AI crypto projects are proliferating as the technology’s potential reshapes the investment landscape.
From AI models on Bitcoin to AI training data on layer 2 blockchains, tokens related to AI crypto projects are extremely popular in the altcoin space.
It reflects broader market conditions. Hot stock Nvidia (NVDA.O) has been making headlines since last year and has added AI to its investment portfolio.
The stock's market value reached more than $1 trillion, making it the seventh public company in the United States to reach that milestone.
As of March 2024, with a market capitalization exceeding $2 trillion, it becomes the third most valuable company in the world after Microsoft and Apple.
Investor demand for exposure to machine learning technologies is growing at a pace that is rivaling that of the world’s largest companies.
As of now, the market capitalization of AI Token is $26.4 billion. In April last year, this figure was only $2.7 billion.
CoinDesk Indices’ computational index, which includes AI-related tokens, has grown in value by more than 165 percent over the past year.
At the end of February, trading volume hit an all-time high of $3.8 billion.
While many investors are chasing price increases, AI-related crypto tokens offer a cryptocurrency opportunity that is uncorrelated to cryptocurrencies themselves. Arguably, the value of these tokens may be more correlated to the rise and fall of the AI industry than to cryptocurrencies.
Investment management firm VanEck predicts that by 2030, AI cryptocurrency revenue could reach a staggering $10.2 billion, with uses similar to non-AI cryptocurrency projects, including reward tokens, physical computing infrastructure, data verification, provenance, etc.
To be sure, the AI and blockchain revolution is still in its infancy. How the merger of these two exciting industries will play out is unclear. For example, Bitcoin maximalists believe that the entire cryptocurrency index could go to zero.
There is a long list of possible uses for AI tokens: payments, trading models, machine-generated non-fungible tokens (NFTs), and blockchain-based AI application marketplaces.
In theory, blockchain improves the security of the protocol through a decentralized and immutable settlement layer.
AI can detect risks in real time and provide an extra layer of security for network security by monitoring network activities, analyzing historical data and source information, and asset status to detect anomalies. It uses predictive analysis technology to make smart contract conditions more efficient and deeply analyze asset source data, status, and market trends.
Imagine a system where these two emerging technologies extract and validate data while managing network load.
Blockchain can serve as a public record of AI training.
AI algorithms improve threat detection and response capabilities; while the immutability of blockchain provides a strong defense for security-related data, which, combined with a decentralized data management approach, can effectively defend against cyber threats.
Once AI-verified information is recorded on the blockchain, it cannot be altered or deleted.
Nonetheless, the merger of AI and blockchain presents new threats.
The risks of AI and blockchain
On March 21, the United Nations General Assembly adopted a global artificial intelligence (AI) resolution to promote the development of "safe, secure and trustworthy" AI.
On March 13, the European Parliament passed an AI bill setting governance standards for the European Union.
Additionally, the European Commission has launched an investigation into the use of AI.
The Biden administration noted safety and security concerns with the development of AI in an October 2023 executive order.
Meanwhile, India introduced AI requirements in March ahead of its general election.
AI and blockchain, whether used alone or in combination, pose privacy and security risks. Vast amounts of sensitive data may one day depend on the security of AI-blockchain applications, and it remains unclear how these applications will be protected.
AI requires a lot of data to learn, predict and act. Over time, this data may contain more and more personal information, which increases the risk of privacy leakage. However, blockchain technology can reduce this risk by anonymizing data transactions. It uses technical means such as zero-knowledge proof to protect personal identity information while generating data records that cannot be tampered with and are usually open to the public.
Data recorded on a public blockchain cannot be deleted by anyone, which conflicts with privacy norms and laws such as the “right to be forgotten.”
AI could theoretically act on data secured by a blockchain without human oversight, raising major questions about consent and privacy.
Promoting beneficial innovation
In order to harness blockchain and AI without creating a dystopia, the world must adhere to ethical principles and safety standards to ensure that these technologies ultimately serve the best interests of humanity and address our most pressing needs.
Collaboration between developers, ethicists, and policymakers is needed to clearly define the boundaries of AI behavior and data integrity on blockchain networks. Developers must design innovative solutions to protect privacy and security in the new digital realm.
To ensure that AI and blockchain systems are designed with social impact in mind, principles of transparency, accountability, and inclusiveness need to be followed. #区块链 #人工智能
