflated, even outside peak times?  Drivers may also have to deal with runaway passengers or no-shows. 

Although the concept is more theoretical than tried-and-tested at this point, AI smart contracts could improve the ride-hailing experience for both sides. Here is how a decentralised ride-hailing model could work.

AI Smart Contracts in Ensuring Fair Pricing and Automated Payments

In the traditional ride-hailing model, centralised companies control pricing algorithms and can change surge pricing during peak hours or special events. Riders may feel exploited, while drivers may not receive a fair share of the earnings.

AI smart contracts could address these issues with a decentralised and transparent pricing mechanism.

1. Dynamic Pricing based on Real-Time Data: AI algorithms can analyse factors such as traffic conditions, demand, weather, and driver availability in real-time. They can then determine fair and dynamic ride prices 
2. Manipulation-free Pricing: The smart contract would contain the pricing logic, making it visible and immutable on the blockchain. This would provide transparency and prevent the platform from arbitrarily changing prices.
3. Automated Payments: After a ride ends, the smart contract would automatically process the payment. Drivers and riders would receive their fair share without delays or disputes
4. Dispute Resolution: If disagreements or discrepancies arise, the smart contract could include a dispute resolution mechanism. AI could analyse ride data and provide impartial recommendations

For example, a passenger might be charged unfairly for tolls or a longer-than-usual route. The AI algorithm could review GPS coordinates, distance traveled, and time taken to identify discrepancies and adjust the final fare or refund.

This would give both parties a transparent and unbiased way to resolve the dispute.

Benefits:

• Fairness and Transparency: AI smart contracts would base prices on objective data and algorithms, reducing unfair surge pricing and biased decisions
• Efficiency and Automation: Automated payments and dispute resolution would simplify the process, reduce administrative work, and improve efficiency for drivers and riders
• Trust and Accountability: Immutable smart contracts on the blockchain would create a trustless environment in which all parties could rely on pre-defined rules and logic

Challenges ahead:

• Data Privacy: Ride-hailing platforms using AI must carefully address data privacy. Anonymisation and encryption should protect user data while allowing the AI to function effectively.
• Algorithm Transparency: The AI algorithms used for pricing and decision-making should be transparent and explainable. This would support accountability and help avoid bias
• Community Governance: Decentralised platforms could use community governance to let stakeholders (drivers, riders, developers) participate in decision-making and platform development

In Closing

This decentralised ride-hailing case study shows how AI smart contracts could offer more flexibility than traditional smart contracts. They could respond to specific conditions, choose tailored solutions for disputes, and use accurate data streams. That could matter when driverless taxis become common on public roads.

These capabilities could support more robust, reliable, user-friendly, and intelligent blockchain technologies. The focus must also remain on ethics, security, and transparent processes. Intelligence—whether human or artificial — works best when used responsibly and with foresight. 

*Disclaimer: The information provided on this blog does not constitute investment advice, financial advice, trading advice, or any other form of professional advice. Aelf makes no guarantees or warranties about the accuracy, completeness, or timeliness of the information on this blog. You should not make any investment decisions based solely on the information provided on this blog. You should always consult with a qualified financial or legal advisor before making any investment decisions.

About aelf

aelf, an AI-enhanced Layer 1 blockchain network, uses the C# programming language to support efficiency and scalability across its multi-layered architecture. Founded in 2017 with its global hub in Singapore, aelf is a pioneer in the industry. It leads Asia in developing blockchain with AI integration and modular Layer 2 ZK Rollup technology. The platform is efficient, low-cost, and highly secure, while remaining accessible to developers and end users. In line with its vision, aelf supports innovation across its ecosystem and the adoption of Web3 and AI technology.

For more information about aelf, please refer to our Whitepaper V2.0.

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