Blockchain
Blockchain is a shared, immutable ledger that provides an immediate, shared and transparent exchange of encrypted data simultaneously to multiple parties as they initiate and complete transactions.
Since members share a single view of the truth, they gain confidence and trust in their transactions with other members, along with new efficiencies and opportunities.
Artificial Intelligence
Artificial intelligence (AI) uses computers, data and sometimes machines to mimic the problem-solving and decision-making capabilities of the human mind.
AI encompasses the sub-fields of machine learning and deep learning, which use AI algorithms that are trained on data to make predictions or classifications.
1. Combined values of Blockchain and AI
Autonomous system
The decentralized ledger technology ensures that no single server handles all the operations of the AI application. The autonomous system drives the decentralization for managing the AI training and operations without being supervised.
Privacy protection
Cryptographic techniques strengthen privacy throughout the network which runs AI training and operations. When you have a robust privacy system you can train and supply AI systems as they are competitive and have higher complexity.
Authenticity
Blockchain’s digital record offers insight into the framework behind AI and the provenance of the data that it is using, addressing the challenge of explainable AI. This insight helps improve trust in data integrity and in the recommendations that AI provides. Using blockchain to store and distribute AI models provides an audit trail, and pairing blockchain and AI can enhance data security. On the other hand, AI can be used to verify and determine the accuracy and reliability of data, and to automatically structure the data in a way that is compatible with smart contracts.
Augmentation
AI can rapidly and comprehensively read, understand and correlate data at incredible speed, bringing a new level of intelligence to blockchain-based business networks. By providing access to large volumes of data from within and outside of the organization, blockchain helps AI scale to provide more actionable insights, manage data usage and model sharing, and create a trustworthy and transparent data economy.
Improved security of decentralized protocols: Blockchain is known for its security properties because of its decentralized and immutable settlement layer. AI can augment these security measures by near-instantly detecting any potential threats in a blockchain protocol. Smart contracts can leverage AI to identify vulnerabilities and enhance encryption methods.
Enhance scalability of blockchain networks: The blockchain trilemma refers to the problem of achieving scalability in blockchains without compromising their security or decentralization. AI can help reduce this problem by predicting and managing network loads, enabling adjustments that optimize the network’s performance. AI’s predictive capabilities can forecast future demands on the network and thus assist in prioritizing resource allocation.
2. Use cases for Blockchain and AI
Healthcare:
AI can help advance almost every field in healthcare, from surfacing treatment insights and supporting user needs to identifying insights from patient data and revealing patterns. With patient data on blockchain, including electronic health records, organizations can work together to improve care while protecting patient privacy.
Supply chain:
By digitizing a largely paper-based process, making the data shareable and trustworthy, and adding intelligence and automation to execute transactions, AI and blockchain are transforming supply chains across industries and creating new opportunities. For example, a manufacturer can track carbon emissions data at the product or parts level, adding accuracy and intelligence to decarbonization efforts.
Smart Contract Optimization:
AI solutions can make smart contracts more efficient by analyzing historical data and using predictive analytics to foresee any challenges to executing contract conditions. Natural language processing can allow smart contracts to decipher and process human legal contracts.
Asset Tokenization:
While blockchain can be used to tokenize real-world assets like stocks and art, AI can be deployed to analyze provenance data, asset conditions, and market trends to calculate the value of each token. Moreover, machine learning can analyze real-time data feeds and continuously update the asset’s tokenized value. Solulab, a California-based AI and blockchain solutions company, provides services to convert real-world assets into digital tokens.
Market Trends and Prediction:
AI can identify patterns and correlations in crypto historical data to predict future price movements. Investors can use this information to bet against future market corrections or hedge their investments. Neureal is an example of a prediction engine that analyzes trends and leverages AI and blockchain to forecast everything from Google searches to stock markets.
Data Integrity:
AI can verify off-chain data sources that feed into smart contracts to verify their accuracy before the data can be stored on-chain. For instance, AI-powered smart contracts can interpret complex legal terms and conditions, reduce legal ambiguities, and ensure compliance with regulatory frameworks. Blackbird.AI is a tool that uses AI to verify off-chain news content for companies in the communication and information space and uses blockchain to store the verified content.
