By Ken Akure | 09 June, 2023 |
Cryptocurrencies transformed the financial landscape by enabling decentralised, peer-to-peer, transparent, and secure transactions. The nascent nature of the cryptocurrency ecosystem, however, brings with it its own set of issues, such as fraud and the need for advanced analytics. Most recently, artificial intelligence (AI) has risen as an emergent technology influencing key areas of business and finance, and the blockchain has not been left behind by its disruptive possibilities.
In this article, we will explore the various ways in which AI is currently influencing and may continue to shape the blockchain space.
AI + Blockchain Tech
Blockchain technology underlies cryptocurrencies like Bitcoin and Ethereum, providing transparency and trust. However, the nature of this technology and its large user base have led to increasingly slower networks, rising network fees, and overall scalability issues. The combination of AI advancements in natural language processing (NLP), machine learning, and data analysis holds great potential for a breakthrough in this regard by enhancing the performance of blockchain networks and addressing security and scalability challenges.
Benefits of AI to Blockchain Tech
There are several key areas in which AI can significantly impact the blockchain space:
Enhancing Security: The decentralised nature of cryptocurrencies and their lack of clear regulation in most jurisdictions make them appealing to cybercriminals and fraud. Traditional fraud detection technologies are having difficulty keeping up with developing strategies. However, AI integration offers a possible solution by using its powers to analyse massive volumes of data and spot patterns suggestive of fraudulent behaviour. New cybersecurity platforms are already leveraging the power of AI on the blockchain to provide more secure user experiences. Platforms like Deeper Network are now popular for their AI-driven privacy and security offerings.
AI-Powered Blockchain Analytics: Blockchain technology creates an immutable and transparent ledger of all cryptocurrency transactions. AI can use this data to obtain useful insights and detect trends that human analysts may miss. Predictive analytics is one area where AI outperforms conventional technologies. AI algorithms, particularly machine learning models, can learn from historical data to assist the industry with real-time blockchain analytics.
Leading agencies like Elliptic have already integrated ChatGPT into their off-chain intelligence processes. With access to over 97% of crypto transactions by trading volume and the largest collection of crypto exchange risk profiles in the world, this ChatGPT integration can provide a holistic view of risk within the blockchain industry. What this means is that AI can help prevent all the vulnerabilities that occur when assets are transferred between blockchains. Preventing everything from security breaches to transaction failures, and interoperability challenges.
AI-Enhanced Smart Contracts: Smart contracts provide cost-effectiveness and tamper-proof attributes. However, their rigid structure hinders their ability to rapidly adapt to change. AI can improve smart contracts by increasing their responsiveness, making them adapt to changing situations or new information. For example, AI can update contract terms in real-time based on financial market conditions or investment performance.
New arrivals like the Cortex Blockchain allow users to purchase AI models that can be integrated into smart contracts to increase their adaptability. This enables the smart contract to cater to the individual demands of the parties participating in an agreement even when changes occur.
Potential Disadvantages of AI on the Blockchain
While AI enhances the capabilities of the blockchain, there are potential disadvantages to consider:
Firstly, AI algorithms are only as good as the data on which they are trained, and biased or inadequate training data may result in false positives or negatives in fraud detection. Furthermore, AI-powered systems may experience difficulties adjusting to new and sophisticated fraud schemes, necessitating ongoing upgrades and improvements.
Secondly, if market conditions change quickly or unforeseen events occur, predictive algorithms may fail to effectively predict future trends. Furthermore, as AI algorithms improve in complexity, there is a concern that algorithmic trading may dominate the market, potentially worsening price volatility.
Finally, the use of AI in smart contracts complicates the development and implementation process, necessitating specialised knowledge and skills. Furthermore, relying on data for AI decision-making poses the possibility of biased or erroneous contract term modifications. Security risks may occur as a result of potential weaknesses in AI algorithms that can be exploited, jeopardising the contracts’ integrity. The application of artificial intelligence in smart contracts will also generate new regulatory concerns, demanding careful adaptation of existing frameworks to ensure compliance and responsibility.
Conclusion: The application of AI in the blockchain and crypto space will continue to grow as technology advances, providing greater security and analytics and opening up new risks as well as opportunities for stakeholders. These benefits will fundamentally impact the present crypto ecosystem and redefine blockchains to a new degree of efficiency and decentralisation.
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