Blockchain and artificial intelligence (AI) are two technologies that are already having an impact on our lives and at the same time have the potential to revolutionize numerous industries. But what opportunities and challenges arise from combining the two technologies?
• Combining blockchain and AI offers many advantages
• Numerous possible applications
• Integrating AI into blockchain brings challenges
Blockchain technology, a publicly viewable and shared database in which transaction data is stored, has become increasingly important in recent years. It is considered forgery-proof because every transaction is checked via the decentralized user network and the information is stored in encrypted form.
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Another topic that has caused quite a stir in the recent past is artificial intelligence (AI). The AI chatbot ChatGPT and software that can generate images based on text descriptions have sparked a real AI hype in recent months. Many companies have jumped on the bandwagon and want to benefit from the great potential that the trend topic promises.
But what opportunities and challenges arise when these two important technologies come together?
Combination of blockchain and AI
According to Medium, the integration of blockchain into AI applications can, for example, create “trust in the results and analyzes of AI systems” due to their decentralization and transparency. The blockchain could also serve as the basis for decentralized data marketplaces, from which AI systems that rely on comprehensive and high-quality data could benefit. With the help of blockchain technology, the management and access to training data for AI models can also be improved. In this way, data sources can be verified and their quality monitored, thereby ensuring the transparency and traceability of the data.
In addition, the combination of blockchain and artificial intelligence offers opportunities for the implementation of decentralized AI models. Instead of running the AI models centrally on a server, they could, as Medium reports, “run on different nodes in a blockchain network,” which increases “scalability, reliability and resistance to attacks.” The provision and use of the AI models can be regulated by smart contracts, which makes the ecosystem fair and efficient.
Possible use cases
The combination of artificial intelligence and decentralized blockchain could be used in many different industries – and revolutionize them.
In the area of logistics and supply chains, blockchains offer the possibility of tracing goods back to their origin, while, according to DEV INSIDER, artificial intelligence is advancing, for example, “solutions for automating loading ports, demand and supply analyzes and quality control systems for transported goods.” For example, according to Cryptopolitan, IBM’s Food Trust combines blockchain to track food origins with AI algorithms to predict and manage disruptions in the supply chain.
The integration of blockchain and AI is also likely to be used in the financial sector and especially in fintechs to optimize operations, reports DEV INSIDER. Here, the technologies could be used, for example, for fraud detection, credit risk assessment, account security, regulation and customer relationship management. For example, decentralized financing platforms could use blockchain technology for transparent transactions and use AI algorithms to assess the creditworthiness of borrowers, reports Cryptopolitan. This could streamline credit decisions and prevent fraud.
In addition, the combination of blockchain and artificial intelligence can increase transparency and speed in payment transactions, for example, and at the same time improve the checkout experience for the customer.
In healthcare, for example, according to IBM, AI and blockchain can help identify patient data, uncover patterns, and collaborate between organizations (including through patient data on the blockchain) to improve patient care and enable them to to decide for themselves with whom they share their sensitive data. For example, according to Cryptopolitan, the MedRec platform uses blockchain to securely share health data, as well as AI for predictive analytics.
In the Pharmaceutical industry Blockchain and AI can contribute to transparency and traceability in the medication supply chain. “Combining intelligent data analytics with a decentralized clinical trial framework enables data integrity, transparency, patient traceability, consent management and automation of trial participation and data collection,” IBM reports.
According to Cryptopolitan, AI-controlled decision-making processes are also increasingly becoming established within Decentralized Autonomous Organizations (DAOs). Smart contracts would “execute actions based on real-time data and AI predictions,” optimizing governance and resource allocation.
In energy trading, the combination of blockchain and artificial intelligence could promote sustainability. According to Cryptopolitan, renewable energy producers can record energy production and transactions on the blockchain, while AI algorithms could optimize energy distribution by predicting demand and efficiently managing resources.
Challenges and possible solutions
Of course, integrating AI into blockchain networks also comes with some challenges. One of the biggest, according to Cryptopolitan, is scalability. The size of AI calculations could strain the capacity of the network, resulting in slower processing of transactions and increased congestion. Another critical issue is data protection when using artificial intelligence in a public blockchain. The “lack of seamless interoperability between blockchain platforms and AI systems” also poses a challenge. In addition, the integration of AI into blockchain networks could increase criticism of the technology’s high energy consumption, particularly with regard to resource-intensive AI calculations.
According to Cryptopolitan, possible solutions in terms of scalability could be sharding or layer 2 solutions. Dividing the blockchain into smaller segments or separating AI calculations from the main chain could avoid congestion and improve scalability. Regarding data protection, AI models and sensitive data could be encrypted before being stored on the blockchain, or zero-knowledge proofs could be used “to perform calculations on encrypted data without revealing the underlying information,” Cryptopolitan reports. With regard to interoperability, there is an opportunity to support industry-wide standardization initiatives or to develop interoperability solutions yourself to facilitate data exchange. In order to keep energy consumption as low as possible, one could switch from energy-intensive consensus mechanisms (e.g. proof-of-work) to more energy-efficient ones (e.g. proof-of-stake). In addition, AI calculations could also be carried out outside the blockchain or on special sidechains.
One thing is certain: the combination of blockchain and artificial intelligence opens up numerous new possibilities. First, however, it remains to be seen whether the technologies will actually grow together, or remain separate and merely complement each other, and where they will be used and in what form.
Editorial team finanzen.net