Decentralized Autonomous Organizations (DAOs)
AI can make decisions for DAOs, and Blockchain ensures a transparent and secure record of all actions taken by the organization.
Identity Verification and Authentication
AI's facial recognition and biometric capabilities, coupled with Blockchain's secure storage, provide a trustworthy solution for identity verification.
Predictive Finance
AI's analysis of financial data predicting market trends, combined with Blockchain's secure and transparent recording of financial transactions, creates a potent tool for financial forecasting.
3. Differences between Blockchain and AI
Core Concepts: Analyzing Vs. Recording
AI involves analyzing and interpreting data, making informed decisions, and predicting outcomes. In contrast, Blockchain technology revolves around a decentralized ledger that securely stores and verifies data. While AI delves into the realms of cognition, Blockchain is anchored in the immutable recording of information.
Data Handling Approaches: Learning Vs. Distributing
AI algorithms necessitate large datasets for training and learning, while Blockchain distributes data across a decentralized ledger. The former seeks insights and predictions, while the latter focuses on creating a secure and transparent transaction record.
Applications: Versatility Vs. Immutability
AI's applications span diverse domains, from medical diagnostics to language translation. Blockchain, on the other hand, finds its strength in providing immutable and transparent records, often associated with financial transactions and supply chain management.
Historical Context: AI's Age-Old Presence Vs. Blockchain's Recent Emergence
AI predates Blockchain by several decades. Its roots trace back to the 1956 Dartmouth Workshop, often regarded as its birthplace. In contrast, Blockchain emerged in 2008 with the creation of Bitcoin. Despite its youth, Blockchain has rapidly become a disruptive force.
4. Challenges of AI in Blockchain
Inadequate data privacy frameworks and standards: Effective regulatory frameworks are needed to ensure AI integration into blockchain meets all ethical and legal standards. Moreover, developing standards for AI-backed decentralized applications is necessary to ensure user privacy and promote user trust. Ethical concerns around AI bias: AI models are susceptible to learning human biases from training data and can amplify these biases. Encoding these biases into an immutable ledger may result in systematic flaws and raise serious ethical issues. Lack of clear mechanisms for AI interoperability: AI models have traditionally struggled to pull and read data from external sources. For AI systems to integrate into blockchain networks, standardized protocols and interfaces are needed to share data effectively.
5. The cultural and economic impact
In the narrative of our digital evolution, Generation Z emerges as the vanguard of a new cultural epoch. Born into a world where virtuality is as real as the air they breathe, these digital natives are the first to fully immerse themselves in the fruits of technological convergence. Their initial forays, playful and experimental in creating memes and digital artifacts, are but the prologue to a deeper, more significant shift. With tools shaped by AI and the metaverse at their fingertips, they are not just using technology; they are reshaping it, bending the digital universe to their imagination and whims. We see these young minds not just embracing but mastering the art of creation within these new realms. They are the pioneers of a world where user-generated content is not just a pastime but a new economic frontier. In their hands, creativity and innovation become more than expression; they are the keys to unlocking new forms of value and influence. The power once held by a select few in coding and legal intricacies is now democratized in the hands of these youthful creators, heralding a future where the digital realm is limited only by imagination.
6. In 2024
As 2024 comes to close, we are at the cusp of a transformative era in technology. The integration of AI, blockchain, and virtual reality is crafting a new digital landscape. This convergence is more than a mere amalgamation of technologies; it's a revolution in how we interact with the digital realm. AI's advancement is redefining creative possibilities in the metaverse, enabling environments to be moulded by thought alone. Blockchain evolves into a fundamental layer of digital trust, making asset ownership seamlessly part of the internet's fabric. Virtual reality, on the brink of a breakthrough, is set to radically change our sensory experiences in digital spaces.
Crucially, this technological synergy is the playground of Generation Z, who are not just users but active creators and shapers of these realms. Their engagement with these technologies is not just about leisure; it's the forging of a new economic and cultural landscape where imagination is the primary currency. In this new era, the limits of the digital world are defined only by our creativity, opening unprecedented avenues for innovation and interaction. The year 2024 marks the beginning of this exciting journey, promising a future where technology and imagination converge to expand the boundaries of what is possible.
Author:
Alexis Nicolaou,
Distributed Ledger Technologies Services Leader,
Grant Thornton Cyprus