We often see AI and blockchain portrayed as competitors for the spotlight and investor funds. Yet, it’s more fitting to see them as partners in innovation. When these two groundbreaking technologies come together, they have the potential to create a powerful synergy, overcoming some of the inherent limitations in their respective paths.
Watching AI and blockchain develop is like watching the popular kids in school. Both have significantly influenced our vision of the future and have been trying to outshine each other since the start of the year. Blockchain, despite being in the limelight for over a decade and promising financial empowerment to individuals, has faced challenges, including unfulfilled promises and numerous hacks.
On the other hand, AI, the newer star of the class, has attracted billions in investments and is growing in popularity, but it has its bag of issues, such as concerns about its impact on our lives and the difficulty of distinguishing real from AI-generated content.
Some have argued cryptocurrency is yesterday’s news and AI is the next big thing. But instead of putting them in a face-off, it’s evident when delving into their core capabilities that they can enhance each other’s strengths and offset limitations. Together, they lay the foundation for a secure and efficient digital realm.
AI’s rapid rise and its trust challenges
AI, once just a futuristic concept, rapidly rose to dominance with ChatGPT hitting 1 million daily users in just five days and a projected over 8.4 billion AI devices globally by 2024.
However, this rapid ascent caught many unprepared. With AI’s increasing use, people often question if the content they encounter is genuine or AI-generated, leading to widespread distrust in online information, with over 75 per cent expressing concerns about misinformation.
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Recently, governments worldwide are rapidly developing AI regulations, with China setting security standards for AI-powered services and the EU focusing on rules for AI use in biometric surveillance and systems like ChatGPT.
The AI landscape faces another critical challenge: centralisation in development. This is a cause for concern because it could lead to a situation similar to what happened with search engines and social media, where large companies Microsoft, OpenAI, and Google ended up controlling the vast amounts of user data that had been accumulated.
Relying on centralised models widens the gap between resource-rich companies and the broader market. Consequently, this not only perpetuates a ‘rich get richer’ cycle, where these companies have the resources and expertise to reap AI rewards, but it also places too much power and control in the hands of a few. All of these trends combined are causing a growing distrust in AI.
Blockchain can help
People should be able to use AI tools without worrying about encountering fakes, scams, or data accuracy issues. AI tools should be easily comprehensible, impartial, unbiased, and transparent. Blockchain technology can make this happen.
Blockchains, rooted in cryptography and security, establish trust through a decentralised, immutable, and continuously growing digital ledger. This ledger comprises ordered records (blocks) linked with cryptographic hashes, timestamps, and transaction data. Altering any part of it requires changing all subsequent blocks and gaining network consensus.
Similar to how a certificate authority verifies website security, blockchain can serve as a certifying agent for digital creations in real-time, providing assurance in a world where authenticity is crucial.
In the 2016 US presidential election, X (formerly Twitter) bots disseminated false information by targeting influential users. Centralised websites also posted articles that weren’t fact-checked and were vulnerable to hacking and misinformation.
However, blockchain can effectively address this problem. For example, in 2020, the Associated Press used blockchain oracles to track US presidential election race calls on the chain for the first time. The AP published election results on Ethereum, creating an unhackable and permanent record of state-by-state results.
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On top of that, it released the smart contract address to allow readers to use block explorers like Etherscan to track results in real-time. This approach will become even more critical as AI now makes it easier to spread misinformation and attempt hacking.
Furthermore, blockchain can address AI’s centralisation issue, as seen in projects like Ocean Protocol, which utilise blockchain and tokens along with its compute-to-data technology. It enables data providers to monetise their data while maintaining privacy and control and for consumers to purchase previously inaccessible data. This decentralises AI workflows, as AI and its machine learning algorithm need data to work.
Blockchain needs AI for an accessibility upgrade
AI technology has risen to prominence for good reasons. AI tools, such as ChatGPT, are user-friendly, with no downloads or signups required. Also, developers find it accessible through APIs from major players like Google and AWS.
On the flip side, the blockchain world seems like it’s still finding its way, with a notable gap between hype and reality. Its intricate user interface poses difficulties in welcoming new users, while those already involved must navigate through untested products and over-optimistic business models. This situation exposes them to public scrutiny and encourages criticism and scepticism.
Imagine if the integration of AI into blockchain projects could facilitate the onboarding of the next wave of users, offering a simplified user experience, a clearer understanding of projects, and a more developer-friendly environment.
AI can simplify user experiences in the Web3 space by assisting in understanding crypto-specific terms like “smart contracts,” “seed phrases,” and “wallets”. Blockchain projects are able to deploy virtual AI assistants trained on Web3 knowledge and built-in search prompts to guide users through actions and explanations.
Additionally, AI can analyse on-chain data for optimal strategies. Instead of sifting through resources like CoinGecko and DeFiLlama, AI tools can provide quick access to information like Bitcoin’s highest price this month or top-performing tokens with a market cap of over US$100 million. This speeds up individual research to the level of larger teams with bigger resources and budgets for more hires.
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Similarly, developers who often have to deal with a scattered assortment of technical resources will also find AI advantageous for streamlining product development. For instance, AI can look at blockchain transaction movements and assist in comprehending the flow of funds, especially following security breaches.
Looking ahead
Recently, we’ve witnessed significant progress in recognising and implementing collaborative blockchain and AI solutions: Congressman Tom Emmer has acknowledged the role of blockchain in content authentication, and Microsoft partners with Aptos to deploy AI and blockchain offerings. From politicians to major tech companies, there’s growing recognition, and more efforts are being made to bring AI and blockchain closer together.
The symbiotic relationship of AI and blockchain is not a matter of “if” but “when.” As our reliance on AI continues to grow, so does the need for trust in digital information. Blockchain is an effective solution to address the trust challenges in the digital age. Its ability to securely record data origins provides the much-needed proof of authenticity required in the era of AI.
Simultaneously, AI can enhance blockchain with user-friendly interfaces and streamline technical resources for developers. We’re optimistic about this fusion and its potential to shape a more transparent and reliable Web3 future.
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