Blockchain and artificial intelligence are the most transformative innovations of the 21st century! They are a powerful duo that can solve many critical issues and improve sectors like warehousing. Blockchain ensures that the data is secure and trustworthy, while AI helps us to make better decisions and automate tasks. However, why it is imperative that the artificial intelligence must be built on the blockchain technology? How they can prevent frauds? Are there any practical examples of AI and blockchain working together nowadays?
In this article I will answer these questions by breaking down their complexity and providing concrete examples.
Securing AI with Blockchain
AI systems heavily rely on large datasets for training and decision-making. The blockchain can securely track the history of these datasets by ensuring their integrity. How? Each record on the blockchain is immutable and as a consequence it ensures that no malicious actor can falsify the data that trains AI models. That’s very important because there are sectors like healthcare and finance that demand absolute reliability! Patient records and diagnostic data must remain accurate and tamper-proof in order to avoid misdiagnoses or inappropriate treatments. This is one of the main reason that artificial intelligence without blockchain can be vulnerable and inefficient!
Preventing Bias and Frauds
Blockchain records the origin of data sources, detailing who added the data, when it was added and under what conditions. By verifying data sources, it can reduce bias and thus improve the fairness of AI models. AI decisions often lack of transparency and in order to address this problem, the blockchain can create a decentralized audit trail that records crucial information like inputs, decision paths and outputs.
Let’s now make an example on how AI and blockchain can prevent a fraud. Imagine an e-commerce platform where do you use a virtual credit card. AI monitors all your transactions and flags anything that is unusual. In case the AI finds something suspicious, like an unexpected purchase from a remote location, it consults the blockchain in order to confirm the user’s historical activity. If it doesn’t match the user’s history, then the system blocks it and stops the fraud.
A Real-World Use Case: Walmart
In 2019 Walmart decided to integrate the blockchain in its business in order to achieve a faster and more reliable food traceability, reinforcing so its commitment to food safety. Before this integration, tracking the source of food items was taking days or even weeks because the data was scattered across multiple systems and organizations. This was a critical issue, but the blockchain solved it! How? By digitizing and streamlining the entire food supply chain process. Blockchain provided an instant access to the full history of any product in the supply chain. This drastically reduced the time needed to trace items. Walmart reduced so the time it took to trace mangoes from 7 days to 2.2 seconds!
Blockchain provided the foundation, however Walmart also integrated the AI to further optimize its supply chain. AI analysed blockchain data to detect patterns such as frequent shipment delays or supply bottlenecks, allowing Walmart to address these issues proactively. Also, by tracking metrics like on-time delivery and quality consistency on the blockchain, AI evaluated the supplier performance and flagged underperformers.
But at the end, what were the concrete benefits for Walmart?
Walmart improved food safety, reduced costs and enhanced consumer trust. In case of contamination, Walmart could isolate affected products instantly, protecting so the consumer health. By reducing inefficiencies, recalls and waste, Walmart experienced a significant cost optimization while also improving the overall supply chain resilience. Walmart can now offer a greater transparency to its customer because it can provide them the origin of the products instantly.
In Conclusion
AI, when combined with the blockchain, unlocks several dynamic capabilities: real-time analysis, prediction and optimization. The example about Walmart’s supply chain transformation was a proof of this. AI systems are only as good as the data they are trained on. Incomplete datasets can lead to inaccurate models and as consequence undermining their reliability and fairness. It is so imperative for the AI to rely on the blockchain technology in order to ensure the data integrity!
STAY TUNED! 🔥 & Remember, Your Support Is MASSIVELY Appreciated 💪 Also Don’t Forget To Share It To Your Buddy! 🎅